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PROTEINURIA IN COMMUNITY-ACQUIRED PNEUMONIA

Summary

Acute kidney injury (AKI), classified according to the Risk, Injury, Failure, Loss and End-stage kidney disease (RIFLE) criteria, is occasionally seen in patients with community-acquired pneumonia (CAP). It is known that the RIFLE criteria may underestimate the occurrence of AKI. The aim of this study was to investigate the predictive value of proteinuria compared with the predictive value of the RIFLE criteria, as marker of AKI in patients with CAP. Proteinuria was measured in a urine sample obtained on the day of admission and was defined as total-protein/creatinine ratio >23 mg/mmol. Primary outcome was length of hospital stay (LOS). Secondary outcomes were in-hospital mortality and one-year mortality.

Urine samples were available for 319/496 patients (64%); 198/319 patients (62%) had proteinuria. In univariate analysis, patients with proteinuria had a significant longer LOS (9.0 days [interquartile range (IQR) 7.0-14.0] versus 7.0 days [IQR 5.0-10.0]) and increased in-hospital mortality compared with patients without proteinuria. The RIFLE criteria were a predictor for the LOS (9.0 days [IQR 7.0-14.0] for patients in RIFLE classes 1-3 compared with 8.0 days [IQR 6.0-12.0] for patients in RIFLE class 0), in-hospital mortality and one-year mortality. In multivariate analysis, only proteinuria was an independent predictor for LOS.

The incidence of proteinuria during CAP is high. Proteinuria and the RIFLE criteria are both associated with adverse outcome in CAP. Only proteinuria is an independent predictor for length of hospital stay.

Proteinuria can be a marker for outcome and may be used to assess the severity of CAP as well.

Internal Medicine, St. Antonius Hospital, Nieuwegein, February - July 2011 1


Index

Page

Introduction .…………………………………………………………………………….. 3

Thesis …………………………………………………………………………………… 7

Materials and Methods ………………………………………………………………… 8

Results …………………………………………………………………………………..12

Discussion ……………………………………………………………………………….20

Conclusion ………………………………………………………………………………23

Acknowledgement ……………………………………………………………………...23

Reference List …………………………………………………………………………..24

Supplements …………………………………………………………………………..28

Supplement 1. Table S1 ……………………………………………………………………….28Supplement 2. Pneumonia Severity Index ……. ……………………………………………29



Supplement 3. SIRS criteria …………………………………………………………………..30Supplement 4. Table S4 ……………………………………………………………………….31Supplement 5. Figures S1A and S1B ………………………………………………………..32Supplement 6. Table S5 ……………………………………………………………………….33Supplement 7. Table S6 ……………………………………………………………………….34Supplement 8. Figures S2, S3 and S4 ……………………………………………………….35Supplement 9. List of abbreviations …………………………………………………………..36Supplement 10. Samenvatting ………………………………………………………………... 37

Introduction

Acute Kidney Injury (AKI) is regularly seen as a complication in hospitalized patients.(1;2) Previously, AKI was called acute tubular necrosis. As pathology only rarely showed necrosis, the name changed to AKI.(3) Before necrosis actually occurs, there is probably a sublethal injury.(4) Normally, there is a perfect balance between the oxygen supply and oxygen demand. This balance is mainly dependent on the renal blood flow and the oxygen use, which is determined by the basal metabolic need and the tubular urine concentration process with active sodium resorption.(5) This balance is maintained within close limits. In conditions that require even more oxygen consumption (e.g. renal hypertrophy, radiocontrast agents), or conditions that cause renal vasoconstriction, the sublethal injury can lead to necrosis.(5) A condition that can lead to renal vasoconstriction is sepsis. Sepsis leads to the release of catecholamins and endotoxins. This can cause a nitric oxide release, which leads to arterial vasodilatation. This results in arterial underfilling, which activates the baroreceptors. The central nervous system will give signals which increase the sympathetic tone and increase the release of vasopressin. The sympathetic tone, the renine-angiotensin-aldosteron-system induces by the sympathetic tone, and the vasopressin all result in renal vasoconstriction with sodium and water retention.(6) A study in patients admitted to the ICU found sepsis as cause of AKI in 32.4%.(7) In a prospective study in post-cardiac surgery patients, renal oxygen consumption in patients with AKI was compared with renal oxygen consumption in patients without AKI. The renal oxygen supply/demand balance was severely impaired in early AKI, as there was an almost 70% increase in renal oxygen extraction.(8) Especially in places where there is already a poor oxygen supply the risk of necrosis is high.(5;9) The segment which is most commonly injured is the proximal tubular cell. In



this part of the kidney, there is little microvascular hypoperfusion and congestion, as result of a different blood flow in this area of the nephron. Furthermore, this cell requires a high metabolic rate for active sodium transport and is able to generate ATP by anaerobic glycolysis only to a limited degree.(9;10)

AKI refers to a clinical diagnosis. The Acute Dialysis Quality Initiative (ADQI) group developed a consensus definition of AKI in 2004: the Risk, Injury, Failure, Loss, and End-stage kidney disease (RIFLE) criteria (table 1A).(2;11) With these criteria, AKI can be divided into three classes (Risk, Injury and Failure), based on urine output or a rise in serum creatinine compared to baseline creatinine. Outcome is categorized in two classes: loss and end-stage kidney disease. Multiple studies validated these criteria as being related to adverse clinical outcome.(7;12;13) A rise in serum creatinine of 1.5 times or more classifies a patient in a RIFLE class.(2) But a meta-analysis in different patients-types and a variety of clinical settings, showed that even mild changes in serum creatinine levels predict adverse outcomes.(14) Before creatinine actually rises, the kidney can already be affected. The relationship between serum creatinine and glomerular filtration rate (GFR) is not linear, and hyperfiltration of nephrons that are less affected will occur.(15) As a result, differences between patients in renal reserve will lead to differences in serum creatinine increase.(15) Furthermore, seriously ill patients lose muscle mass, which means that GFR has to decline even more before serum creatinine concentration will double.(16;17) Also, patients with chronic kidney disease (CKD) have a higher baseline creatinine compared with patients with a normal kidney function. In patients with CKD, the percentile increase in serum creatinine will rise slower compared to the percentile increase in people with a healthy kidney function on baseline.(15) Because the RIFLE criteria use only a percentage change in serum creatinine for the first two classes (Risk and Injury), patients with CKD are at risk to be under-classified. For the third class (Failure), the RIFLE criteria do give an absolute change when baseline creatinine is >350µmol/L. Another limitation of the RIFLE criteria is that the classification system is based on an increase in serum creatinine from a baseline creatinine value. Often a baseline creatinine value is not available. When a baseline value is not available, the ADQI group recommends a back-estimation by using the Modification of Diet in Renal Disease (MDRD) formula, assuming an estimated GFR (eGFR) of 75 mL/min/1.73 m2.(2) By using this estimated baseline creatinine, patients will be overestimated and underestimated in a RIFLE class.(18-20) If the actual creatinine clearance is higher than 75 mL/min/1.73 m2, this estimation results in under-classification of the RIFLE class. Contrary, patients with lower clearances are over-classified. Since the GFR decreases with age, the use of an eGFR 75 mL/min/1.73 m2

results in over-classification in the elderly. Improvements have been suggested: e.g. the use of creatinine value taken at the time of hospital admission, the use of the lowest creatinine level during admission(18), calculating baseline creatinine by using a newly developed equation, or the use of a gender-fixed eGFR(19). However, none of these alternative methods offered an improvement compared to the MDRD-based



estimates.(18;19) The Acute Kidney Injury Network (AKIN) proposed a refinement of the RIFLE criteria to classify patients with AKI, through use of dynamic changes in serum creatinine during the first 48 hours of admission (table 1B).(11) Use of this method reduced the need for a baseline creatinine value. However, this classification method did not seem to improve sensitivity or predictive value compared to the RIFLE criteria.(12)

Class Glomerular Filtration Rate criteria Urine Output criteria1A. RIFLE criteriaRisk Serum creatinine ≥1.5x or decrease in GFR ≥25% from

baseline<0.5 mL/kg/h x 6 h

Injury Serum creatinine ≥2 or decrease in GFR ≥50% from baseline <0.5 mL/kg/h x 12 h

Failure Serum creatinine ≥3 or decrease in GFR ≥75% from baseline or an absolute serum creatinine ≥354 μmol/L with an acute rise of at least 44 μmol/L

<0.3 mL/kg/h x 24 horanuria x12 h

Loss Persistent acute renal failure = complete loss of kidney function >4 weeks

End-stage End-stage kidney disease > 3 months1B. AKIN classification Stage I Increase in serum creatinine ≥26.2 μmol/L <48 hours or

increase to ≥1.5x from baseline<0.5 mL/kg/h x 6 h

Stage II Increase in serum creatinine ≥2x from baseline <0.5 mL/kg/h x 12 h

Stage III Increase in serum creatinine ≥3x from baseline or serum creatinine ≥354 μmol/L with an acute rise of at least 44 μmol/L or initiation of renal replacement therapy.

