Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
AbstractObjectiveTo assess the predictive value of the initial clinical and paraclinical features in the differentiationof inflammatory myelopathies from other causes of myelopathy in patients with initial diagnosisof transverse myelitis (TM)
MethodsWe analyzed the clinical presentation spinal cord MRI and CSF features in a cohort of 457patients referred to a specialized myelopathy center with the presumptive diagnosis of TMAfter evaluation the myelopathies were classified as inflammatory ischemicstroke arterio-venous malformationsfistulas spondylotic or other A multivariable logistic regression modelwas used to determine characteristics associated with the final diagnosis and predictors thatwould improve classification accuracy
ResultsOut of 457 patients referred as TM only 247 (54) were confirmed as inflammatory theremaining 46 were diagnosed as vascular (20) spondylotic (8) or other myelopathy(18) Our predictive model identified the temporal profile of symptom presentation (hy-peracute lt6 hours acute 6ndash48 hours subacute 48 hoursndash21 days chronic gt21 days) initialmotor examination and MRI lesion distribution as characteristics that improve the correctclassification rate of myelopathies from 67 to 87 (multinomial area under the curve in-creased from 032 to 067) compared to only considering CSF pleocytosis andMRI gadoliniumenhancement Of all predictors the temporal profile of symptoms contributed the most to theincreased discriminatory power
ConclusionsThe temporal profile of symptoms serves as a clinical biomarker in the differential diagnosis ofTM The establishment of a definite diagnosis in TM requires a critical analysis of the MRI andCSF characteristics to rule out non-inflammatory causes of myelopathy
Classification of evidenceThis study provides Class IV evidence that for patients presenting with myelopathy temporalprofile of symptoms initial motor examination and MRI lesion distribution distinguish thosewith inflammatory myelopathies from those with other causes of myelopathy
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Class of evidenceCriteria for ratingtherapeutic and diagnosticstudies
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PodcastDr Stacey Clardyinterviews Dr Carlos Pardoabout his paper on clinicalbiomarkers and differentialdiagnosis of myelitis
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From the Department of Neurology (PB KCF MAM DB SDN ML CAP) and Division of Interventional Neuroradiology (PG) Johns Hopkins University School of MedicineBaltimore MD Universidad de Antioquia ( JAJ) Neuroclinica ( JAJ) Medellin Colombia and International Neurorehabilitation Institute (DB) Lutherville MD
Go to NeurologyorgN for full disclosures Funding information and disclosures deemed relevant by the authors if any are provided at the end of the article
The Article Processing Charge was funded by The Bart McLean Fund for Neuroimmunology Research and the Transverse Myelitis Association
This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 40 (CC BY-NC-ND) which permits downloadingand sharing the work provided it is properly cited The work cannot be changed in any way or used commercially without permission from the journal
e12 Copyright copy 2017 The Author(s) Published by Wolters Kluwer Health Inc on behalf of the American Academy of Neurology
GlossaryAUC = area under the curve AVF = arteriovenous fistulas AVM = arteriovenous malformations CCR = correct classificationrateCI = confidence intervalGd+ = gadolinium enhancement IDI = integrated discrimination increment IM = inflammatorymyelopathy LE = longitudinally extensiveMS =multiple sclerosisNMOSD = neuromyelitis optica spectrum disorderNRI =net reclassification improvement OCB = oligoclonal bands OM = other causes of myelopathy OR = odds ratio SM =spondylotic myelopathy TM = transverse myelitis VM = vascular myelopathy
Transverse myelitis (TM) is an inflammatory disorder affectingthe spinal cord TM is recognized to be a heterogeneous syn-drome which manifests with motor sensory and autonomicsymptoms attributable to spinal cord dysfunction12 The termTM has been applied broadly to myelopathic syndromes in thesetting of autoimmune demyelinating infectious and post-infectious disorders The diagnosis of TM presents a challengeto the clinician as the list of possible differential diagnoses isextensive and non-inflammatory myelopathies with neoplasticvascular compressive ormetabolic etiologic origin oftenmimicTM3ndash5 While CSF pleocytosis or lesion enhancement on MRIhave been widely used to define inflammatory myelopathiessimilar features have been reported in non-inflammatorymyelopathies3467 The overlap of clinical MRI and CSF fea-tures among the wide spectrum of myelopathies may lead to anerroneous diagnosis of TM and subsequent unwarrantedtreatments with potentially harmful immunosuppressive ther-apies and delays in adequate therapeutic measures89
We performed a detailed evaluation of different types ofmyelopathies and determined the value of the clinical featuresthe temporal profile spinal cordMRI and CSF characteristicsfor establishing a more accurate diagnosis in a group of over450 patients presenting with myelopathy
MethodsStudy design and patient populationWe retrospectively analyzed the clinical presentation initialneurologic examination and characteristics of the initial MRIand CSF profile in 457 out of 575 patients referred to a spe-cialized myelopathy center for a newly established diagnosisof TM from 2010 to 2015 A total of 118 patients wereexcluded due to lack of complete or verifiable informationregarding their initial presentation Patients referred for rea-sons other than presumed TM including those with a pre-viously established etiologic diagnosis (eg multiple sclerosis[MS] neuromyelitis optica spectrum disorder [NMOSD]spinal vascular malformations) were not included Werecorded demographic characteristics medical history andinformation on the clinical presentation including the tem-poral profile initial symptoms and the neurologic examina-tion CSF analysis and MRI features including lesiontopography at the initial assessment were analyzed As clini-cally indicated patients underwent additional studies in-cluding serologic and imaging studies (eg spinal angiogram)(see e-Methods httplinkslwwcomWNLA10)
DefinitionsThe final diagnosis was classified as inflammatory myelopathy(IM) vascular myelopathy (VM) spondylotic myelopathy(SM) or other causes of myelopathy (OM) (table 1) Thetemporal profile from symptom onset to nadir neurologicdysfunction was classified as hyperacute (lt6 hours) acute(6ndash48 hours) subacute (gt48 hoursndash21 days) or chronic (gt21days) Nadir was defined as the point of worst neurologicfunction before improvement or plateau based on historyand neurologic examination Features of the initial pre-sentation were confirmed during the clinical visit interview
Statistical analysisOur analysis had 2 aims to (1) assess descriptively howspecific characteristics are associated with myelopathies ofdifferent etiologies and (2) derive a subset of predictors thatimprove the prediction accuracy of identifying etiologic originof a given myelopathy For the first stage we grouped char-acteristics into 5 sets of potentially relevant predictorsdemographicmedical history (age sex ethnicity smokingstatus obesity hypertension diabetes dyslipidemia autoim-mune disease infection in the last 30 days vaccination in thelast 90 days) clinical presentation (temporal profile presenceof motor sensory or bladderbowel symptoms new onsetback pain worsening by exercise) neurologic examination(motor examination sensory abnormality presence of urinaryretention or abnormal rectal tone reflexes) MRI (sagittallesion location and extension gadolinium enhancement [Gd+] multifocality axial lesion topography) and CSF (pleocy-tosis protein immunoglobulin G index and oligoclonalbands [OCB]) For each group of predictors we fit a multi-nomial regression model where we considered each mye-lopathy type as an outcome Models for MRI and CSFfeatures were adjusted for time to MRI or time to lumbarpuncture
Our second objective was to evaluate after accounting forGd+ and pleocytosis whether a subset of predictors wouldimprove accuracy in discriminating the different myelopathycategories We focused on estimation of the multinomial-generalized integrated discrimination increment (IDI)a measure of separation of the predicted probabilities for eachtype of event and the net reclassification improvement(NRI) the proportion of participants correctly vs incorrectlyclassified between 2 models as measures that estimateprediction increment of new variables15 (see e-MethodshttplinkslwwcomWNLA10) Statistical analyses were
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Table 1 Definitions of diagnostic categoriesa
Myelopathy A clinical syndrome characterized by motor sensory or autonomic symptomsattributable anatomically to spinal cord dysfunction
Inflammatory myelopathy Myelopathy meeting the diagnostic criteria for known specific inflammatory disordersincluding MS10 NMOSD11 sarcoidosis12 and rheumatologic myelopathies13 when otheralternative etiologies were ruled out or meeting criteria for idiopathic TM2
Vascular myelopathy related to ischemic disease (strokes)
Definite bull Myelopathy
bull MRI hyperintense lesion in a defined vascular territory or watershed areab on T2-weighted images
bull Vascular abnormality demonstrated on spinal angiogram explanatory of the clinicalpresentation
bull Exclusion of other etiologies
Probable bull Myelopathy
bull MRI-hyperintense lesion in a defined vascular territory or watershed area on T2-weighted images
bull Spinal angiogram negative or not available
bull Positive DWI or known stroke risk factors or mechanism explanatory of the clinicalpresentation (ie severe hypotension hypercoagulable state)
bull Exclusion of other etiologies
Possible bull Myelopathy
bull MRI hyperintense lesion in a defined vascular territory or watershed area on T2-weighted images
bull Spinal angiogram and DWI negative or not available
bull No identifiable risk factor or mechanism
bull Exclusion of other etiologies
Vascular myelopathy associated with AVMAVF
Definite bull Myelopathy
bull MRI hyperintense lesion in the spinal cord on T2-weighted images
bull Angiogram proven AVM or AVF
bull Exclusion of other etiologies
Probable bull Myelopathy
bull MRI hyperintense lesion in the spinal cord on T2-weighted images
bull MRI vasculature abnormality consistent with AVF or AVM (prominent flow voids)
bull Spinal angiogram not available
bull Exclusion of other etiologies
Spondylotic myelopathy Myelopathy withMRI hyperintense lesion in the spinal cord on T2-weighted images in theregion of spine degenerative changes such as disc herniation spondylolisthesis cervicalstenosis or osteophyte mass effect and where other causes were ruled out
Other myelopathiesc Non-inflammatorymyelopathies not meeting criteria for the above diagnostic categories