<0.3 mL/kg/h x 24 horanuria x 12 h

Table 1. The RIFLE criteria and the AKIN classification.Two systems to classify acute kidney injury: the Risk, Injury, Failure, Loss and End-stage kidney disease (RIFLE) criteria and the Acute Kidney Injury Network (AKIN) classification. Abbreviations: GFR = glomerular filtration rate.

AKI is frequently seen as a complication during community-acquired pneumonia (CAP).(21) CAP is a common cause of hospital admission.(22) Apart from a high mortality rate, the healthcare costs related to CAP are significant.(22-25) The incidence of AKI in CAP, as determined using the RIFLE criteria, ranges in different studies from 18% to 34%.(21;26) Two different trials investigated CAP related AKI. In a prospective observational study in patients with CAP, the RIFLE criteria independently predicted an increased 30-day mortality rate and a higher need for renal replacement therapy.(21) The second study investigated the epidemiology and immune response of CAP related AKI (classified according to the RIFLE criteria). CAP patients with AKI showed higher biomarker concentrations (interleukin-6 (IL-6), tumor necrosis factor (TNF) and D-dimer) compared with CAP patients without AKI. They also found higher mortality in patients with CAP complicated by AKI compared with patients with CAP not complicated by AKI, even among patients with non-severe CAP.(26)In non septic AKI there is most probably, as in septic AKI, a systemic role of inflammation markers. Patients with non severe CAP with AKI showed higher values of inflammation markers (white cell count, C-reactive protein, IL-6, TNF, and D-dimer) compared to patients with non-severe CAP



without AKI, at time of presentation on the emergency department and during their first week.(26)

Much effort has been put in identifying early markers of AKI.(17;20;27;28)Albuminuria was proposed as a useful biomarker of AKI in two recent studies, based mainly on investigations in mice and rats.(28;29) In the first study(28), albuminuria and proteinuria were tested as biomarker of AKI. Total-protein/creatinine ratio (P/C ratio) and albumin/creatinine ratio (A/C ratio) were measured in mice in five different AKI models: maleate (a nephrotoxic substance which leads to proximal tubule injury), ischemia-reperfusion, rhabdomyolysis, endotoxemia and urethral obstruction. In the first three models (maleate, ischemia-reperfusion and rhabsomyolysis) both the P/C ratio and the A/C ratio were elevated. In the endotoxemia model, neither the P/C ratio nor the A/C ratio was elevated. In the urethral obstruction model, only the P/C ratio was elevated. They also performed a clinical assessment in three different populations: in 15 critical ill patients with AKI (determined using the AKIN classification), in 14 critical ill patients without AKI, and in 6 healthy volunteers, they measured the P/C ratio and the A/C ratio. In the ill patients without AKI compared with the healthy volunteers, both the P/C ratio and the A/C ratio were modestly elevated (p:0.07 and p<0.025, respectively). The albumin/total-protein ratio was not statistically different between the two groups. In the ill patients with AKI compared with the ill patients without AKI, both the P/C ratio and the A/C ratio were markedly elevated (p<0.015 and p<0.01, respectively). The albumin/total-protein ratio was significantly elevated in the ill patients with AKI compared with the ill patients without AKI, as the contribution of albumin rose of 15% to 50% (p<0.005). Therefore, the investigators concluded that the A/C ratio was a better marker for AKI compared to the P/C ratio. The area under the receiver operating characteristic curves were comparable for the P/C ratio and the A/C ratio: 0.729 versus 0.874, respectively.(28) The second study (29) evaluated the performance of albumin as AKI biomarker in rats treated with either kidney toxicants, non-renal toxicants or diuretic treatments. They concluded that to detect AKI, albumin is a more sensitive biomarker compared to a rise in serum creatinine.(29)

Data on proteinuria during sepsis are sparse, however, micro-albuminuria is frequently seen in septic patients.(30-32) Pro-inflammatory cytokines affect glomerular permeability, which leads to proteinuria.(33;34) Proteinuria may also result from a defect in the proximal tubular reabsorption.(35)Normally, a small fraction of serum albumin (<1 out of 1,000 albumin molecules) passes the glomerular basement membrane and is reabsorbed in the proximal tubules.(29) Older and recent literature has shown that in patients with CKD, as well as in the general population, the presence of proteinuria predicts outcome, independent of renal function.(36-40) Two community-based cohort studies were performed among healthy individuals showing proteinuria to be a predictor of an increased development of AKI and increased mortality.(37;38) The first study showed an increased risk of hospital admission for AKI in people with mild or heavy proteinuria for all values of eGFR. This suggested that baseline proteinuria,



in addition to kidney function, might be a valuable predictor to identify people at risk for AKI.(37) The next study reported an increased mortality rate of more than two-fold among participants with heavy proteinuria and an eGFR of >60 mL/min/1.73 m2 on baseline, compared with people with an eGFR 45-60 mL/min/1.73 m2 and normal protein excretion. Also, the risk of myocardial infarction and progression to kidney failure was increased in people with a higher level of proteinuria.(38) However, the predictive value of proteinuria during an episode of acute illness has not been reported yet. There was one study that reported the incidence of proteinuria in 109 patients with CAP. They found proteinuria in 54% of the patients. Patients with a Streptococcus pneumoniae caused CAP had significantly more often proteinuria compared with patients with a Mycoplasma pneumoniae caused or a Chlamydia pneumoniae caused CAP: 91.7% (number of patients (n)=11) versus 40.9% (n=9) and 50.0% (n=9), respectively (p:0.046).(41) A case report describes a transient proteinuria in a patient with a M. pneumoniae pneumonia.(42) Other case reports mentioning proteinuria in CAP are all in the paediatric population, where proteinuria is based on the known pathology of acute glomerulonephritis.(43)

In the present study, the incidence and the predictive value of proteinuria during admission will be investigated, in patients admitted with severe and non-severe CAP.

Furthermore, a possible relationship between proteinuria and the pathogen will be explored.

Third, use of an age-and-gender adjusted eGFR is compared with the use of a fixed eGFR of 75 mL/min/1.73 m2 for predicting the RIFLE class.

Thesis



The aim of the present study was to investigate the incidence and predictive value of proteinuria on admission in patients with severe and non-severe CAP. Second, a possible relationship between the causing pathogen and proteinuria was explored. Furthermore, the accuracy of the use of an age- and gender-adjusted eGFR value for classification in the RIFLE classes, was compared with the use of a fixed eGFR of 75 mL/min/1.73 m2.

Primary outcome:

- Is there a difference in length of stay (LOS) between patients with and patients without proteinuria?

Secondary outcomes:

- Is proteinuria related to in-hospital mortality?- Is proteinuria related to one-year mortality?

Side studies:

- Is proteinuria related to AKI?- Is proteinuria related to seriousness of the CAP?- Is proteinuria related to sepsis?- Is proteinuria related to a certain causing pathogen?

- Are the RIFLE criteria more accurately classified when using an age- and gender-adjusted eGFR compared with using a fixed eGFR of 75 mL/min/1.73 m2?



Materials and Methods

Study protocol

This is a retrospective observational analysis of prospectively collected data. Proteinuria and the RIFLE criteria were investigated in patients hospitalized with severe and non-severe CAP. Proteinuria and the RIFLE criteria were related to baseline characteristics and outcome (length of stay (LOS), in-hospital mortality, and one-year mortality).

Data were obtained from patients >18 years of age, who were hospitalized with CAP and who participated in two consecutive clinical trials with similar in- and exclusion criteria.(44;45) Patients were hospitalized during the period from October 2004 to August 2006 or November 2007 to October 2010 in a general 880-bed and a general 550-bed teaching hospital in The Netherlands. Baseline characteristics and outcomes of both cohorts are shown in supplement 1 (table S1, page 28). Selection of the antibiotic treatment was decided by the medical team in charge and was done according to the national guidelines.(46) In the second cohort, patients were randomized to receive either dexamethasone or placebo during the first four days of admission. They found that administration of dexamethasone reduced median LOS within one day.(45) CAP was defined as a new infiltrate on the chest radiograph, as evaluated by an experienced radiologist, for patients with at least two of the following clinical symptoms of pneumonia: cough, sputum production, temperature >38.0 °C or <36.0 °C, signs on chest auscultation compatible with pneumonia, leukocytosis or leucopenia (white blood count >10x109/L, <4x109/L, respectively) or >10% rods in leukocyte differentiation, or C-reactive protein >15 mg/dL. Patients with defined immunodeficiencies (a known congenital or acquired immunodeficiency, chemotherapy within the last 6 weeks, oral corticosteroid use in the last 6 weeks, immunosuppressive medication within the last 6 weeks), or hematological malignancies were excluded. A total of 505 patients were enrolled in the two cohorts. Nine patients on renal replacement therapy were excluded in this study.

Data collection

In the 496 patients, blood samples were obtained at day 0 (=day of admission) and days 1 to 7 to measure renal function and electrolytes. Urine collection was not part of the study protocols. However, in 238 patients, a urine sample, taken on the day of admission, was available. These urine samples were tested for protein, first by standard reagent strip with a threshold of 0.15 mg/L, followed by the laboratorial quantification of total protein by turbidimetric method with a lower threshold of 40 mg/L (Roche Diagnostics cobas C501, TPUC3). Urine creatinine was measured to correct for concentration. For 81 additional patients, stored frozen (-20 ºC) urine samples were available from the day of admission. Total protein and creatinine were measured in these samples. In total, 319/496 patients whom had available urine samples



could be included in this study. Baseline characteristics of the participants (e.g. age, comorbidities), duration of hospital stay and survival were assessed; the Pneumonia Severity Index (PSI, shown in supplement 2, page 29)(47) was calculated on admission. Sepsis was defined as having ≥2 systemic inflammatory response syndrome (SIRS) criteria (supplement 3, page 30). Serum baseline creatinine values were obtained by searching for creatinine values in the hospital and general practitioner database. Preferably, the sample was taken in the three months before admission. Samples taken during an acute phase of illness were excluded.

Proteinuria

Proteinuria was defined as a total-protein/creatinine ratio (P/C ratio) of >23 mg/mmol, following the 2002 National Kidney Foundation Disease Outcomes Quality Initiative (NFK KDOQI) guidelines.(48) A P/C ratio in a spot-urine sample is, according to earlier studies, a suitable alternative to 24-h collection for the quantification of proteinuria.(49)

RIFLE criteria

Patients were classified according to the RIFLE criteria. Baseline serum creatinine values were used if available. For patients in which no known baseline serum creatinine value was available, it was estimated using the 4-variable MDRD study equation(50), with an assumed eGFR of 75 mL/min/1.73 m2 as recommended by the ADQI group.(2) This approach to estimation has been validated in patients without chronic renal failure.(2) Serum creatinine measured on the day of admission (day 0) was used to range patients in RIFLE class ‘Risk’, ‘Injury’ or ‘Failure’ if applicable. Patients were classified as class ‘Risk’ if serum creatinine was 1.5 times baseline creatinine, and class ‘Injury’ if serum creatinine was twice the baseline value. Class ‘Failure’ denoted serum creatinine levels that were three-fold higher than the baseline, baseline serum creatinine ≥4 mg/dL (354 µmol/L) with an acute rise >0.5 mg/dL (44 µmol/L) or ongoing treatment with renal replacement therapy. By measuring the urine output over the first several hours, the patient can be reclassified according to the RIFLE criteria. It was not possible to reclassify patients as urine output measures were not available. For this study, the outcome RIFLE categories of loss and end-stage kidney failure were not evaluated. Furthermore, in this study, class 1 refers to class ‘Risk’, class 2 refers to class ‘Injury’ and class 3 refers to class ‘Failure’.

Pathogen identification

From each patient, at least two sets of separate blood and sputum samples were cultured. Mycoplasma pneumoniae, Legionella pneumophila, Coxiella burnetii, and Chlamydophila pneumoniae and psittaci were analyzed in sputum samples by polymerase chain reaction for atypical pathogens. Streptococcus pneumoniae and Legionella pneumophila serogroup 1 were searched by sampling urine for antigen testing. Serum samples taken on the day of hospital admission and day 10 were analyzed



in pairs for detection of a fourfold rise of antibodies to respiratory viruses, Coxiella burnetii, Mycoplasma pneumoniae, and Chlamydophila psittaci by complement fixation assay. Pharyngeal samples were taken for viral culture.

Age- and gender-adjusted eGFR

In the this side study analysis on the age- and gender-adjusted eGFR, only patients which had a known baseline serum creatinine value were included. As a result, the patient cohort for this analysis differs from the patient cohort used in the analyses on proteinuria; patients without a urine sample but with a known baseline serum creatinine value, were included in this side analysis. Furthermore, patients with a urine sample but without a baseline serum creatinine sample, were excluded. In total, 271 patients could be included in this analysis, from which 171 patients (63%) were also included in the main analyses on proteinuria. Baseline creatinine values were defined as “creatinine-actual”. The RIFLE criteria were determined thrice. First, the RIFLE criteria were calculated using creatinine-actual. Second, the RIFLE criteria were calculated using a creatinine value which was back-calculated using the MDRD-formula, with a fixed eGFR of 75 mL/min/1.73 m2 (defined as “creatinine-75”), suggested by the ADQI group.(2) Third, the RIFLE criteria were calculated using a creatinine value back-calculated with an age- and gender-adjusted eGFR (defined as “creatinine-age”), obtained in a population around Nijmegen.(51)

Outcomes

Outcome was investigated with length of hospital stay as the primary outcome. The number of days until discharge or death was counted. Secondary outcomes were in-hospital mortality and one-year mortality. One-year mortality was assessed by checking whether the patient visited the hospital after the first year of discharge and if not, the general practitioner of the patient was contacted to ask if the patient was still alive. The date of death was recorded. Four patients did not reach the one-year survival endpoint. Three patients were lost to follow-up. A relationship between the quantity of proteinuria and AKI, classified according to the RIFLE criteria, was investigated. Seriousness of the CAP (according to the PSI) and sepsis (≥2 SIRS criteria), were related to the quantity of proteinuria. Pathogens were linked to the presence and quantity of proteinuria. The RIFLE criteria based on use of an age- and gender-adjusted eGFR were compared with the RIFLE criteria based on use of a fixed eGFR of 75 mL/min/1.73 m2.

Statistical analyses

All data were analyzed with SPSS statistical software for Windows, version 19.0. Categorical data on baseline characteristics were compared using the X2 test or Fisher’s exact test. Student’s t-test was used when data



were normally distributed. Non-parametrical data were analyzed using the Mann-Whitney U-test. For length of stay, patients who died during their hospital stay were removed from this calculation, because patients who died early would count as having a short length of hospital stay. Cox proportional hazard regression analysis was used for univariate and multivariate analyses of LOS and one-year mortality. For LOS, the event was hospital discharge. Patients who died during hospital stay were censored. Binary logistic regression analysis was used for univariate and multivariate regression analysis of in-hospital mortality. In the multivariate regression analyses, the following variables were used: proteinuria, the RIFLE criteria (RIFLE class 0 versus RIFLE classes 1-3), PSI severity (I-III versus IV-V), and dexamethasone, or the combined variable proteinuria and RIFLE classes 1-3, PSI severity, and dexamethasone. No statistical variable selection method was used. Kaplan Meier analysis was applied to visualize the effect of proteinuria and RIFLE criteria on LOS, and of proteinuria and RIFLE classes 1-3 combined on one-year mortality. In Kaplan Meier analysis, the log-rank test was used.Three sensitivity analyses were done. In the first sensitivity analysis, patients for whom total protein had been quantified using a stored frozen urine sample were excluded. The literature shows that urine storage in -20ºC can lead to the underestimation of protein quantification.(52;53) In the next sensitivity analysis, patients who received dexamethasone during their admission were excluded. This analysis was added to rule out an effect on the results on outcome, as dexamethasone influenced LOS.(45) The third sensitivity analysis was done in all patients arranged for AKI according to the AKIN classification instead of the RIFLE criteria. The AKIN proposed a refinement of the RIFLE criteria to improve results on outcome.(11)Kruskal-Wallis H test was used to investigate whether there was a difference in quantity of the proteinuria for different PSI scores, for different RIFLE classes, and for the amount of SIRS criteria. The RIFLE classification based on creatinine-75 and creatinine-age were compared with the RIFLE classification based on creatinine-actual, the reference value. Wilcoxon Signed Rank Test was used to compare division in RIFLE classes. McNemar’s Test was used to compare classification in kidney injury (RIFLE classes 1-3) versus no kidney injury (RIFLE class 0). For all analyses, a p-value of <0.05 was considered statistically significant.





Results

Study population

The total study population consisted of 496 patients. In 319/496 patients (64%), a urine sample taken on the day of admission was available. We compared baseline characteristics and outcomes in the 319 patients with available urine samples to the 177 patients who did not provide a urine sample upon admission. Patients with a urine sample had less often chronic obstructive pulmonary disease (COPD) (15% versus 28%), were more often staged in RIFLE classes 1-3 (16% versus 8%), had a lower systolic blood pressure (131.0 ± 22.2 versus 135.2 ± 23.2) and received more often dexamethasone (36% versus 18%). Remaining baseline characteristics were not statistically different. One-year mortality was higher in the cohort with a urine sample available compared with the cohort without a urine sample available: 11% versus 6%. This difference was borderline significant (p:0.06). The baseline table is shown in supplement 4 (table S4, page 31). In the 319 patients for whom urine samples were available, 198 (62%) patients had proteinuria (P/C ratio >23 mg/mmol). The baseline characteristics of subjects with and without proteinuria are shown in table 2. All further analyses were performed in the 319 patients in whom proteinuria could be quantified.