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations DWI = diffusion-weighted imaging MS = multiple sclerosis NMOSD =neuromyelitis optica spectrum disorder TM = transverse myelitisa For a diagnosis to be made all the conditions in the definition need to be metb Arterial territory supplied by sources flowing in opposite directions includes the upper thoracic region isolated graymatter and the posterior lumbosacralwatershed area14c Includes myelopathies of metabolic neoplastic infectious and unknown etiology
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implemented with R version 322 (httpswwwr-projectorg) This study provides Class IV evidence that for patientspresenting with myelopathy temporal profile of symptomsinitial motor examination and MRI lesion distribution dis-tinguish those with inflammatory myelopathies from thosewith other causes of myelopathy
Standard protocol approvals registrationsand patient consentsThe institutional review board at Johns Hopkins Hospital ap-proved the study and waived patient consent (IRB00115274)
ResultsPatient populationA total of 457 patients (58 female median age 46 yearsinterquartile range 33ndash56 years) with the presumptive di-agnosis of TM were analyzed (table 2 and tables e-1 e-2 ande-3 httplinkslwwcomWNLA9) After thorough as-sessment of the clinical MRI and CSF features final di-agnoses were reclassified as IM in 247 (55) patients VM in92 (20) patients (62 ischemicstroke and 30 arteriovenousmalformations [AVM]arteriovenous fistulas [AVF]) SM in35 (8) patients and OM in 83 (18) patients For the VMischemicstroke category the diagnosis was definite in 13probable in 26 and possible in 23 patients For 28 patientswith AVMAVF the diagnosis was definite 2 patients withprominent flow voids on MRI and a compatible clinicalprofile declined angiography and were classified as probableVM-AVMAVF
Demographics and medical historyThe majority of patients were Caucasian in all categoriesRelative to the inflammatory group AVMAVF and SM weremore likely with increasing age (for AVMAVF odds ratio[OR] per 10 years increment 178 95 confidence interval[CI] 134ndash244 for SM OR 204 95 CI 15ndash288) AVMAVF and SM were more common in men than in women (forVM-AVMAVF OR 504 95 CI 181ndash1407 for SM OR309 95 CI 129ndash735) A history of autoimmune diseasewas less frequent in the VM-ischemicstroke group comparedto IM (OR 025 95 CI 007ndash089) and while a history ofa preceding infection was more frequent in IM this was notstatistically significant in multivariate analysis (figure 1 andtable e-1 httplinkslwwcomWNLA9)
Temporal profileIM presented more often with a subacute temporal profile(55) Relative to IM VM-ischemicstroke exhibited morefrequently a hyperacute profile (89 OR 3519 95 CI892ndash13890) in contrast to VM-AVMAVF SM and OMwhich were significantly more likely to exhibit a chronic pat-tern (83 86 61 respectively all OR gt 3)
Initial symptomsThe presence of acute excruciating back pain at onset wasassociated with the VM-ischemicstroke group relative to IM
(OR 730 95 CI 221ndash2411) bladderbowel dysfunctionand symptom worsening with exercise were associated withthe VM-AVMAVF relative to IM (for bladderbowel dys-function 412 95 CI 137ndash1244 for worsening with ex-ercise 1399 95 CI 202ndash9711)
Neurologic examinationWhile weakness was present in the majority of patientsa higher frequency was seen in the VM group (98 table 2)In participants with VM-ischemicstroke and VM-AVMAVF flaccid weakness was substantially more common rela-tive to IM (all OR gt10) Hyporeflexia was more frequent inthe VM-ischemicstroke group (63) relative to other typesParticipants with SM or OM were less likely to have com-promised sphincters relative to IM (for SM OR 030 95 CI009ndash099 for OM 037 95 CI 018ndash980) A sensory levelwas more frequently seen in the VM-ischemicstroke andVM-AVMAVF groups (79 70) as compared with the IMSM and OM groups (50 51 and 49 respectively) In allcategories the most frequent sensory level was thoracic
MRI characteristicsLongitudinally extensive myelopathy (LE 3 or more vertebrallevels in length) was observed in all groups but most fre-quently in the VM group (ischemicstroke 60 AVMAVF70) For VM-ischemicstroke this was significantly morefrequent when compared to IM (OR 387 95 CI115ndash1302) Almost half of the IM and SM lesions (44 and46 respectively) exhibited LE The likelihood of multifocallesions was higher in the IM group relative to any other my-elopathy category All of the reclassified myelopathies wereless likely to have Gd+ (all OR lt050) relative to IM howevernotably this finding was not specific as 21 of the VM-ischemicstrokes 60 of the VM-AVMAVF and 46 of SMpatients category were also enhancing
The pattern of lesion distribution for each diagnostic categoryin both axial and sagittal views is shown in figure 2 The IMlesions affected more frequently the posterolateral spinal cordrelative to all other myelopathy groups (all OR lt10) and werelocated more often in the cervical and upper thoracic spinalcord (C1-T6) Lesions in the VM-ischemicstroke group weremore frequently anterior (67) these lesions were involvingmore commonly the cervical cord and the lower thoracic spinalcord SM lesions tended to locate in the central spinal cord(77 OR relative to IM 459 95 CI 150ndash140) and to bemore frequently cervical Lesions involving the conus medul-laris were more common in VM-AVMAVF than IM (OR1923 95 CI 335ndash11038) these lesions were less likely toinvolve the posterior cord relative to IM (OR 019 004ndash076)and were more frequently central (77)
CSF featuresThe laboratory profile of the initial CSF obtained after theonset of symptoms was available for 390 patients Pleocytosiswas observed more frequently in the IM group (57) how-ever it is worth noting that pleocytosis was also present in
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Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya
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a substantial proportion of VM-AVMAVF (35) and VM-ischemicstroke (17) Moreover 43 of the patients whomet the criteria for IM did not exhibit pleocytosis Elevatedprotein was more frequently observed in the VM-AVMAVFand SM group (74 and 45 respectively) OCB were al-most exclusive of the IM group although they were onlypresent in 45 of patients tested Participants with VM-ischemicstroke were less likely to have pleocytosis or OCBrelative to IM (all ORs lt1)
Prediction model for identifying diagnosticcategory of myelopathiesOur predictive model selected the following predictors ascharacteristics that improve discriminatory power for identi-fying the correct diagnostic category of a given myelopathytemporal profile of symptoms motor examination findingsconus medullaris involvement and presence of posteriorspinal cord lesions (table 3) By including these 4 additionalcharacteristics the correct classification rate (CCR) increasedfrom 67 to 87 and the multinomial area under the curve(AUC) increased from 032 to 067 suggesting markedimprovements in the correct classification of a given mye-lopathy NRI (34) and IDI (38) values associated with thispredictor set are also notable as both the CCR and AUC aresensitive to the differences in the prevalence of underlyingoutcomes This suggests improved classification and moresuccinct separation in prediction of diagnostic categories ofgiven myelopathies relative to only considering Gd+ and
pleocytosis (typically used to define IM) Of all the predictorsconsidered the temporal profile contributed to the largestchanges in IDI NRI and CCR relative to the traditionalmodel (Gd+ and pleocytosis) By including the temporalprofile only (and no other predictor) the CCR is 068 and themultinomial AUC is 03916 Relative to the null model (nopredictors) inclusion of the temporal profile results in animproved integrated discrimination index of 15 (12ndash19)and improved net reclassification index of 15 (2ndash28)(table e-4 httplinkslwwcomWNLA9) Results of oursensitivity analyses (derivation of a prediction model onlyconsidering demographics clinical presentation and neuro-logic examination and no additional MRI findings) were con-sistent Relative to a model considering Gd+ and pleocytosiswith the inclusion of motor examination findings and thetemporal profile of symptoms the CCR increased from 67 to81 and themultinomial AUC increased from 032 to 060 IDI(26) and potentially NRI (22) similarly suggested im-proved discriminatory power associated with the inclusion ofthe temporal profile and motor examination findings
DiscussionThe broad differential diagnosis of TM makes it necessary todevelop strategies that accurately distinguish among the dif-ferent etiologies of myelopathy Our study which is thelargest known cohort evaluating patients with presumed TM
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya (continued)
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations Gd+ = gadolinium enhancement IgG = immunoglobulin G IQR = inter-quartile range LE = longitudinally extensiveValues are n ()a Percentages include all participants in each category as the denominatorb Information for reflexes available for 444457 patientsc MRI data were obtained from first MRI available after onset of symptoms 67 were done in lt2 days 74 were done from 2 to 5 days 58 from 6 to 10 days 72from 11 to 30 days and 186 were done gt30 days after onset of symptomsd Percentages based on the total of patients tested CSF data were obtained from first CSF evaluated after onset of symptoms 53390 were obtained in lt2days 62390 were obtained from 2 to 5 days 58390 were obtained from 6 to 10 days 45390 were obtained from 11 to 30 days and 172390 were obtainedgt30 days after onset of symptoms
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e17
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
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myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
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are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
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ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
GlossaryAUC = area under the curve AVF = arteriovenous fistulas AVM = arteriovenous malformations CCR = correct classificationrateCI = confidence intervalGd+ = gadolinium enhancement IDI = integrated discrimination increment IM = inflammatorymyelopathy LE = longitudinally extensiveMS =multiple sclerosisNMOSD = neuromyelitis optica spectrum disorderNRI =net reclassification improvement OCB = oligoclonal bands OM = other causes of myelopathy OR = odds ratio SM =spondylotic myelopathy TM = transverse myelitis VM = vascular myelopathy
Transverse myelitis (TM) is an inflammatory disorder affectingthe spinal cord TM is recognized to be a heterogeneous syn-drome which manifests with motor sensory and autonomicsymptoms attributable to spinal cord dysfunction12 The termTM has been applied broadly to myelopathic syndromes in thesetting of autoimmune demyelinating infectious and post-infectious disorders The diagnosis of TM presents a challengeto the clinician as the list of possible differential diagnoses isextensive and non-inflammatory myelopathies with neoplasticvascular compressive ormetabolic etiologic origin oftenmimicTM3ndash5 While CSF pleocytosis or lesion enhancement on MRIhave been widely used to define inflammatory myelopathiessimilar features have been reported in non-inflammatorymyelopathies3467 The overlap of clinical MRI and CSF fea-tures among the wide spectrum of myelopathies may lead to anerroneous diagnosis of TM and subsequent unwarrantedtreatments with potentially harmful immunosuppressive ther-apies and delays in adequate therapeutic measures89