Outcome

In this study, median LOS was 8.0 days [6.0-12.0]; 19/319

Internal Medicine, St. Antonius Hospital, Nieuwegein, February - July 2011

Proteinurian = 198 (62%)

No proteinurian = 121 (38%)

p-value

Male sex 113 (57%) 67 (55%) 0.77Age (year) 68.5 [52.5-

80.0]67.0 [49.0-79.0]

0.27

Race 1

- Caucasian- Other

196 (99%)2 (1%)

119 (98%)2 (2%) 0.62

Nursing-home resident 12 ( 6%) 4 (3%) 0.27Comorbidities 2

- Chronic kidney disease- Diabetes mellitus - Liver disease - Neoplastic disease - Congestive heart

failure- COPD

16 (8%)31 (16%)0 15 (8%)29 (15%)26 (13%)

9 (7%)20 (17%)2 (2%)8 (7%)18 (15%)21 (17%)

0.840.840.140.750.960.30

Sepsis (SIRS criteria ≥2) 171 (90%) 89 (80%) 0.024Pneumonia Severity Index class

- Class I – III- Class IV-V

96 (49%)102 (52%)

79 (65%)42 (35%) 0.003

RIFLE class- RIFLE class 0 - RIFLE classes 1-3

157 (79%)41 (21%)

112 (93%)9 (7%) 0.002

Systemic blood pressure- Systolic (mm Hg) - Diastolic (mm Hg)

132.0 (21.9)73.2 (11.8)

129.2 (22.7)74.2 (13.5)

0.280.49

Temperature (ºC) 38.3 (1.1) 38.1 (1.1) 0.027Laboratory parameters

- C-reactive protein (mg/L)

- White blood count (x109/L)

- Creatinine (µmol/L) - Urea (mmol/L)

264.1 (142.3)15.3 (6.8)91.0 [72.0-126.5]8.4 [5.3-12.6]

147.6 (112.4)13.8 (6.5)83.0 [69.0-108.5]6.3 [4.1-8.9]

<0.00010.060.018*<0.0001

Current medication- NSAID- ACE inhibitor or ARB

20 (10%)36 (18%)

16 (13%)31 (12%)

0.380.11

Dexamethasone 3 60 (30%) 56 (46%) 0.004Table 2. Baseline characteristics of enrolled patients. Data are presented as mean (±), median [interquartile range] or number (%). Abbreviations: ACE inhibitor = angiotensin-converting enzyme inhibitor, ARB = angiotensin receptor blocker, COPD = chronic obstructive pulmonary disease, NSAID = nonsteroidal anti-inflammatory drug. 1 Race was self-reported. 2 Patients could have more than one comorbidity. 3 As part of a clinical trial.

14


patients (6%) died during their hospital stay. One-year mortality was 51/312 patients (16%).



Proteinuria and outcome

The median LOS of patients with proteinuria was 9.0 days [interquartile range (IQR) 7.0-14.0], as compared to 7.0 days [IQR 5.0-10.0] for patients without proteinuria (hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.28-2.06). Kaplan Meier analysis for LOS is shown in figure 1A. Proteinuria was associated with increased in-hospital mortality: 17/198 patients (8.6%) with proteinuria died during admission, compared to 2/121 patients (1.7%) without proteinuria (odds ratio (OR) 5.59, 95% CI 1.27-24.63). The difference in one-year mortality in patients with proteinuria did not reach statistical difference: 37/193 patients (19%) with proteinuria died, compared with 14/119 patients (12%) without proteinuria (hazard ratio (HR) 1.74, 95% CI 0.94-3.22). Kaplan Meier analysis for one-year mortality is shown in supplement 5 (figure S1A, page 32).

RIFLE criteria and outcome

Patients in RIFLE classes 1-3 had a median LOS of 9.0 days [IQR 7.0-14.0], compared with 8.0 days [IQR 6.0-12.0] in patients classified as RIFLE class 0 (HR 1.55, 95% CI 1.12-2.15). Kaplan Meier analysis for LOS is shown in figure 1B. In-hospital mortality occurred in 7/50 patients (14%) labeled as RIFLE classes 1-3, as compared to 11/268 patients (4.1%) in RIFLE class 0 (OR 3.81, 95% CI 1.40-10.35). One-year mortality increased in patients classified as RIFLE classes 1-3 compared with patients labeled as RIFLE class 0: 16/47 patients (34%) in RIFLE classes 1-3 died compared to 34/264 (13%) of the patients in RIFLE


Figure 1. Kaplan Meier analysis of length of stay in patients hospitalized with community-acquired pneumonia.A: The effect of proteinuria on length of stay (log-rank p<0.001).B: The effect of RIFLE classification on length of stay (log-rank p:0.005).

A

B


class 0 (HR 3.06, 95% CI 1.69-5.55). Kaplan Meier analysis for one-year mortality is shown in supplement 5 (figure S1B, page 32).

Of the total population, 64% of the patients had an urine sample available and was included in the analyses. To account for the possible impact of selection bias on our results, the predictive value of the RIFLE criteria was analyzed for the 36% of the patients without a urine sample that was not included in the analyses. In this cohort, the RIFLE criteria did predict the LOS, adjusted and unadjusted. Neither in-hospital mortality nor one-year mortality was predicted by the RIFLE criteria. Odds and hazard ratios are shown in supplement 6 (table S5, page 33).

Proteinuria versus the RIFLE criteria, multivariate analyses

Proteinuria was an independent predictor for LOS: HR 1.38, 95% CI 1.08-1.75. The RIFLE criteria appeared not to be an independent predictor (HR 1.21, 95% CI 0.86-1.71). The administration of dexamethasone and PSI score were also independent predictors of LOS in this model. For in-hospital mortality, proteinuria had an OR 3.27, 95% CI 0.69-15.45 and RIFLE criteria had an OR 1.81, 95% CI 0.62-5.27. The RIFLE criteria were compared with proteinuria as predictor for one-year mortality. Neither proteinuria nor the RIFLE criteria were independent predictors when PSI severity (I-III versus IV-V) and dexamethasone were in the model. Odds and hazard ratios are shown in figure 2. The same analyses were performed for the combinedvariable proteinuria and RIFLE classes 1-3. Figure 3 shows Kaplan Meier analysis of one-year survival of the cohort stratified in four subgroups

(neither RIFLE classes 1-3 nor proteinuria, either RIFLE classes 1-3 or proteinuria, or both RIFLE classes 1-3 and proteinuria). All univariate analyses


Figure 2. Odds ratios and hazard ratios for all outcomes for proteinuria and RIFLE classes 1-3. Adjusted ratios were calculated for proteinuria and RIFLE classes 1-3 in one model together with PSI severity (I-III versus IV-V) and dexamethasone. Abbreviations: HR = hazard ratio, OR = odds ratio. *


were significant, in contrast to all multivariate results of this combined variable. All odds and hazard ratios can be found in supplement 7 (table S6, page 34).


Figure 3. Kaplan Meier analysis of the effect of four subgroups on one-year mortality. One-year mortality was significantly different between the four subgroups (log-


Sensitivity analyses

Three sensitivity analyses were performed. All results are shown in table 3.In the first sensitivity analysis, patients in which total protein was quantified using a stored frozen urine sample (n=81) were excluded. Analyses in the other 238 patients did not change the results. Univariate analysis identified proteinuria as a significant predictor for LOS and in-hospital mortality. One-year mortality did not reach significance, similar to the results obtained by earlier analysis. The RIFLE criteria were still significant for LOS, in-hospital mortality, and one-year mortality. In multivariate analysis, proteinuria remained an independent predictor for LOS, while the RIFLE criteria did not. For in-hospital mortality and for one-year mortality, similar to earlier analysis, neither proteinuria nor the RIFLE criteria were an independent predictor. In the second sensitivity analysis, patients who received dexamethasone as part of the study protocol, were excluded. Univariate, LOS was not significantly anymore for patients classified in RIFLE classes 1-3. In-hospital mortality was not significant anymore for proteinuria; one-year mortality was significant for proteinuria. The third sensitivity analysis was accomplished using the AKIN classification instead of the RIFLE criteria. All outcomes were identical to earlier analyses with the use of the RIFLE criteria.

RIFLE criteriaAll patients

RIFLE criteriaFrozen urine

samples excluded

RIFLE criteriaPatients who

received dexamethasone

excluded

AKIN classificationAll patients

N 319 238 190 319Unadjusted OR or HR (95% CI) OR or HR (95% CI) OR or HR (95% CI) OR or HR (95%

CI)

LOSProteinuria 1.63 (1.28-2.06) 1.72 (1.30-2.26) 1.69 (1.24-2.29) 1.63 (1.28-

2.06)AKI criteria 1.55 (1.12-2.15) 1.46 (1.02-2.09) NS 1.53 (1.12-

2.08)In-hospital mort

Proteinuria 5.59 (1.27-24.63) 9.67 (1.25-74.50) NS 5.59 (1.27-24.63)

AKI criteria 3.81 (1.40-10.35) 3.89 (1.36-11.10) 3.33 (1.02-10.89) 3.18 (1.18-8.61)

One-year mort

Proteinuria NS NS 3.52 (1.23-10.06) NSAKI criteria 3.06 (1.69-5.55) 2.64 (1.39-5.01) 3.21 (1.54-6.71) 2.51 (1.39-

4.56)Adjusted OR/ HR (95% CI) OR/ HR (95% CI) OR/ HR (95% CI) OR/ HR (95% CI)

LOSProteinuriaAKI criteria

1.38 (1.08-1.75)NS

1.49 (1.12-1.98)NS

1.52 (1.10-2.08)NS

1.39 (1.09-1.77)NS

In-hospital mort

ProteinuriaAKI criteria

NSNS

NSNS

NSNS

NSNS

One-year



mortProteinuriaAKI criteria

NSNS

NSNS

NSNS

NSNS

Table 3. Outcomes of the main analysis plus three sensitivity analyses.Odds ratios (OR) and hazard ratios (HR) with 95% confidence intervals (CI) were calculated in three subgroups. Abbreviations: AKI = acute kidney injury, LOS = length of stay, mort = mortality, N = number of patients, NS = not significant.

Quantity of proteinuria

The quantity of proteinuria was related to the severity of the pneumonia (arranged according to the PSI), to the severity of AKI (classified according to the RIFLE criteria), and to the number of present SIRS criteria. Quantification in relation to the causing pathogen is described in the next subheading. Patients in PSI class I-III (n=175) showed more often proteinuria compared with patients in PSI class IV-V (n=144) (p:0.003), as shown earlier in the baseline table (table 1, page 12). Quantified in all patients, the median P/C ratio of patients in PSI class I-III was 28.2 mg/mmol [4.5-68.2], compared with 48.7 mg/mmol [5.6-85.3] in patients in PSI class IV-V (p:0.01). Selected only patients with proteinuria, the median P/C ratio of patients in PSI class I-III (n=96) was 65.3 mg/mmol [42.7-90.0] compared with 65.6 mg/mmol [46.6-111.0] in patients in PSI class IV-V (n=102) (p:0.20). The quantity of proteinuria for each PSI class individually is shown in figure 4 as median [IQR] (p:0.01).

As shown in the baseline table (table 1, page 12), patients labeled as RIFLE classes 1-3 (n=50) showed more often proteinuria compared with patients labeled as RIFLE class 0 (n=268) (p:0.002). Quantified in all patients, patients in RIFLE class 0 had a median P/C ratio of 34.8 mg/mmol [0.0-70.6] compared with a median ratio of 52.6 mg/mmol [33.5-82.7] in patients labeled as RIFLE classes 1-3 (p:0.003). Selected only the


Figure 4. Quantity of proteinuria for each PSI classThe total-protein/creatinine ratio of all patients classified according to their pneumonia severity index (PSI) class.

Figure 5. Quantity of proteinuria for each RIFLE classThe total-protein/creatinine ratio of all patients classified according to the RIFLE criteria, with no kidney injury = 0, Risk =1, and Injury and Failure = 2+3.


patients with proteinuria, patients in RIFLE class 0 (n=156) had a median P/C ratio of 64.2 mg/mmol [43.4-101.1] compared with a median P/C ratio of 67.0 mg/mmol [47.0-93.3] in patients labeled as RIFLE classes 1-3 (n=41) (p:0.72). Quantity of proteinuria for each RIFLE class is shown in figure 5 as median [IQR] (p:0.007).

Patients with sepsis (≥2 SIRS criteria) had significantly more often proteinuria (table 1, page 12, p:0.024). Quantified in all patients, patients without sepsis (n=42) had a median P/C ratio of 21.5 mg/mmol [0.0-58.5] and patients with sepsis (n=260) had a ratio of 45.6 mg/mmol [9.6-79.8] (p:0.04). Selected only patients with proteinuria, patients without sepsis (n=20) had a median P/C ratio of 61.2 mg/mmol [39.6-80.0] and patients with sepsis (n=171) had a median P/C ratio of 66.3 mg/mmol [45.6-101.5] (p:0.44). Quantity of proteinuria for each number of SIRS criteria is shown in figure 6 on the previous page, as median [IQR] (p:0.06).

P/C ratios selected only patients with proteinuria are shown in supplement 8 on page 35 in figures S2 (PSI class), S3 (RIFLE class) and S4 (SIRS criteria).

Proteinuria and CAP causing pathogen

The causing pathogen was identified in 181/319 (57%) of the patients. Of the detected pathogens, 75/181 (41%) was S. pneumoniae and 57/181 (31%) was an atypical bacterium (Chlamydia species, Legionella species, Coxiella burnetii, or Mycoplasma pneumoniae). Presence and absence of proteinuria for each pathogen is shown in table 4. Quantity of proteinuria for each pathogen is shown in figure 7.


Proteinuria No Proteinuria TotalNumber of patients (%) 198 (62%) 121 (38%) 319 Streptococcus pneumoniae 52 (69%) 23 (31%) 75 Atypical Chlamydia species Legionella species Coxiella burnetti Mycoplasma pneumoniae

39 (68%) 11 (92% 13 (81%) 14 (58%) 1 (20%)

18 (32%) 1 (8%) 3 (9%) 10 (42%) 4 (60%)

57 12 16 24 5

Gram-negative bacterium 8 (47%) 9 (53%) 17 Gram-positive bacterium 8 (89%) 1 (11%) 9Viral pathogen 19 (83%) 4 (17%) 23Unknown pathogen 72 (52%) 66 (48%) 138Table 4. Incidence of proteinuria in different groups of pneumonia causing pathogens.Proteinuria was defined as total-protein/creatinine >23 mg/mmol.

21

Figure 6. Quantity of proteinuria for each number of SIRS criteriaThe total-protein/creatinine ratio of all patients classified according to the number of present systemic inflammatory response syndrome (SIRS) criteria.


Figure 7. Quantity of proteinuria for each pathogen.Total-protein/creatinine ratio for each pathogen group. Data are presented as median [interquartile range].



Age- and gender-adjusted eGFR

RIFLE classification based on creatinine-75 and creatinine-age were compared with RIFLE classification based on creatinine-actual, the reference value.

Use of creatinine-75 resulted in over-classification (e.g. classification in a higher RIFLE class) in 46/271 patients. Under-classification occurred in 19/271 patients. Classification was correct in 206/271 patients (p<0.0001, comparing creatinine-75 classification with creatinine-actual classification). Use of creatinine-age resulted in over-classification of 29/271 patients, under-classification of 20/271 patients and correct classification of 222/271 patients (p:0.04). (Figure 8)

The same analyses were performed in patients >76 years (n=96). Using creatinine-75, 27/96 patients were over-classified, 4/96 patients were under-classified and 65/96 patients were classified correct (p<0.0001). Use of creatinine-age resulted in over-classification of 12/96 patients, under-classification of 6/96 patients and correct classification of 78/96 patients (p:0.10). (Figure 9)


Figure 8. The RIFLE classification for all patients.The RIFLE classification calculated with actual creatinine (“gold standard”) compared with the RIFLE classification based on the use of a fixed eGFR of 75 mL/min/1.73 m2 (creatinine-75) (p<0.0001), and compared with the RIFLE classification based on the use of an age- and gender-adjusted eGFR (creatinine-age) (p:0.04).

Figure 9. The RIFLE classification for patients >76 years (n=96).The RIFLE classification calculated with actual creatinine (“gold standard”) compared with the RIFLE classification based on the use of a fixed eGFR of 75 mL/min/1.73 m2 (creatinine-75) (p<0.001), and compared with the RIFLE classification based on the use of an age- and gender-adjusted eGFR (creatinine-age) (p:0.10).


Next, for all patients and for the patients >76 years, division in RIFLE classes 1-3 taken together (presence of AKI according to the RIFLE criteria) and RIFLE class 0 (absence of AKI according to the RIFLE criteria), was evaluated. Results are shown in table 5.

Application of the age- and gender-adjusted eGFR to patient cohort included in the main analyses

In the study cohort of the main analyses (n=319), the age- and gender-adjusted eGFR was applied (instead of the fixed eGFR of 75 mL/min) for the RIFLE classification in

patients without a known baseline creatinine (n=148). This new RIFLE arrangement in RIFLE class 0 or RIFLE classes 1-3 classified 5 patients differently. In the new classification, 4 patients were classified in RIFLE class 0 instead of RIFLE classes 1-3, and 1 patient was classified in RIFLE classes 1-3 instead of RIFLE class 0.