We performed a detailed evaluation of different types ofmyelopathies and determined the value of the clinical featuresthe temporal profile spinal cordMRI and CSF characteristicsfor establishing a more accurate diagnosis in a group of over450 patients presenting with myelopathy
MethodsStudy design and patient populationWe retrospectively analyzed the clinical presentation initialneurologic examination and characteristics of the initial MRIand CSF profile in 457 out of 575 patients referred to a spe-cialized myelopathy center for a newly established diagnosisof TM from 2010 to 2015 A total of 118 patients wereexcluded due to lack of complete or verifiable informationregarding their initial presentation Patients referred for rea-sons other than presumed TM including those with a pre-viously established etiologic diagnosis (eg multiple sclerosis[MS] neuromyelitis optica spectrum disorder [NMOSD]spinal vascular malformations) were not included Werecorded demographic characteristics medical history andinformation on the clinical presentation including the tem-poral profile initial symptoms and the neurologic examina-tion CSF analysis and MRI features including lesiontopography at the initial assessment were analyzed As clini-cally indicated patients underwent additional studies in-cluding serologic and imaging studies (eg spinal angiogram)(see e-Methods httplinkslwwcomWNLA10)
DefinitionsThe final diagnosis was classified as inflammatory myelopathy(IM) vascular myelopathy (VM) spondylotic myelopathy(SM) or other causes of myelopathy (OM) (table 1) Thetemporal profile from symptom onset to nadir neurologicdysfunction was classified as hyperacute (lt6 hours) acute(6ndash48 hours) subacute (gt48 hoursndash21 days) or chronic (gt21days) Nadir was defined as the point of worst neurologicfunction before improvement or plateau based on historyand neurologic examination Features of the initial pre-sentation were confirmed during the clinical visit interview
Statistical analysisOur analysis had 2 aims to (1) assess descriptively howspecific characteristics are associated with myelopathies ofdifferent etiologies and (2) derive a subset of predictors thatimprove the prediction accuracy of identifying etiologic originof a given myelopathy For the first stage we grouped char-acteristics into 5 sets of potentially relevant predictorsdemographicmedical history (age sex ethnicity smokingstatus obesity hypertension diabetes dyslipidemia autoim-mune disease infection in the last 30 days vaccination in thelast 90 days) clinical presentation (temporal profile presenceof motor sensory or bladderbowel symptoms new onsetback pain worsening by exercise) neurologic examination(motor examination sensory abnormality presence of urinaryretention or abnormal rectal tone reflexes) MRI (sagittallesion location and extension gadolinium enhancement [Gd+] multifocality axial lesion topography) and CSF (pleocy-tosis protein immunoglobulin G index and oligoclonalbands [OCB]) For each group of predictors we fit a multi-nomial regression model where we considered each mye-lopathy type as an outcome Models for MRI and CSFfeatures were adjusted for time to MRI or time to lumbarpuncture
Our second objective was to evaluate after accounting forGd+ and pleocytosis whether a subset of predictors wouldimprove accuracy in discriminating the different myelopathycategories We focused on estimation of the multinomial-generalized integrated discrimination increment (IDI)a measure of separation of the predicted probabilities for eachtype of event and the net reclassification improvement(NRI) the proportion of participants correctly vs incorrectlyclassified between 2 models as measures that estimateprediction increment of new variables15 (see e-MethodshttplinkslwwcomWNLA10) Statistical analyses were
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e13
Table 1 Definitions of diagnostic categoriesa
Myelopathy A clinical syndrome characterized by motor sensory or autonomic symptomsattributable anatomically to spinal cord dysfunction
Inflammatory myelopathy Myelopathy meeting the diagnostic criteria for known specific inflammatory disordersincluding MS10 NMOSD11 sarcoidosis12 and rheumatologic myelopathies13 when otheralternative etiologies were ruled out or meeting criteria for idiopathic TM2
Vascular myelopathy related to ischemic disease (strokes)
Definite bull Myelopathy
bull MRI hyperintense lesion in a defined vascular territory or watershed areab on T2-weighted images
bull Vascular abnormality demonstrated on spinal angiogram explanatory of the clinicalpresentation
bull Exclusion of other etiologies
Probable bull Myelopathy
bull MRI-hyperintense lesion in a defined vascular territory or watershed area on T2-weighted images
bull Spinal angiogram negative or not available
bull Positive DWI or known stroke risk factors or mechanism explanatory of the clinicalpresentation (ie severe hypotension hypercoagulable state)
bull Exclusion of other etiologies
Possible bull Myelopathy
bull MRI hyperintense lesion in a defined vascular territory or watershed area on T2-weighted images
bull Spinal angiogram and DWI negative or not available
bull No identifiable risk factor or mechanism
bull Exclusion of other etiologies
Vascular myelopathy associated with AVMAVF
Definite bull Myelopathy
bull MRI hyperintense lesion in the spinal cord on T2-weighted images
bull Angiogram proven AVM or AVF
bull Exclusion of other etiologies
Probable bull Myelopathy
bull MRI hyperintense lesion in the spinal cord on T2-weighted images
bull MRI vasculature abnormality consistent with AVF or AVM (prominent flow voids)
bull Spinal angiogram not available
bull Exclusion of other etiologies
Spondylotic myelopathy Myelopathy withMRI hyperintense lesion in the spinal cord on T2-weighted images in theregion of spine degenerative changes such as disc herniation spondylolisthesis cervicalstenosis or osteophyte mass effect and where other causes were ruled out
Other myelopathiesc Non-inflammatorymyelopathies not meeting criteria for the above diagnostic categories
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations DWI = diffusion-weighted imaging MS = multiple sclerosis NMOSD =neuromyelitis optica spectrum disorder TM = transverse myelitisa For a diagnosis to be made all the conditions in the definition need to be metb Arterial territory supplied by sources flowing in opposite directions includes the upper thoracic region isolated graymatter and the posterior lumbosacralwatershed area14c Includes myelopathies of metabolic neoplastic infectious and unknown etiology
e14 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
implemented with R version 322 (httpswwwr-projectorg) This study provides Class IV evidence that for patientspresenting with myelopathy temporal profile of symptomsinitial motor examination and MRI lesion distribution dis-tinguish those with inflammatory myelopathies from thosewith other causes of myelopathy
Standard protocol approvals registrationsand patient consentsThe institutional review board at Johns Hopkins Hospital ap-proved the study and waived patient consent (IRB00115274)
ResultsPatient populationA total of 457 patients (58 female median age 46 yearsinterquartile range 33ndash56 years) with the presumptive di-agnosis of TM were analyzed (table 2 and tables e-1 e-2 ande-3 httplinkslwwcomWNLA9) After thorough as-sessment of the clinical MRI and CSF features final di-agnoses were reclassified as IM in 247 (55) patients VM in92 (20) patients (62 ischemicstroke and 30 arteriovenousmalformations [AVM]arteriovenous fistulas [AVF]) SM in35 (8) patients and OM in 83 (18) patients For the VMischemicstroke category the diagnosis was definite in 13probable in 26 and possible in 23 patients For 28 patientswith AVMAVF the diagnosis was definite 2 patients withprominent flow voids on MRI and a compatible clinicalprofile declined angiography and were classified as probableVM-AVMAVF
Demographics and medical historyThe majority of patients were Caucasian in all categoriesRelative to the inflammatory group AVMAVF and SM weremore likely with increasing age (for AVMAVF odds ratio[OR] per 10 years increment 178 95 confidence interval[CI] 134ndash244 for SM OR 204 95 CI 15ndash288) AVMAVF and SM were more common in men than in women (forVM-AVMAVF OR 504 95 CI 181ndash1407 for SM OR309 95 CI 129ndash735) A history of autoimmune diseasewas less frequent in the VM-ischemicstroke group comparedto IM (OR 025 95 CI 007ndash089) and while a history ofa preceding infection was more frequent in IM this was notstatistically significant in multivariate analysis (figure 1 andtable e-1 httplinkslwwcomWNLA9)
Temporal profileIM presented more often with a subacute temporal profile(55) Relative to IM VM-ischemicstroke exhibited morefrequently a hyperacute profile (89 OR 3519 95 CI892ndash13890) in contrast to VM-AVMAVF SM and OMwhich were significantly more likely to exhibit a chronic pat-tern (83 86 61 respectively all OR gt 3)
Initial symptomsThe presence of acute excruciating back pain at onset wasassociated with the VM-ischemicstroke group relative to IM
(OR 730 95 CI 221ndash2411) bladderbowel dysfunctionand symptom worsening with exercise were associated withthe VM-AVMAVF relative to IM (for bladderbowel dys-function 412 95 CI 137ndash1244 for worsening with ex-ercise 1399 95 CI 202ndash9711)
Neurologic examinationWhile weakness was present in the majority of patientsa higher frequency was seen in the VM group (98 table 2)In participants with VM-ischemicstroke and VM-AVMAVF flaccid weakness was substantially more common rela-tive to IM (all OR gt10) Hyporeflexia was more frequent inthe VM-ischemicstroke group (63) relative to other typesParticipants with SM or OM were less likely to have com-promised sphincters relative to IM (for SM OR 030 95 CI009ndash099 for OM 037 95 CI 018ndash980) A sensory levelwas more frequently seen in the VM-ischemicstroke andVM-AVMAVF groups (79 70) as compared with the IMSM and OM groups (50 51 and 49 respectively) In allcategories the most frequent sensory level was thoracic
MRI characteristicsLongitudinally extensive myelopathy (LE 3 or more vertebrallevels in length) was observed in all groups but most fre-quently in the VM group (ischemicstroke 60 AVMAVF70) For VM-ischemicstroke this was significantly morefrequent when compared to IM (OR 387 95 CI115ndash1302) Almost half of the IM and SM lesions (44 and46 respectively) exhibited LE The likelihood of multifocallesions was higher in the IM group relative to any other my-elopathy category All of the reclassified myelopathies wereless likely to have Gd+ (all OR lt050) relative to IM howevernotably this finding was not specific as 21 of the VM-ischemicstrokes 60 of the VM-AVMAVF and 46 of SMpatients category were also enhancing
The pattern of lesion distribution for each diagnostic categoryin both axial and sagittal views is shown in figure 2 The IMlesions affected more frequently the posterolateral spinal cordrelative to all other myelopathy groups (all OR lt10) and werelocated more often in the cervical and upper thoracic spinalcord (C1-T6) Lesions in the VM-ischemicstroke group weremore frequently anterior (67) these lesions were involvingmore commonly the cervical cord and the lower thoracic spinalcord SM lesions tended to locate in the central spinal cord(77 OR relative to IM 459 95 CI 150ndash140) and to bemore frequently cervical Lesions involving the conus medul-laris were more common in VM-AVMAVF than IM (OR1923 95 CI 335ndash11038) these lesions were less likely toinvolve the posterior cord relative to IM (OR 019 004ndash076)and were more frequently central (77)
CSF featuresThe laboratory profile of the initial CSF obtained after theonset of symptoms was available for 390 patients Pleocytosiswas observed more frequently in the IM group (57) how-ever it is worth noting that pleocytosis was also present in
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e15
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya
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a substantial proportion of VM-AVMAVF (35) and VM-ischemicstroke (17) Moreover 43 of the patients whomet the criteria for IM did not exhibit pleocytosis Elevatedprotein was more frequently observed in the VM-AVMAVFand SM group (74 and 45 respectively) OCB were al-most exclusive of the IM group although they were onlypresent in 45 of patients tested Participants with VM-ischemicstroke were less likely to have pleocytosis or OCBrelative to IM (all ORs lt1)
Prediction model for identifying diagnosticcategory of myelopathiesOur predictive model selected the following predictors ascharacteristics that improve discriminatory power for identi-fying the correct diagnostic category of a given myelopathytemporal profile of symptoms motor examination findingsconus medullaris involvement and presence of posteriorspinal cord lesions (table 3) By including these 4 additionalcharacteristics the correct classification rate (CCR) increasedfrom 67 to 87 and the multinomial area under the curve(AUC) increased from 032 to 067 suggesting markedimprovements in the correct classification of a given mye-lopathy NRI (34) and IDI (38) values associated with thispredictor set are also notable as both the CCR and AUC aresensitive to the differences in the prevalence of underlyingoutcomes This suggests improved classification and moresuccinct separation in prediction of diagnostic categories ofgiven myelopathies relative to only considering Gd+ and
pleocytosis (typically used to define IM) Of all the predictorsconsidered the temporal profile contributed to the largestchanges in IDI NRI and CCR relative to the traditionalmodel (Gd+ and pleocytosis) By including the temporalprofile only (and no other predictor) the CCR is 068 and themultinomial AUC is 03916 Relative to the null model (nopredictors) inclusion of the temporal profile results in animproved integrated discrimination index of 15 (12ndash19)and improved net reclassification index of 15 (2ndash28)(table e-4 httplinkslwwcomWNLA9) Results of oursensitivity analyses (derivation of a prediction model onlyconsidering demographics clinical presentation and neuro-logic examination and no additional MRI findings) were con-sistent Relative to a model considering Gd+ and pleocytosiswith the inclusion of motor examination findings and thetemporal profile of symptoms the CCR increased from 67 to81 and themultinomial AUC increased from 032 to 060 IDI(26) and potentially NRI (22) similarly suggested im-proved discriminatory power associated with the inclusion ofthe temporal profile and motor examination findings
DiscussionThe broad differential diagnosis of TM makes it necessary todevelop strategies that accurately distinguish among the dif-ferent etiologies of myelopathy Our study which is thelargest known cohort evaluating patients with presumed TM
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya (continued)
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations Gd+ = gadolinium enhancement IgG = immunoglobulin G IQR = inter-quartile range LE = longitudinally extensiveValues are n ()a Percentages include all participants in each category as the denominatorb Information for reflexes available for 444457 patientsc MRI data were obtained from first MRI available after onset of symptoms 67 were done in lt2 days 74 were done from 2 to 5 days 58 from 6 to 10 days 72from 11 to 30 days and 186 were done gt30 days after onset of symptomsd Percentages based on the total of patients tested CSF data were obtained from first CSF evaluated after onset of symptoms 53390 were obtained in lt2days 62390 were obtained from 2 to 5 days 58390 were obtained from 6 to 10 days 45390 were obtained from 11 to 30 days and 172390 were obtainedgt30 days after onset of symptoms
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e17
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
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myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
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20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
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ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
Table 1 Definitions of diagnostic categoriesa
Myelopathy A clinical syndrome characterized by motor sensory or autonomic symptomsattributable anatomically to spinal cord dysfunction
Inflammatory myelopathy Myelopathy meeting the diagnostic criteria for known specific inflammatory disordersincluding MS10 NMOSD11 sarcoidosis12 and rheumatologic myelopathies13 when otheralternative etiologies were ruled out or meeting criteria for idiopathic TM2
Vascular myelopathy related to ischemic disease (strokes)
Definite bull Myelopathy
bull MRI hyperintense lesion in a defined vascular territory or watershed areab on T2-weighted images
bull Vascular abnormality demonstrated on spinal angiogram explanatory of the clinicalpresentation
bull Exclusion of other etiologies
Probable bull Myelopathy
bull MRI-hyperintense lesion in a defined vascular territory or watershed area on T2-weighted images
bull Spinal angiogram negative or not available
bull Positive DWI or known stroke risk factors or mechanism explanatory of the clinicalpresentation (ie severe hypotension hypercoagulable state)
bull Exclusion of other etiologies
Possible bull Myelopathy
bull MRI hyperintense lesion in a defined vascular territory or watershed area on T2-weighted images
bull Spinal angiogram and DWI negative or not available
bull No identifiable risk factor or mechanism
bull Exclusion of other etiologies
Vascular myelopathy associated with AVMAVF
Definite bull Myelopathy
bull MRI hyperintense lesion in the spinal cord on T2-weighted images
bull Angiogram proven AVM or AVF
bull Exclusion of other etiologies
Probable bull Myelopathy
bull MRI hyperintense lesion in the spinal cord on T2-weighted images
bull MRI vasculature abnormality consistent with AVF or AVM (prominent flow voids)
bull Spinal angiogram not available
bull Exclusion of other etiologies
Spondylotic myelopathy Myelopathy withMRI hyperintense lesion in the spinal cord on T2-weighted images in theregion of spine degenerative changes such as disc herniation spondylolisthesis cervicalstenosis or osteophyte mass effect and where other causes were ruled out
Other myelopathiesc Non-inflammatorymyelopathies not meeting criteria for the above diagnostic categories
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations DWI = diffusion-weighted imaging MS = multiple sclerosis NMOSD =neuromyelitis optica spectrum disorder TM = transverse myelitisa For a diagnosis to be made all the conditions in the definition need to be metb Arterial territory supplied by sources flowing in opposite directions includes the upper thoracic region isolated graymatter and the posterior lumbosacralwatershed area14c Includes myelopathies of metabolic neoplastic infectious and unknown etiology
e14 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
implemented with R version 322 (httpswwwr-projectorg) This study provides Class IV evidence that for patientspresenting with myelopathy temporal profile of symptomsinitial motor examination and MRI lesion distribution dis-tinguish those with inflammatory myelopathies from thosewith other causes of myelopathy
Standard protocol approvals registrationsand patient consentsThe institutional review board at Johns Hopkins Hospital ap-proved the study and waived patient consent (IRB00115274)
ResultsPatient populationA total of 457 patients (58 female median age 46 yearsinterquartile range 33ndash56 years) with the presumptive di-agnosis of TM were analyzed (table 2 and tables e-1 e-2 ande-3 httplinkslwwcomWNLA9) After thorough as-sessment of the clinical MRI and CSF features final di-agnoses were reclassified as IM in 247 (55) patients VM in92 (20) patients (62 ischemicstroke and 30 arteriovenousmalformations [AVM]arteriovenous fistulas [AVF]) SM in35 (8) patients and OM in 83 (18) patients For the VMischemicstroke category the diagnosis was definite in 13probable in 26 and possible in 23 patients For 28 patientswith AVMAVF the diagnosis was definite 2 patients withprominent flow voids on MRI and a compatible clinicalprofile declined angiography and were classified as probableVM-AVMAVF
Demographics and medical historyThe majority of patients were Caucasian in all categoriesRelative to the inflammatory group AVMAVF and SM weremore likely with increasing age (for AVMAVF odds ratio[OR] per 10 years increment 178 95 confidence interval[CI] 134ndash244 for SM OR 204 95 CI 15ndash288) AVMAVF and SM were more common in men than in women (forVM-AVMAVF OR 504 95 CI 181ndash1407 for SM OR309 95 CI 129ndash735) A history of autoimmune diseasewas less frequent in the VM-ischemicstroke group comparedto IM (OR 025 95 CI 007ndash089) and while a history ofa preceding infection was more frequent in IM this was notstatistically significant in multivariate analysis (figure 1 andtable e-1 httplinkslwwcomWNLA9)
Temporal profileIM presented more often with a subacute temporal profile(55) Relative to IM VM-ischemicstroke exhibited morefrequently a hyperacute profile (89 OR 3519 95 CI892ndash13890) in contrast to VM-AVMAVF SM and OMwhich were significantly more likely to exhibit a chronic pat-tern (83 86 61 respectively all OR gt 3)
Initial symptomsThe presence of acute excruciating back pain at onset wasassociated with the VM-ischemicstroke group relative to IM
(OR 730 95 CI 221ndash2411) bladderbowel dysfunctionand symptom worsening with exercise were associated withthe VM-AVMAVF relative to IM (for bladderbowel dys-function 412 95 CI 137ndash1244 for worsening with ex-ercise 1399 95 CI 202ndash9711)
Neurologic examinationWhile weakness was present in the majority of patientsa higher frequency was seen in the VM group (98 table 2)In participants with VM-ischemicstroke and VM-AVMAVF flaccid weakness was substantially more common rela-tive to IM (all OR gt10) Hyporeflexia was more frequent inthe VM-ischemicstroke group (63) relative to other typesParticipants with SM or OM were less likely to have com-promised sphincters relative to IM (for SM OR 030 95 CI009ndash099 for OM 037 95 CI 018ndash980) A sensory levelwas more frequently seen in the VM-ischemicstroke andVM-AVMAVF groups (79 70) as compared with the IMSM and OM groups (50 51 and 49 respectively) In allcategories the most frequent sensory level was thoracic