RIFLE classes 1-3

RIFLE class 0

p-value

All patients (n=271)

Creatinine-actual

34 237 reference

Creatinine-75 55 216 0.007Creatinine-age 37 234 0.76Age > 76 years (n=96)

Creatinine-actual

11 85 reference

Creatinine-75 31 65 <0.0001Creatinine-age 15 81 0.45Table 5. Classification in RIFLE classes 1-3 or RIFLE class 0.The p-values present the RIFLE classification based on creatinine-75 (based on a fixed eGFR of 75 mL/min/1.73m2) and creatinine-age (age- and gender-adjusted eGFR) compared with the RIFLE classification based on creatinine-actual (known baseline creatinine).

24


Discussion

Primary and secondary outcomes

In this study, proteinuria was frequently present in patients with CAP. Its occurrence is substantially higher than the occurrence of AKI according to the RIFLE criteria. Proteinuria was independently associated with a longer length of hospital stay; the RIFLE criteria were not. For in-hospital mortality, proteinuria had a higher adjusted OR compared to the RIFLE criteria (3.27 versus 1.81), however this was not statistically significant. For the combined endpoint proteinuria and RIFLE classes 1-3, the univariate analyses were significant for all outcomes. Though, in multivariate analyses, this effect was lost.

Side studies

Proteinuria was more often present and the P/C ratio was higher in patients in PSI class IV-V compared with patients in PSI class I-III. Analyzed per class, the P/C ratio seemed to increase, but this was not significant for each consecutive class. The same trend was seen for AKI classes and the number of SIRS criteria. The trend was not significant in these variables either. Furthermore, analysing only patients with proteinuria, there was no significant difference anymore between the P/C ratios of PSI classes, RIFLE classes or number of SIRS criteria. Hence, presence or absence of proteinuria is of more value to assess the severity of the CAP than the specific amount of the proteinuria.

Legionella species and Chlamydia species seem to result more often and in a higher quantity of proteinuria. Larger studies are needed to confirm this finding.

Use of a fixed eGFR of 75 mL/min/1.73 m2 led to a significant different classification in RIFLE class compared to the use of an actual baseline creatinine (p:0.007). Use of an age- and gender-adjusted eGFR resulted in a comparable RIFLE classification compared to the use of real baseline creatinine (p:0.76). Especially for patients aged >76 years, the RIFLE classification was more accurate with the age- and gender-adjusted eGFR. However, in this study, the use of the age- and gender-adjusted creatinine did not change the results on outcome, as only five patients were classified differently.

Background

In this patient cohort, 16% of the patients was staged in RIFLE classes 1-3. This percentage is consistent with the literature on CAP.(26) The RIFLE criteria have been shown to be related with increased mortality in several groups of patients, for example in patients with severe and non-severe CAP.(21) In agreement with these studies, in univariate analysis there was increased mortality for patients staged in RIFLE classes 1-3. Contrary to previous studies, in this study, the RIFLE criteria were not an independent



predictor for in-hospital mortality or for one-year mortality when corrected for PSI score.(21) This difference in outcome could be the result of a smaller patient cohort than in most studies that investigated the RIFLE criteria. An other cause could be the fact that in 46% of the patients, the RIFLE criteria were based on an estimated baseline creatinine instead of on a known baseline creatinine. This could have resulted in underperformance of the RIFLE criteria in this study.In the current study, proteinuria was present in 62% of the patients in whom a urine sample was available, as opposed to AKI (classified according to the RIFLE criteria) in 16% of the patients. Among the 50 patients classified in RIFLE classes 1-3, 41 had proteinuria; AKI is often associated with proteinuria. On the other hand, proteinuria without AKI occurred in 156 patients. Pathophysiologic changes occurring during inflammatory disorders can affect glomerular permeability, due to the presence of pro-inflammatory cytokines.(35) Proteinuria may also result from a defect in proximal tubular reabsorption.(35) This results in transient proteinuria, as the tubular reabsorptive mechanism for albumin is close to saturation.(35) Albuminuria was proposed as a useful biomarker of AKI in two recent studies, based mainly on investigations in mice and rats.(28;29) This is the first study that investigates the predictive value of proteinuria during acute infection in a clinical setting.

Strengths and limitations

This study has several strengths. First, a urine measurement is easy to obtain in every patient. This is in contrast with the RIFLE criteria, as baseline creatinine values are often not available. Second, a urine P/C ratio quantification is an inexpensive test, as distinct from other recently introduced urinary markers for AKI, such as kidney injury molecule-1, cystatin C and neutrophil-gelatinase-associated lipocalin.(54) Third, both proteinuria and RIFLE criteria were compared as predictors of outcome. Some studies relate a possible new marker only to the RIFLE criteria and not to outcome.(27;28) RIFLE criteria represent an established method with which to predict outcome in AKI, but it is known that this standard is not perfect.(14) Comparing a new marker to an imperfect standard can lead to a new marker with the same intrinsic limitations. In this study, an independent relation of proteinuria with outcome is shown. Fourth, only three patients (0.9%) were lost to follow-up, and could not be included to calculate one-year mortality.

Our study has limitations. Only 319/496 (64%) of the patient population who had a useful urine sample available, could be included. Patients with a urine sample were more often staged in RIFLE classes 1-3, were slightly older, were more often known with CKD, and less often with COPD. Thus, availability of a urine sample was not random, and selection may have occurred. This could have had an effect on the high prevalence of proteinuria found in our study. Because the predictive value of presence of proteinuria was investigated, this probable confounder does not challenge the conclusion that proteinuria predicts a longer length of stay. Also, there was no significant difference in outcomes between these cohorts.



Furthermore, we analyzed the predictive value of the RIFLE criteria in the cohort of patients without a urine sample. The RIFLE criteria predicted independently LOS in those patients, but did also not predict in-hospital mortality nor one-year mortality. A second limitation was that cohorts from two consecutive studies were used for all analyses. In- and exclusion criteria were the same, but there were differences in results on outcome for presence of proteinuria and for LOS. The LOS was significantly longer in cohort 1 compared to cohort 2 (p<0.0001). This longer LOS is probably the result of a reduction in the LOS over time: cohort 1 was included from 2004 to 2006 and cohort 2 from 2007 to 2010. In cohort 1, patients had more often proteinuria compared with patients from cohort 2: 66/88 (75%) in cohort 1 versus 132/231 (57%) in cohort 2 (p:0.003). Of the 198 patients with proteinuria in the total study cohort, 66/198 patients (33%) were from cohort 1 and 132/198 patients (67%) were from cohort 2. As a result, the longer LOS in cohort 1 could have influenced the overall longer LOS for patients with proteinuria, but only marginally, as only 33% of the patients with proteinuria was from cohort 1. It was not possible to perform the analyses in the two cohorts individually, as cohort 1 consisted of too little patients.Third, not in all patients a baseline creatinine value was available. In patients in which a baseline creatinine value was not available, an estimated baseline creatinine was back-calculated by using an eGFR of 75 mL/min/1.73 m2, as recommended by the ADQI group.(2) However, by using this estimated baseline creatinine, the RIFLE class may be over-classified or under-classified.(18;19) The availability of known baseline creatinine values (54% of patients), is higher than in a previous study on AKI as determined using the RIFLE criteria in patients with CAP.(26) The AKIN criteria were proposed as a refinement of the RIFLE criteria(11). In this study, a sensitivity analysis was performed with the AKIN classification instead of the RIFLE criteria. Similar to earlier studies, this did not change or improve the results on outcome.(12) Furthermore, in this study the total-protein/creatinine was used, with a threshold of 23 mg/mmol. This was recommended by the NFK KDOQI 2002 guidelines.(48) The NFK KDOQI 2007 guidelines do not indicate a particular P/C ratio threshold value. Decided was to use the threshold given in the 2002 guidelines, as it is the lowest value specified in guidelines. Micro-albuminuria and the albumin/creatinine ratio (A/C ratio) might be more sensitive to detect AKI compared with the P/C ratio.(28;55) The Scottish Intercollegiate Guidelines Network (SIGN) CKD 2008 guidelines state that both the P/C ratio and the A/C ratio are accurate methods with which to rule out proteinuria, when the probability of proteinuria is high.(56) A cross-sectional study in an Australian adult population concluded that among those with known or suspected renal disease, measurements of total protein may provide superior diagnostic and prognostic information compared with measuring albuminuria, as 8% of the people with proteinuria tested negative for albuminuria.(57) SIGN guidelines also state that use of the P/C ratio outweighs use of the A/C ratio when conformation is needed for diagnostic purposes, because of the lower cost of obtaining the P/C ratio.(56) Disadvantages that are named against using proteinuria is that it is not specific enough. Proteinuria can be present in



other circumstances besides AKI, for example in patients with fever, dehydration, diabetes or hypertension and after exercise. In the baseline characteristics, there were no differences in diabetes or hypertension between patients with and patients without proteinuria. Using the P/C ratio instead of the total protein excretion excludes dehydration to play a role. Baseline values of urinary protein excretion were not available. Therefore it was not possible to distinguish between acute and chronic proteinuria. The presence of proteinuria in 62% of patients (a percentage that is much higher than the presence of proteinuria in the general population(58)) suggests that the observed proteinuria results from CAP in most patients. Patients in the group with proteinuria did not have more often CKD compared with the patients in the group without proteinuria (table 1). Urinary protein measurements obtained after the CAP episode were not available either. It would be interesting to see if the proteinuria was transient or persistent. The course of kidney injury during CAP requires further investigation. Finally, data were used which were primarily collected to investigate the influence of dexamethasone on LOS in patients hospitalized with CAP.(45) Patients which were included in our analysis received dexamethason more often. This could have led to a shorter LOS in the overall study cohort than could be assumed in a normal population hospitalized with CAP. Furthermore, patients without proteinuria received dexamethasone more frequently compared to patients with proteinuria. This could have influenced the longer LOS found for patients with proteinuria. A sensitivity analysis was performed, in which patients who received dexamethasone were excluded. The LOS for patients with proteinuria was still significantly different compared with the LOS for patients without proteinuria, both unadjusted and adjusted. Furthermore, there was correction for the use of dexamethasone in multivariate analyses on outcome.