MRI characteristicsLongitudinally extensive myelopathy (LE 3 or more vertebrallevels in length) was observed in all groups but most fre-quently in the VM group (ischemicstroke 60 AVMAVF70) For VM-ischemicstroke this was significantly morefrequent when compared to IM (OR 387 95 CI115ndash1302) Almost half of the IM and SM lesions (44 and46 respectively) exhibited LE The likelihood of multifocallesions was higher in the IM group relative to any other my-elopathy category All of the reclassified myelopathies wereless likely to have Gd+ (all OR lt050) relative to IM howevernotably this finding was not specific as 21 of the VM-ischemicstrokes 60 of the VM-AVMAVF and 46 of SMpatients category were also enhancing
The pattern of lesion distribution for each diagnostic categoryin both axial and sagittal views is shown in figure 2 The IMlesions affected more frequently the posterolateral spinal cordrelative to all other myelopathy groups (all OR lt10) and werelocated more often in the cervical and upper thoracic spinalcord (C1-T6) Lesions in the VM-ischemicstroke group weremore frequently anterior (67) these lesions were involvingmore commonly the cervical cord and the lower thoracic spinalcord SM lesions tended to locate in the central spinal cord(77 OR relative to IM 459 95 CI 150ndash140) and to bemore frequently cervical Lesions involving the conus medul-laris were more common in VM-AVMAVF than IM (OR1923 95 CI 335ndash11038) these lesions were less likely toinvolve the posterior cord relative to IM (OR 019 004ndash076)and were more frequently central (77)
CSF featuresThe laboratory profile of the initial CSF obtained after theonset of symptoms was available for 390 patients Pleocytosiswas observed more frequently in the IM group (57) how-ever it is worth noting that pleocytosis was also present in
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e15
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya
e16 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
a substantial proportion of VM-AVMAVF (35) and VM-ischemicstroke (17) Moreover 43 of the patients whomet the criteria for IM did not exhibit pleocytosis Elevatedprotein was more frequently observed in the VM-AVMAVFand SM group (74 and 45 respectively) OCB were al-most exclusive of the IM group although they were onlypresent in 45 of patients tested Participants with VM-ischemicstroke were less likely to have pleocytosis or OCBrelative to IM (all ORs lt1)
Prediction model for identifying diagnosticcategory of myelopathiesOur predictive model selected the following predictors ascharacteristics that improve discriminatory power for identi-fying the correct diagnostic category of a given myelopathytemporal profile of symptoms motor examination findingsconus medullaris involvement and presence of posteriorspinal cord lesions (table 3) By including these 4 additionalcharacteristics the correct classification rate (CCR) increasedfrom 67 to 87 and the multinomial area under the curve(AUC) increased from 032 to 067 suggesting markedimprovements in the correct classification of a given mye-lopathy NRI (34) and IDI (38) values associated with thispredictor set are also notable as both the CCR and AUC aresensitive to the differences in the prevalence of underlyingoutcomes This suggests improved classification and moresuccinct separation in prediction of diagnostic categories ofgiven myelopathies relative to only considering Gd+ and
pleocytosis (typically used to define IM) Of all the predictorsconsidered the temporal profile contributed to the largestchanges in IDI NRI and CCR relative to the traditionalmodel (Gd+ and pleocytosis) By including the temporalprofile only (and no other predictor) the CCR is 068 and themultinomial AUC is 03916 Relative to the null model (nopredictors) inclusion of the temporal profile results in animproved integrated discrimination index of 15 (12ndash19)and improved net reclassification index of 15 (2ndash28)(table e-4 httplinkslwwcomWNLA9) Results of oursensitivity analyses (derivation of a prediction model onlyconsidering demographics clinical presentation and neuro-logic examination and no additional MRI findings) were con-sistent Relative to a model considering Gd+ and pleocytosiswith the inclusion of motor examination findings and thetemporal profile of symptoms the CCR increased from 67 to81 and themultinomial AUC increased from 032 to 060 IDI(26) and potentially NRI (22) similarly suggested im-proved discriminatory power associated with the inclusion ofthe temporal profile and motor examination findings
DiscussionThe broad differential diagnosis of TM makes it necessary todevelop strategies that accurately distinguish among the dif-ferent etiologies of myelopathy Our study which is thelargest known cohort evaluating patients with presumed TM
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya (continued)
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations Gd+ = gadolinium enhancement IgG = immunoglobulin G IQR = inter-quartile range LE = longitudinally extensiveValues are n ()a Percentages include all participants in each category as the denominatorb Information for reflexes available for 444457 patientsc MRI data were obtained from first MRI available after onset of symptoms 67 were done in lt2 days 74 were done from 2 to 5 days 58 from 6 to 10 days 72from 11 to 30 days and 186 were done gt30 days after onset of symptomsd Percentages based on the total of patients tested CSF data were obtained from first CSF evaluated after onset of symptoms 53390 were obtained in lt2days 62390 were obtained from 2 to 5 days 58390 were obtained from 6 to 10 days 45390 were obtained from 11 to 30 days and 172390 were obtainedgt30 days after onset of symptoms
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e17
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e19
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
implemented with R version 322 (httpswwwr-projectorg) This study provides Class IV evidence that for patientspresenting with myelopathy temporal profile of symptomsinitial motor examination and MRI lesion distribution dis-tinguish those with inflammatory myelopathies from thosewith other causes of myelopathy
Standard protocol approvals registrationsand patient consentsThe institutional review board at Johns Hopkins Hospital ap-proved the study and waived patient consent (IRB00115274)
ResultsPatient populationA total of 457 patients (58 female median age 46 yearsinterquartile range 33ndash56 years) with the presumptive di-agnosis of TM were analyzed (table 2 and tables e-1 e-2 ande-3 httplinkslwwcomWNLA9) After thorough as-sessment of the clinical MRI and CSF features final di-agnoses were reclassified as IM in 247 (55) patients VM in92 (20) patients (62 ischemicstroke and 30 arteriovenousmalformations [AVM]arteriovenous fistulas [AVF]) SM in35 (8) patients and OM in 83 (18) patients For the VMischemicstroke category the diagnosis was definite in 13probable in 26 and possible in 23 patients For 28 patientswith AVMAVF the diagnosis was definite 2 patients withprominent flow voids on MRI and a compatible clinicalprofile declined angiography and were classified as probableVM-AVMAVF
Demographics and medical historyThe majority of patients were Caucasian in all categoriesRelative to the inflammatory group AVMAVF and SM weremore likely with increasing age (for AVMAVF odds ratio[OR] per 10 years increment 178 95 confidence interval[CI] 134ndash244 for SM OR 204 95 CI 15ndash288) AVMAVF and SM were more common in men than in women (forVM-AVMAVF OR 504 95 CI 181ndash1407 for SM OR309 95 CI 129ndash735) A history of autoimmune diseasewas less frequent in the VM-ischemicstroke group comparedto IM (OR 025 95 CI 007ndash089) and while a history ofa preceding infection was more frequent in IM this was notstatistically significant in multivariate analysis (figure 1 andtable e-1 httplinkslwwcomWNLA9)
Temporal profileIM presented more often with a subacute temporal profile(55) Relative to IM VM-ischemicstroke exhibited morefrequently a hyperacute profile (89 OR 3519 95 CI892ndash13890) in contrast to VM-AVMAVF SM and OMwhich were significantly more likely to exhibit a chronic pat-tern (83 86 61 respectively all OR gt 3)
Initial symptomsThe presence of acute excruciating back pain at onset wasassociated with the VM-ischemicstroke group relative to IM
(OR 730 95 CI 221ndash2411) bladderbowel dysfunctionand symptom worsening with exercise were associated withthe VM-AVMAVF relative to IM (for bladderbowel dys-function 412 95 CI 137ndash1244 for worsening with ex-ercise 1399 95 CI 202ndash9711)
Neurologic examinationWhile weakness was present in the majority of patientsa higher frequency was seen in the VM group (98 table 2)In participants with VM-ischemicstroke and VM-AVMAVF flaccid weakness was substantially more common rela-tive to IM (all OR gt10) Hyporeflexia was more frequent inthe VM-ischemicstroke group (63) relative to other typesParticipants with SM or OM were less likely to have com-promised sphincters relative to IM (for SM OR 030 95 CI009ndash099 for OM 037 95 CI 018ndash980) A sensory levelwas more frequently seen in the VM-ischemicstroke andVM-AVMAVF groups (79 70) as compared with the IMSM and OM groups (50 51 and 49 respectively) In allcategories the most frequent sensory level was thoracic
MRI characteristicsLongitudinally extensive myelopathy (LE 3 or more vertebrallevels in length) was observed in all groups but most fre-quently in the VM group (ischemicstroke 60 AVMAVF70) For VM-ischemicstroke this was significantly morefrequent when compared to IM (OR 387 95 CI115ndash1302) Almost half of the IM and SM lesions (44 and46 respectively) exhibited LE The likelihood of multifocallesions was higher in the IM group relative to any other my-elopathy category All of the reclassified myelopathies wereless likely to have Gd+ (all OR lt050) relative to IM howevernotably this finding was not specific as 21 of the VM-ischemicstrokes 60 of the VM-AVMAVF and 46 of SMpatients category were also enhancing
The pattern of lesion distribution for each diagnostic categoryin both axial and sagittal views is shown in figure 2 The IMlesions affected more frequently the posterolateral spinal cordrelative to all other myelopathy groups (all OR lt10) and werelocated more often in the cervical and upper thoracic spinalcord (C1-T6) Lesions in the VM-ischemicstroke group weremore frequently anterior (67) these lesions were involvingmore commonly the cervical cord and the lower thoracic spinalcord SM lesions tended to locate in the central spinal cord(77 OR relative to IM 459 95 CI 150ndash140) and to bemore frequently cervical Lesions involving the conus medul-laris were more common in VM-AVMAVF than IM (OR1923 95 CI 335ndash11038) these lesions were less likely toinvolve the posterior cord relative to IM (OR 019 004ndash076)and were more frequently central (77)
CSF featuresThe laboratory profile of the initial CSF obtained after theonset of symptoms was available for 390 patients Pleocytosiswas observed more frequently in the IM group (57) how-ever it is worth noting that pleocytosis was also present in