Conclusion

Proteinuria is common in patients with CAP. In contrast to the RIFLE criteria, proteinuria is an independent predictor for length of hospital stay. Proteinuria can be a marker for outcome, with the advantage of circumventing the need for a baseline creatinine sample, and may be used to assess the severity of CAP as well.

Acknowledgements

I would like to thank all people that helped me realizing this manuscript. First of all, I would like to thank dr. Sabine Meijvis for her assistance, her critical revises, and the guidance in the world of research in medicine. Second, I would like to thank dr. Willem Jan Bos, whose supervision was excellent and who had, despite his busy schedule, always time to answer my questions. Furthermore, I want to thank professor dr. Gerjan Navis for her critical revision and dr. Hans Kelder for verifying my statistical analyses. Last, I want to thank my family, especially my mother and my younger sister, for their final improvements in the lay out.





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Supplements

Supplement 1. Table S1Patient cohort 1§

n = 88 (45%)

Patient cohort 2§§

n = 231 (77%)

p-value

Male sex 51 (58%) 129 (56%) 0.73Age (year) 69.0 [53.3-

80.0]67 [51.0-80.0] 0.89

Race 1

- Caucasian - Other

88 (100%)0

227 (98%)4 (2%) 0.58

Nursing-home resident 3 (3%) 13 (6%) 0.57Comorbidities 2

- Chronic kidney disease- Diabetes mellitus- Liver disease- Neoplastic disease - Congestive heart

failure- COPD

3 (3%)17 (19%)07 (8%)8 (9%)20 (23%)

13 (6%)34 (15%)2 (1%)16 (7%)39 (17%)27 (12%)

0.070.321.000.750.080.013


- Class I-III - Class IV-V

51 (58%37 (42%)

124 (54%) 107 (46%) 0.49

RIFLE class- RIFLE class 0- RIFLE classes 1-3

72 (82%)16 (18%)

196 (85%)34 (15%) 0.45

Systemic blood pressure- Systolic (mm Hg)- Diastolic (mm Hg)

129.0 (21.4)70.4 (12.5)

131.7 (22.5)74.7 (12.3)

0.330.005


- C-reactive protein (mg/L)

- White blood count (x 109/L)

- Creatinine (µmol/L)- Urea (mmol/L)

235.7 (138.7)16.2 (7.4)92.0 [72.3-135.0]7.7 [5.3-12.3]

213.8 (144.7)14.2 (6.4)87.0 [70.0-113.3]6.9 [4.7-10.8]

0.220.0180.070.18

Current medication- NSAID - ACE inhibitor and/or

ARB

5 (6%)20 (23%)

31 (14%)47 (20%)

0.0460.64

Outcomes- Presence of proteinuria - Length of stay- In-hospital mortality- One-year mortality

66 (75%)11.0 [8.0-16.0]5 (6%)13 (15%)

132 (57%)8.0 [5.5-11.0]14 (6%)38 (17%)

0.003<0.00010.900.72

Table S1. Baseline characteristics of the two study cohorts§ Cohort 1: Study population included in the period October 2004 to August 2006 in the 880-bed St. Antonius Hospital in Nieuwegein. Total number of patients included: 197.§§ Cohort 2: Study population included in the period November 2007 to October 2010 either in the 880-bed St. Antonius Hospital in Nieuwegein or in the 550-bed Gelderse Vallei Hospital in Ede. Total number of patients included: 300.Data are presented as mean (±), median [interquartile range] or number (%).Abbreviations: ACE inhibitor = angiotensin-converting enzyme, ARB = angiotensin receptor blocker, COPD = chronic obstructive pulmonary disease, NSAID = nonsteroidal anti-inflammatory drug.1 Race was self-reported. 2 Patients could have more than one comorbidity.



Supplement 2. Pneumonia Severity Index

The pneumonia severity index (PSI) is counted by scoring certain patient characteristics that can be found in the PSI scoring system (table S2). The mortality risk for each number of points is shown in table S3.Patients characteristics Points assignedDemographic factorsAge

MalesFemales

Nursing home resident

Age in yearsAge in years – 10+ 10

ComorbiditiesNeoplastic disease1

Liver disease2

Congestive heart failure3

Cerebrovascular disease4

Renal disease5

+30+20+10+10+10

Physical examination findingsAltered mental status6

Respiratory rate ≥30/minute Systolic blood pressure <90 mm Hg Temperature <35 ºC or ≥40 ºC Pulse ≥125/minute

+20+20+20+15+10

Laboratory findingspH:7.35Urea >22.9 mmol/L Sodium <130 mEq/LGlucose >13.9 mmol/LHematocrit <30%pO2 <60 mm HgPleural effusion

+30+20+20+10+10+10+10

Table S2. Pneumonia Severity Index Scoring System.1 Neoplastic disease: any cancer except basal- or squamous cell cancer of the skin that was active at the time of presentation or diagnosed within one year of presentation. 2 Liver disease: a clinical or histological diagnosis of cirrhosis or another form of chronic liver disease, such as chronic active hepatitis. 3 Congestive heart failure: systolic or diastolic ventricular dysfunction documented by history, physical examination, and chest radiograph, echocardiogram, multiple gated acquisition scan, or left ventriculogram. 4 Cerebrovascular disease: a clinical diagnosis of stroke or transient ischemic attack or stroke documented by magnetic resonance imaging or computed tomography. 5 Renal disease: a history of chronic renal disease or abnormal blood urea nitrogen and creatinine concentrations documented in the medical record.6 Altered mental status: disorientation with respect to person, place, or time that is not known to be chronic, stupor, or coma.

Risk class (points)

30-day mortality risk:

I (0) 0.1%II (1-70) 3.6%III (71-90) 0.9%IV (91-130) 9.3%V (>130) 27.0%Table S3. Prediction model.Mortality risk for number of points assigned bythe pneumonia severity index scoring system.



Supplement 3. SIRS criteria

Systemic Inflammatory Response Syndrome (SIRS) criteria:

- Temperature <36 °C or >38 °C;- Heart rate >90/minute;- Respiratory rate >20 breaths/minute or PaCO2 <32 mm Hg;- White blood count >12,000 cells/μL, or <4,000 cells/μL, or > 10% rods.

SIRS: two or more of the criteria.Sepsis: two or more of the criteria + infection.



Supplement 4. Table S4Urine samplen = 319 (64%)

No urine samplen = 177 (36%)

p-value

Male sex 180 (56%) 111 (63%) 0.17Age (year) 68.0 [51.0-

80.0]65.0 [51.0-74.0]

0.050

Race 1

- Caucasian- Other

315 (99%)4 (1%)

176 (99%)1 (1%)

0.66

Nursing-home resident 16 (5%) 3 (2%) 0.07Comorbidities 2

- Chronic kidney disease- Diabetes mellitus- Liver disease- Neoplastic disease- Congestive heart failure- COPD

25 (8%)51 (16%)2 (1%)23 (7%)47 (15%)47 (15%)

6 (3%)22 (12%)0 22 (12%)19 (11%)49 (28%)

0.0500.280.540.0530.21<0.0001


- Class I – III - Class IV-V

175 (55%)144 (45%)

101 (57%)76 (43%) 0.64

RIFLE class- RIFLE class 0- RIFLE classes 1-3

268 (84%)50 (16%)

163 (92%)14 (8%) 0.013

Systemic blood pressure- Systolic (mm Hg) - Diastolic (mm Hg)

131.0 (22.2)73.5 (12.5)

135.2 (23.2)75.1 (14.0)

0.0470.20


- C-reactive protein (mg/L) - White blood count (x

109/L) - Creatinine (µmol/L) - Urea (mmol/L)

219.9 (143.2)14.7 (6.7)89.0 [71.0-117.3]7.3 [4.7-1.0]

209.7 (136.0)14.3 (6.4)90.0 [72.0-107.0]6.3 [4.9-9.5]

0.440.500.740.07

Current medication- NSAID - ACE inhibitor and/or ARB

36 (11%)67 (21%)

16 (9%)38 (22%)

0.430.90

Dexamethasone 3 116 (36%) 31 (18%) <0.0001Outcomes

- Length of stay - In-hospital mortality- One-year mortality

8.0 [6.0-13.0]19 (6%)51 (16%)

9.0 [6.0-14.0]5 (3%)19 (11%)

0.310.130.06

Table S4. Baseline characteristics of 496 patients with community-acquired pneumonia included in the study.Data are presented as mean (±), median [interquartile range] or number (%). Abbreviations: ACE inhibitor = angiotensin-converting enzyme, ARB = angiotensin receptor blocker, COPD = chronic obstructive pulmonary disease, NSAID = nonsteroidal anti-inflammatory drug.1 Race was self-reported. 2 Patients could have more than one comorbidity. 3 As part of a clinical trial.