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e15
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya
e16 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
a substantial proportion of VM-AVMAVF (35) and VM-ischemicstroke (17) Moreover 43 of the patients whomet the criteria for IM did not exhibit pleocytosis Elevatedprotein was more frequently observed in the VM-AVMAVFand SM group (74 and 45 respectively) OCB were al-most exclusive of the IM group although they were onlypresent in 45 of patients tested Participants with VM-ischemicstroke were less likely to have pleocytosis or OCBrelative to IM (all ORs lt1)
Prediction model for identifying diagnosticcategory of myelopathiesOur predictive model selected the following predictors ascharacteristics that improve discriminatory power for identi-fying the correct diagnostic category of a given myelopathytemporal profile of symptoms motor examination findingsconus medullaris involvement and presence of posteriorspinal cord lesions (table 3) By including these 4 additionalcharacteristics the correct classification rate (CCR) increasedfrom 67 to 87 and the multinomial area under the curve(AUC) increased from 032 to 067 suggesting markedimprovements in the correct classification of a given mye-lopathy NRI (34) and IDI (38) values associated with thispredictor set are also notable as both the CCR and AUC aresensitive to the differences in the prevalence of underlyingoutcomes This suggests improved classification and moresuccinct separation in prediction of diagnostic categories ofgiven myelopathies relative to only considering Gd+ and
pleocytosis (typically used to define IM) Of all the predictorsconsidered the temporal profile contributed to the largestchanges in IDI NRI and CCR relative to the traditionalmodel (Gd+ and pleocytosis) By including the temporalprofile only (and no other predictor) the CCR is 068 and themultinomial AUC is 03916 Relative to the null model (nopredictors) inclusion of the temporal profile results in animproved integrated discrimination index of 15 (12ndash19)and improved net reclassification index of 15 (2ndash28)(table e-4 httplinkslwwcomWNLA9) Results of oursensitivity analyses (derivation of a prediction model onlyconsidering demographics clinical presentation and neuro-logic examination and no additional MRI findings) were con-sistent Relative to a model considering Gd+ and pleocytosiswith the inclusion of motor examination findings and thetemporal profile of symptoms the CCR increased from 67 to81 and themultinomial AUC increased from 032 to 060 IDI(26) and potentially NRI (22) similarly suggested im-proved discriminatory power associated with the inclusion ofthe temporal profile and motor examination findings
DiscussionThe broad differential diagnosis of TM makes it necessary todevelop strategies that accurately distinguish among the dif-ferent etiologies of myelopathy Our study which is thelargest known cohort evaluating patients with presumed TM
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya (continued)
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations Gd+ = gadolinium enhancement IgG = immunoglobulin G IQR = inter-quartile range LE = longitudinally extensiveValues are n ()a Percentages include all participants in each category as the denominatorb Information for reflexes available for 444457 patientsc MRI data were obtained from first MRI available after onset of symptoms 67 were done in lt2 days 74 were done from 2 to 5 days 58 from 6 to 10 days 72from 11 to 30 days and 186 were done gt30 days after onset of symptomsd Percentages based on the total of patients tested CSF data were obtained from first CSF evaluated after onset of symptoms 53390 were obtained in lt2days 62390 were obtained from 2 to 5 days 58390 were obtained from 6 to 10 days 45390 were obtained from 11 to 30 days and 172390 were obtainedgt30 days after onset of symptoms
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e17
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e19
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya
e16 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
a substantial proportion of VM-AVMAVF (35) and VM-ischemicstroke (17) Moreover 43 of the patients whomet the criteria for IM did not exhibit pleocytosis Elevatedprotein was more frequently observed in the VM-AVMAVFand SM group (74 and 45 respectively) OCB were al-most exclusive of the IM group although they were onlypresent in 45 of patients tested Participants with VM-ischemicstroke were less likely to have pleocytosis or OCBrelative to IM (all ORs lt1)
Prediction model for identifying diagnosticcategory of myelopathiesOur predictive model selected the following predictors ascharacteristics that improve discriminatory power for identi-fying the correct diagnostic category of a given myelopathytemporal profile of symptoms motor examination findingsconus medullaris involvement and presence of posteriorspinal cord lesions (table 3) By including these 4 additionalcharacteristics the correct classification rate (CCR) increasedfrom 67 to 87 and the multinomial area under the curve(AUC) increased from 032 to 067 suggesting markedimprovements in the correct classification of a given mye-lopathy NRI (34) and IDI (38) values associated with thispredictor set are also notable as both the CCR and AUC aresensitive to the differences in the prevalence of underlyingoutcomes This suggests improved classification and moresuccinct separation in prediction of diagnostic categories ofgiven myelopathies relative to only considering Gd+ and
pleocytosis (typically used to define IM) Of all the predictorsconsidered the temporal profile contributed to the largestchanges in IDI NRI and CCR relative to the traditionalmodel (Gd+ and pleocytosis) By including the temporalprofile only (and no other predictor) the CCR is 068 and themultinomial AUC is 03916 Relative to the null model (nopredictors) inclusion of the temporal profile results in animproved integrated discrimination index of 15 (12ndash19)and improved net reclassification index of 15 (2ndash28)(table e-4 httplinkslwwcomWNLA9) Results of oursensitivity analyses (derivation of a prediction model onlyconsidering demographics clinical presentation and neuro-logic examination and no additional MRI findings) were con-sistent Relative to a model considering Gd+ and pleocytosiswith the inclusion of motor examination findings and thetemporal profile of symptoms the CCR increased from 67 to81 and themultinomial AUC increased from 032 to 060 IDI(26) and potentially NRI (22) similarly suggested im-proved discriminatory power associated with the inclusion ofthe temporal profile and motor examination findings
DiscussionThe broad differential diagnosis of TM makes it necessary todevelop strategies that accurately distinguish among the dif-ferent etiologies of myelopathy Our study which is thelargest known cohort evaluating patients with presumed TM
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya (continued)
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations Gd+ = gadolinium enhancement IgG = immunoglobulin G IQR = inter-quartile range LE = longitudinally extensiveValues are n ()a Percentages include all participants in each category as the denominatorb Information for reflexes available for 444457 patientsc MRI data were obtained from first MRI available after onset of symptoms 67 were done in lt2 days 74 were done from 2 to 5 days 58 from 6 to 10 days 72from 11 to 30 days and 186 were done gt30 days after onset of symptomsd Percentages based on the total of patients tested CSF data were obtained from first CSF evaluated after onset of symptoms 53390 were obtained in lt2days 62390 were obtained from 2 to 5 days 58390 were obtained from 6 to 10 days 45390 were obtained from 11 to 30 days and 172390 were obtainedgt30 days after onset of symptoms
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e17
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e19
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
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httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
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ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
a substantial proportion of VM-AVMAVF (35) and VM-ischemicstroke (17) Moreover 43 of the patients whomet the criteria for IM did not exhibit pleocytosis Elevatedprotein was more frequently observed in the VM-AVMAVFand SM group (74 and 45 respectively) OCB were al-most exclusive of the IM group although they were onlypresent in 45 of patients tested Participants with VM-ischemicstroke were less likely to have pleocytosis or OCBrelative to IM (all ORs lt1)
Prediction model for identifying diagnosticcategory of myelopathiesOur predictive model selected the following predictors ascharacteristics that improve discriminatory power for identi-fying the correct diagnostic category of a given myelopathytemporal profile of symptoms motor examination findingsconus medullaris involvement and presence of posteriorspinal cord lesions (table 3) By including these 4 additionalcharacteristics the correct classification rate (CCR) increasedfrom 67 to 87 and the multinomial area under the curve(AUC) increased from 032 to 067 suggesting markedimprovements in the correct classification of a given mye-lopathy NRI (34) and IDI (38) values associated with thispredictor set are also notable as both the CCR and AUC aresensitive to the differences in the prevalence of underlyingoutcomes This suggests improved classification and moresuccinct separation in prediction of diagnostic categories ofgiven myelopathies relative to only considering Gd+ and
pleocytosis (typically used to define IM) Of all the predictorsconsidered the temporal profile contributed to the largestchanges in IDI NRI and CCR relative to the traditionalmodel (Gd+ and pleocytosis) By including the temporalprofile only (and no other predictor) the CCR is 068 and themultinomial AUC is 03916 Relative to the null model (nopredictors) inclusion of the temporal profile results in animproved integrated discrimination index of 15 (12ndash19)and improved net reclassification index of 15 (2ndash28)(table e-4 httplinkslwwcomWNLA9) Results of oursensitivity analyses (derivation of a prediction model onlyconsidering demographics clinical presentation and neuro-logic examination and no additional MRI findings) were con-sistent Relative to a model considering Gd+ and pleocytosiswith the inclusion of motor examination findings and thetemporal profile of symptoms the CCR increased from 67 to81 and themultinomial AUC increased from 032 to 060 IDI(26) and potentially NRI (22) similarly suggested im-proved discriminatory power associated with the inclusion ofthe temporal profile and motor examination findings
DiscussionThe broad differential diagnosis of TM makes it necessary todevelop strategies that accurately distinguish among the dif-ferent etiologies of myelopathy Our study which is thelargest known cohort evaluating patients with presumed TM
Table 2 Clinical features of 457 patients with myelopathy by diagnostic categorya (continued)
Abbreviations AVF = arteriovenous fistulas AVM = arteriovenous malformations Gd+ = gadolinium enhancement IgG = immunoglobulin G IQR = inter-quartile range LE = longitudinally extensiveValues are n ()a Percentages include all participants in each category as the denominatorb Information for reflexes available for 444457 patientsc MRI data were obtained from first MRI available after onset of symptoms 67 were done in lt2 days 74 were done from 2 to 5 days 58 from 6 to 10 days 72from 11 to 30 days and 186 were done gt30 days after onset of symptomsd Percentages based on the total of patients tested CSF data were obtained from first CSF evaluated after onset of symptoms 53390 were obtained in lt2days 62390 were obtained from 2 to 5 days 58390 were obtained from 6 to 10 days 45390 were obtained from 11 to 30 days and 172390 were obtainedgt30 days after onset of symptoms
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e17
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e19
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
demonstrated that only 54 of the patients referred as TMhad a confirmed inflammatory etiology While this may reflectto some degree a referral bias it also reflects the confusionsurrounding the term ldquotransverse myelitisrdquo among cliniciansin the community The use of this term is challenging sinceinflammatory myelopathies do not always present in agree-ment with the ldquoclassicrdquo definition of the syndrome as uni-lateral asymmetric and chronic presentations can occur17
signs of upper motor neuron disease are often not presentacutely and sensory levels are frequently absent19 In addi-tion the term TM is often used by clinicians to describeinvolvement of the spinal cord in different pathologic con-ditions even without clear evidence of inflammation an ap-proach that delays proper diagnosis and treatment Hence itis critically important to identify clinical biomarkers that helpestablish a correct etiologic diagnosis
In our analysis the clinical features distinguishing IM from othercauses of myelopathies at first presentation included the
temporal profile of symptoms (initial onset to nadir dysfunc-tion) the initial motor examination findings and the pattern oflesion distribution on MRI Since the temporal profile was themost helpful predictor in improving the diagnostic accuracy itcould be used in the clinical setting to guide the diagnosis ofmyelopathy A subacute presentation suggests an inflammatoryetiology as described previously29 while a hyperacute pre-sentation suggests a spinal cord ischemic stroke A chronicevolution suggests a vascular lesion such as VM- AVMAVFa chronic SM or other causes of myelopathy These findings arein agreementwith previous descriptions of spinal cord stroke1819
compressive myelopathies45 and vascular malformations720
Another important factor to consider is the medical history Inour cohort a history of sudden back pain orworsening by exercisepointed towards a vascular etiology which is in accordance withprevious descriptions1 Conversely a prior diagnosis of systemicinflammatory disorder suggests an inflammatory myelopathySeveral systemic disorders are known to potentially cause
Figure 1 Individual clinical predictors for each diagnostic category
Odds ratio estimates and 95 confidence intervals (CI) are shown for each diagnostic category relative to the inflammatory group statistically significantassociations (p lt 005) are highlighted in red AVF = arteriovenous fistulas AVM = arteriovenous malformations Gad+ = gadolinium-enhanced lesions IgG =immunoglobulin G LE = longitudinally extensive lesions OCB = oligoclonal bands R = reference group VM = vascular myelopathy
e18 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e19
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
Figure 2 Spinal cord MRI lesion patterns in patients with myelopathies
(A) Heatmap representationof lesiondistribution frequency for eachdiagnostic category The y axis represents sagittal localizationbased onusing the vertebral levels(C2ndashL2) and the xndashz axes represent the axial distribution of the lesion as affecting the anterior central lateral or posterior regions of the spinal cord Frequency foreach localization ranges from 0 (yellow) to 100 (bright red) (B) MRI examples in the different myelopathy diagnostic categories (Ba) Cervical spine MRI froma patient with idiopathic inflammatory myelopathy reveals signal intensity abnormality in T2-weighted sequences and enhancement in the postero-lateral region ofthe cervical cord (T1-weighted + gadolinium [Gad]) (Bb) Cervical spine MRI from a patient with vascular myelopathy (VM)ndashischemicstroke shows an anterior signalintensity abnormality in T2-weighted sequences in both sagittal and axial views which appears unenhanced in T1-weighted sequences + Gad (Bc) Thoracic MRI inapatientwithaVMndasharteriovenous fistula (AVF) seenasa longitudinal extensivemyelopathyanddiffuse intra-axial enhancement in thecentral cord thereareenlargedvessels in the dorsal surface of the cord (arrow) (Bd) Cervical spineMRI in a patient with spondylotic myelopathy shows signal intensity abnormality in T2-weightedsequences and patchy enhancement (T1 + Gad) in the central cervical cord AVM = arteriovenous malformations
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e19
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
myelitis such as Sjogren syndrome systemic lupus eryth-ematosus and sarcoidosis113 making a thorough medical historycrucial
The assessment of lesion distribution on MRI is also extremelyimportant The axial pattern may provide meaningful in-formation about the underlying pathogenic mechanism Forinstance MS would preferentially affect the myelinated tracts inthe posterolateral spinal cord Similarly a lesion affecting a dis-crete vascular distribution or a spinal cord watershed area wouldbe highly suggestive of an ischemic stroke Venous congestionand venous hypertension in the setting of VM-AVMAVF orcompression of the vasculature in SM would more frequentlyaffect the central cord region The classification of LE vs non-LElesions was less helpful while non-LE was suggestive of IM thedifferential diagnosis of LE lesions remained broad and includedinflammatory etiologies (NMOSD sarcoidosis rheumatologicand idiopathic myelitis) as well as VM and SM lesions
Regarding MRI and CSF findings traditionally considered tobe associated with IM such as pleocytosis elevated CSFprotein and Gd+ our cohort showed that these features werenot specific to the IM group This is highlighted by the lowdiagnostic accuracy in our model when considering only Gd+and pleocytosis to differentiate IM from other myelopathiesMoreover previous studies described Gd+ and CSF pleocy-tosis occurring in vascular6 and spondylotic myelopathies5 Arecent study of 56 patients with spondylotic myelopathyshowed CSF pleocytosis in 125 elevated CSF protein in70 and Gd+ lesions in up to 80 of patients4 The highfrequency of these CSF and MRI features in non-inflammatory myelopathies may account for their frequentmisdiagnosis as TM Part of the difficulty in making this dis-tinction arises from the common assumption that all CNSinflammation is due to a primary inflammatory disorder Anyinjury to the CNS has the potential to cause a secondary in-flammatory response that may manifest with some degree ofpleocytosis or disruption of the bloodndashbrain barrier causing
Gd+ in addition hemodynamic changes in the lesion such asvasodilation and ldquoluxury perfusionrdquo may also result in Gd+21
This situation is well-illustrated by Gd+ in ischemic brainstrokes within 1 week of onset22 Thus evidence of a Gd+lesion on MRI or CSF pleocytosis is not definitively diagnosticof a primary inflammatory disease and immunosuppressivetherapy may not be warranted Instead these findings shouldbe considered with the temporal profile and clinical pre-sentation of the myelopathy motor examination findings andMRI lesion distribution (particularly the axial pattern) Takingthese features into account can increase significantly the correctdiagnostic classification of myelopathies
The term TM should be used with caution as IMs do notalways present with a ldquotransverserdquo sensory level and non-IMmay mimic inflammatory disorders This highlights some ofthe limitations of the 2002 acute TM criteria2 which requirea clear sensory level and bilateral findings to diagnose TM andadditionally rely on CSF pleocytosis and MRI Gd+ to defineinflammation the criteria could perhaps be improved by notusing the word ldquotransverserdquo not requiring bilateral findings ora sensory level and emphasizing the importance of the tem-poral profile and consideration of non-inflammatory myelo-pathies even in presence of CSF pleocytosis or MRI Gd+ Itwould be less confusing to describe the myelopathic syn-drome as being caused either by a primary inflammatory ornon-inflammatory etiology the latter secondary to a specificpathologic process Once a diagnostic category is establisheda critical analysis of ancillary tests including brain MRI andspinal angiography as indicated is necessary to define thespecific etiology before assigning the label of idiopathic TM
This study is limited by its retrospective nature By analyzing theinflammatory group as a category this study may not reflectimportant differences among specific etiologies within the in-flammatory group such as MS vs NMOSD or NMOSD vs sar-coidosis myelopathy as has been shown previously In additionas a major referral center cases that pose a diagnostic challenge
Table 3 Results for top discriminatory model to predict the myelopathy diagnostic categorya
All of the aboved 038 (028ndash047) 034 (008ndash061) 087 076
Abbreviations AUC = area under the curve CI = confidence intervala Model was derived in the training set values displayed are derived from fitting the model with the selected characteristics in the testing setb In the multinomial extension a noninformative value is 1M where M is the number of outcome categories In this case M = 5 and a non-informativemultinomial AUC is 15 = 1125 = 0008c Multinomial model includes lesion enhancement pleocytosis and individual selected characteristic (eg [lesion enhancement pleocytosis temporalprofile] or [lesion enhancement pleocytosis motor examination])d Multinomialmodel including lesion enhancement pleocytosis temporal profilemotor examination conusmedullaris lesion location posterior cord lesion
e20 Neurology | Volume 90 Number 1 | January 2 2018 NeurologyorgN
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
are overrepresented in our cohort therefore the percent of IMmay not be reflective of what is seen in the community
Myelopathies may encompass a wide differential diagnosisthat requires a thorough diagnostic workup with consider-ation of inflammatory and non-inflammatory etiologies Thetemporal profile of symptoms might serve as a potentialclinical biomarker in the differential diagnosis of myelo-pathies which should be considered in conjunction witha critical analysis of MRI and CSF characteristics