Supplement 5. Figures S1A and S1B

Figure S1. Kaplan Meier analysis of one-year mortality in patients hospitalized with community-acquired pneumonia.A. The effect of proteinuria on one-year mortality (log-rank p:0.07).B. The effect of RIFLE classes 1-3 on one-year mortality (log-rank p<0.0001).


A

B


Supplement 6. Table S5

RIFLE classes 1-3

OR or HR 95% CI p-value

Length of stay

Unadjusted2 3.62 1.88-6.97 <0.0001

Adjusted2 4.15 2.15-8.02 <0.0001

In-hospital mortality

Unadjusted1 2.84 0.30-

27.17

0.37

Adjusted1 3.65 0.33-

40.90

0.30

One-year mortality

Unadjusted2 2.32 0.67-8.02 0.18

Adjusted2 2.66 0.77-9.22 0.12

Table S5. Odds ratios and hazard ratios for all outcomes, classified according to RIFLE classes 1-3, for patients without a urine sample available (n=177).Unadjusted and adjusted odds ratios1 and hazard ratios2 for RIFLE classes 1-3. Adjusted ratios are calculated for proteinuria and RIFLE classes 1-3 together with PSI severity (I-III versus IV-V) and dexamethasone in one model. Abbreviations: CI = confidence interval, HR = hazard ratio, OR = odds ratio.



Supplement 7. Table S6

Proteinuria RIFLE classes 1-3 Proteinuria +

RIFLE classes 1-3

OR or HR (95%

CI)

p-

value

OR or HR (95%

CI)

p-

value

OR or HR (95%

CI)

p-

value

Length of stay

Unadjusted2 1.63 (1.28-2.06) <0.00

01

1.55 (1.12-2.15) 0.009 1.69 (0.41-0.85) 0.004

Adjusted2 1.38 (1.08-1.75) 0.01 1.21 (0.86-1.71) 0.27 1.37 (0.51-1.06) 0.09

In-hospital

mortality

Unadjusted1 5.59 (1.27-

24.63)

0.02 3.81 (1.40-

10.35)

0.009 3.79 (1.34-

10.72)

0.01

Adjusted1 3.27 (0.69-

15.45)

0.14 1.81 (0.62-5.27) 0.28 1.90 (0.63-5.73) 0.25

One-year

mortality

Unadjusted2 1.74 (0.94-3.22) 0.08 3.06 (1.69-5.55) <0.00

01

3.21 (1.73-5.95) <0.00

01

Adjusted2 1.09 (0.56-2.10) 0.80 1.81 (0.97-3.37) 0.06 1.80 (0.94-3.42) 0.08

Table S6. Odds ratios and hazard ratios for all outcomes for proteinuria, RIFLE classes 1-3, and proteinuria and RIFLE classes 1-3 combined.Unadjusted and adjusted odds ratios1 and hazard ratios2 for the presence of proteinuria, for RIFLE classes 1-3, and for proteinuria and RIFLE classes 1-3 combined. Adjusted ratios are calculated for proteinuria and RIFLE classes 1-3 together with PSI severity (I-III versus IV-V) and dexamethasone in one model, or proteinuria and RIFLE classes 1-3 combined together with PSI severity and dexamethasone in one model. Abbreviations: CI = confidence interval, HR = hazard ratio, OR = odds ratio.



Supplement 8. Figures S2, S3 and S4

Figure S2. Quantity of proteinuria for each PSI class. The total-protein/creatinine ratio of all patients classified according to their pneumonia severity index (PSI) class, selected only patients with proteinuria.

Figure S3. Quantity of proteinuria for each RIFLE class.The total-protein/creatinine ratio of all patients classified according to the RIFLE criteria, with no kidney injury = 0, Risk =1, and Injury and Failure = 2+3, selected only patients with proteinuria.

Figure S4. Quantity of proteinuria for each number of SIRS criteria. The total-protein/creatinine ratio of all patients classified according to the number of present systemic inflammatory response syndrome (SIRS) criteria, selected only patients with proteinuria.



Supplement 9. List of abbreviations

A/C ratio Albumin/creatinine ratioACE inhibitor Angiotensin-converting enzyme inhibitor ADQI group Acute Dialysis Quality Initiative groupAKI Acute kidney injuryAKIN Acute kidney injury networkARB Angiotensin receptor blocker CAP Community-acquired pneumoniaCI Confidence interval CKD Chronic kidney disease COPD Chronic obstructive pulmonary disease Creatinine-75 Baseline serum creatinine value back-calculated using an

eGFR of 75 mL/min/1.73 m2

Creatinine-actual Actual baseline serum creatinine valueCreatinine-age Baseline serum creatinine value back-calculated using an

age- and gender-adjusted eGFRCRP C-reactive proteineGFR Estimated glomerular filtration rateGFR Glomerular filtration rateHR Hazard ratio `IL-6 Interleukin-6IQR Interquartile range LOS Length of stayMDRD formula Modification of Diet in Renal Disease formulaMort Mortality N Number of patients NFK KDOQI National Kidney Foundation Disease Outcomes Quality InitiativeNS Not significantNSAID Nonsteroidal anti-inflammatory drugOR Odds ratioP/C ratio Total-protein/creatinine ratioPSI Pneumonia severity indexRIFLE criteria Risk, injury, failure, loss and end-stage renal disease criteriaSIRS Systemic inflammatory response syndromeTNF Tumor necrosis factor



Supplement 10. Samenvatting

Acuut nierfalen (AKI, acute kidney injury), geclassificeerd volgens de Risk, Injury, Failure, Loss and End-Stage kidney disease (RIFLE) criteria, komt regelmatig voor bij patiënten met buiten het ziekenhuis opgelopen pneumonie (CAP, community-acquired pneumonia). Uit verschillende onderzoeken is gebleken dat de RIFLE criteria de incidentie van AKI onderschatten. Het doel van deze studie was het onderzoeken of bij patiënten met een CAP, proteïnurie een betere marker voor AKI is in vergelijking met de RIFLE criteria. De voorspellende waarde van proteïnurie voor het ziekenhuisbeloop werd vergeleken met de voorspellende waarde van de RIFLE criteria voor het ziekenhuisbeloop. Proteïnurie (gedefinieerd als totaal-eiwit/kreatinine ratio >23 mg/mmol) werd gemeten in urinemonsters die verkregen waren op de dag van opname. De primaire uitkomst was opnameduur. Secundaire uitkomsten waren ziekenhuismortaliteit en één-jaars mortaliteit. Bij 319/496 patiënten (64%) was er een urinemonster verkregen op de dag van opname. Van de 319 patiënten hadden 198 patiënten (62%) proteïnurie. In univariate analyse hadden patiënten met proteïnurie een significant langere opnameduur dan patiënten zonder proteïnurie: 9.0 dagen [IQR 7.0-14.0] versus 7.0 dagen [IQR 5.0-10.0]. Ook de ziekenhuismortaliteit was verhoogd bij patiënten met proteïnurie. De RIFLE criteria waren een voorspeller voor opnameduur (9.0 dagen [IQR 7.0-14.0] voor patiënten in RIFLE klassen 1-3 versus 8.0 dagen [IQR 6.0-12.0] voor patiënten in RIFLE klasse 0), ziekenhuismortaliteit, en één-jaars mortaliteit. Doch, in multivariate analyse was alleen proteïnurie een onafhankelijke voorspeller van opnameduur. Proteïnurie komt vaak voor tijdens een CAP. Zowel proteïnurie als de RIFLE criteria zijn geassocieerd met een ongunstig beloop bij deze patiëntenpopulatie, maar alleen proteïnurie was een onafhankelijke voorspeller voor opnameduur. Proteïnurie kan een voorspeller zijn voor het ziekenhuisbeloop en kan mogelijk gebruikt worden om de ernst van de CAP te beoordelen.


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