Author contributionsPaula Barreras study design acquisition of data analysis andinterpretation of the data study coordination drafting and re-vising of the manuscript Kathryn C Fitzgerald statistical anal-ysis analysis and interpretation of the data revising themanuscript Maureen A Mealy acquisition and interpretation ofthe data revising the manuscript Jorge A Jimenez study designacquisition of the data revising the manuscript Daniel Beckerexamination of patients revising the manuscript Scott DNewsome examination of patients interpretation of data re-vising the manuscript Michael Levy examination of patientsinterpretation of data revising themanuscript PhilippeGailloudstudy design interpretation of the data revising the manuscriptCarlos A Pardo conception and design of the study obtainingfunding study supervision examination of patients analysis andinterpretation of the data drafting and revising the manuscript
Study fundingThis work was supported by The Bart McLean Fund forNeuroimmunology Research Johns Hopkins Project Restoreand the Transverse Myelitis Association
DisclosureP Barreras K Fitzgerald M Mealy and J Jimenez report nodisclosures relevant to the manuscript D Becker has receivedresearch support from NIH TMA PVA Novartis Sanofi-Genzyme Mallinckrodt and Biogen participated in scientificadvisory boards for the Multiple Sclerosis Society NovartisPharmaceuticals Sanofi-Aventis and TEVA Pharmaceuticalsand has received speaker honoraria from TEVA Pharma-ceuticals Novartis Sanofi-Genzyme Mallinckrodt andAcorda S Newsome has received research support (paid di-rectly to the institution) from Biogen Novartis Genentechand the National MS society and has participated in scientificadvisory boards for Biogen and Genentech M Levy currentlyreceives research support from the NIH Maryland Tech-nology Development Corporation Sanofi Genzyme AlexionAlnylam Shire Acorda and Apopharma received personalcompensation for consultation with Alexion Acorda andGenzyme and serves on the scientific advisory boards forAlexion Acorda and Quest Diagnostics P Gailloud has
served on the Scientific Advisory Board for ArtVentiveMedical holds Stock Options in ArtVentive Medical has re-ceived ConsultingSpeaker Honoraria from Codman Neu-rovascular and has the following patents EOS deviceEndovascular closure device EmbosphereEmbogel Liquidembolic agent and dissolvent C Pardo currently serves on theScientific Advisory Board of the Transverse Myelitis Associ-ation and receives research support from the NIH Medi-mmune Oncology Chugai Pharmaceuticals and the BartMcLean Fund forNeuroimmunology Research JohnsHopkinsProject Restore Go to NeurologyorgN for full disclosures
Received May 12 2017 Accepted in final form September 21 2017
References1 Beh SC Greenberg BM Frohman T Frohman EM Transverse myelitis Neurol Clin
20133179ndash1382 Transverse Myelitis Consortium Working Group Proposed diagnostic criteria and
nosology of acute transverse myelitis Neurology 200259499ndash5053 Bazerbachi F Maiser S Clark HB Giant thoracic schwannoma masquerading as
transverse myelitis QJM 2013106759ndash7614 Flanagan EP Krecke KN Marsh RW et al Specific pattern of gadolinium en-
hancement in spondylotic myelopathy Ann Neurol 20147654ndash655 Bee YJ Lee JW Park KS et al Compressive myelopathy magnetic resonance imaging
6 Matsubayashi J Tsuchiya K Shimizu S et al Posterior spinal artery syndromeshowingmarked swelling of the spinal cord a clinico-pathological study J Spinal CordMed 20133631ndash35
7 Lee YJ Terbrugge KG Saliou G Krings T Clinical features and outcomes of spinalcord arteriovenous malformations comparison between nidus and fistulous typesStroke 2014452606ndash2612
8 Lee CS Pyun HW Chae EY Kim KK Rhim SC Suh DC Reversible aggravation ofneurological deficits after steroid medication in patients with venous congestivemyelopathy caused by spinal arteriovenous malformation Interv Neuroradiol 200915325ndash329
9 Schmalstieg WF Weinshenker BG Approach to acute or subacute myelopathyNeurology 201075(suppl 1)S2ndashS8
10 Polman CH Reingold SC Banwell B et al Diagnostic criteria for multiple sclerosis2010 revisions to the McDonald criteria Ann Neurol 201169292ndash302
11 Wingerchuk DM Lennon VA Pittock SJ et al Revised diagnostic criteria for neu-romyelitis optica Neurology 2006661485ndash1489
12 Zajicek JP Scolding NJ Foster O et al Central nervous system sarcoidosis diagnosisand management Q JM 199992103ndash117
13 Birnbaum J Petri M Thompson R Izbudak I Kerr D Distinct subtypes of myelitis insystemic lupus erythematosus Arthritis Rheum 2009603378ndash3387
14 Gailloud P Gregg L Galan P Becker D Pardo C Periconal arterial anastomotic circleand posterior lumbosacral watershed zone of the spinal cord J Neurointerv Surg20157848ndash853
15 Li J Jiang B Fine JP Multicategory reclassification statistics for assessing improve-ments in diagnostic accuracy Biostatistics 201314382ndash394
16 Li J Fine JP ROC analysis with multiple classes and multiple tests methodology andits application in microarray studies Biostatistics 20089566ndash576
17 Frohman EM Wingerchuk DM Transverse myelitis N Engl J Med 2010363564ndash572
18 Novy J Carruzzo A Maeder P Bogousslavsky J Spinal cord ischemia clinical andimaging patterns pathogenesis and outcomes in 27 patients Arch Neurol 2006631113ndash1120
19 Wong JJ Dufton J Mior SA Spontaneous conus medullaris infarction in a 79-year-oldfemale with cardiovascular risk factors a case report J Can Chiropr Assoc 20125658ndash65
20 Jellema K Canta LR Tijssen CC van Rooij WJ Koudstaal PJ van Gijn J Spinal duralarteriovenous fistulas clinical features in 80 patients J Neurol Neurosurg Psychiatry2003741438ndash1440
21 Liu HS ChungHW ChouMC et al Effects of microvascular permeability changes oncontrast-enhanced T1 and pharmacokinetic MR imaging after ischemia Stroke 2013441872ndash1877
22 Karonen JO Partanen PL Vanninen RL Vainio PA Aronen HJ Evolution of MRcontrast enhancement patterns during the first week after acute ischemic strokeAJNR Am J Neuroradiol 200122103ndash111
NeurologyorgN Neurology | Volume 90 Number 1 | January 2 2018 e21
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
SOURCE ARTICLE NPuborgl73d2c
Clinical biomarkers differentiate myelitis fromvascular and other causes of myelopathyPaula Barreras MD Kathryn C Fitzgerald ScD Maureen A Mealy RN BSN Jorge A Jimenez MD
Daniel Becker MD Scott D Newsome DO Michael Levy MD PhD Philippe Gailloud MD
Study fundingpotential competing interestsThe study was funded by the Bart McLean Fund for Neuro-immunology Research Johns Hopkins Project Restore andthe Transverse Myelitis Association Several authors reportreceiving research funding personal compensation andoradvisory committee appointments from various pharmaceuti-cal companies medical device manufacturers and scholarlyassociations Go to NeurologyorgN for full disclosures
Study questionWhich clinical and paraclinical features of patients diagnosedwith transversemyelitis (TM) can differentiate those who haveinflammatorymyelopathies from thosewith non-inflammatorymyelopathies
Summary answerThe temporal profile of symptoms is the most powerful bio-marker for differentiating inflammatory and non-inflammatorymyelopathies
What is known and what this paper addsTM is a highly heterogeneous inflammatory syndrome non-inflammatory myelopathies are often misdiagnosed as TMGadolinium enhancement in MRI and CSF pleocytosis havebeen used to define inflammation in TM This study showsthat these features are nonspecific and that the subacute onsetof symptoms the absence of flaccid weakness and the pres-ence of multifocal (cervical and thoracic and posterior lateral)lesions on MRI suggest an inflammatory etiology
Participants and settingThe study examined 457 of 575 patients who had been di-agnosed with TM and referred to a specialized myelopathycenter between 2010 and 2015 The other 118 were excludeddue to incomplete or unverifiable information
Design size and durationThis study retrospectively analyzed patient records includingdemographic characteristics medical histories temporalsymptom profiles initial symptoms and results from neuro-logic MRI and CSF examinations The final diagnosis wasclassified as inflammatory vascular spondylotic or other causes
of myelopathy Multinomial regression modeling was appliedto determine characteristics associated with each final diagnosisand predictors that would improve classification accuracy
Main results and the role of chanceOf the 457 myelopathies evaluated 247 (54) patients hada confirmed inflammatory etiology Compared to inflammatorycases vascular myelopathies related to ischemic strokes weremore likely hyperacute (odds ratio [OR] 3519 95 confi-dence interval 892ndash13890) and other non-inflammatorycases were more likely to exhibit chronic patterns (ORs gt3)Adding the temporal profile initial motor examination featuresand MRI pattern of lesion distribution to the multinomialpredictive model provided greater predictive power than onlyconsidering CSF pleocytosis and MRI gadolinium enhance-ment Of all predictors the temporal profile contributed themost to the increased discriminatory power
Bias confounding and other reasons for cautionThe study is limited by its retrospective nature The study alsogrouped all inflammatory myelopathy cases together not ac-counting for important distinctions between various types ofinflammatory myelopathies
Generalizability to other populationsThis study examined cases at a major referral center andtherefore diagnostically challenging cases were probablyoverrepresented in the cohort The frequency of inflammatorymyelopathies may not reflect that found in the general patientpopulation
Variables consideredCorrectclassification rate
Multinomial areaunder the curve
MRI lesion enhancementand pleocytosis
067 032
+ Temporal profile 077 054
+ Motor exam findings 070 046
+ Posterior cord lesion 068 037
+ Conus medullaris lesion 069 037
All of the above 087 076
A draft of the short-form article was written by M Dalefied a writer with Editage a division of Cactus Communications The authors of the full-length article and the journal editors edited and approved the final version
Copyright copy 2017 American Academy of Neurology 19
SHORT-FORM ARTICLE
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
DOI 101212WNL0000000000004765201890e12-e21 Published Online before print December 1 2017Neurology
Paula Barreras Kathryn C Fitzgerald Maureen A Mealy et al myelopathy
Clinical biomarkers differentiate myelitis from vascular and other causes of
This information is current as of December 1 2017
ServicesUpdated Information amp
httpnneurologyorgcontent901e12fullincluding high resolution figures can be found at
httpnneurologyorgcgicollectionall_spinal_cordAll Spinal Cordfollowing collection(s) This article along with others on similar topics appears in the
Permissions amp Licensing
httpwwwneurologyorgaboutabout_the_journalpermissionsits entirety can be found online atInformation about reproducing this article in parts (figurestables) or in
Reprints
httpnneurologyorgsubscribersadvertiseInformation about ordering reprints can be found online
ISSN 0028-3878 Online ISSN 1526-632XWolters Kluwer Health Inc on behalf of the American Academy of Neurology All rights reserved Print1951 it is now a weekly with 48 issues per year Copyright Copyright copy 2017 The Author(s) Published by
reg is the official journal of the American Academy of Neurology Published continuously sinceNeurology
