Confidential: For Review Only - BMJ · 11. Daniel I. McIsaac, MD, MPH Assistant Professor...

Confidential: For Review OnlyPre- and Intra-Arrest Prognostic Factors Associated with

Survival Following In-Hospital Cardiac Arrest – A Systematic Review and Meta-Analysis

Journal: BMJ

Manuscript ID BMJ-2019-051261

Article Type: Research

BMJ Journal: BMJ

Date Submitted by the Author: 23-Jun-2019

Complete List of Authors: Fernando, Shannon; University of Ottawa, Department of Emergency MedicineTran, Alexandre; University of OttawaCheng, Wei; Ottawa Hospital Research Institute, Clinical Epidemiology ProgramRochwerg, Bram; McMaster University, Taljaard, Monica; Ottawa Hospital Research Institute, Clinical EpidemiologyVaillancourt, Christian; University of Ottawa, Department of Emergency MedicineRowan, Kathryn; Intensive Care National Audit and Research Centre ICNARCHarrison, David; ICNARC, Clinical Trials UnitNolan, Jerry; University of Warwick, Clinical Trials Unit; Royal United Hospital Bath NHS Trust, Kyeremanteng, Kwadwo; University of Ottawa, Department of MedicineMcIsaac, Daniel; University of Ottawa, Department of Anesthesiology and Pain MedicineGuyatt, Gordon; McMaster University, Perry, Jeffrey; University of Ottawa, Department of Emergency Medicine

Keywords: Cardiac Arrest, Critical Care Medicine, Internal Medicine, Hospital Medicine

https://mc.manuscriptcentral.com/bmj

BMJ

Confidential: For Review Only

Prognosis for Survival After In-Hospital Cardiac Arrest

1

TITLE: Pre- and Intra-Arrest Prognostic Factors Associated with Survival Following In-Hospital Cardiac Arrest – A Systematic Review and Meta-Analysis

RUNNING HEAD: Prognosis for Survival After In-Hospital Cardiac Arrest

AUTHORS: Shannon M. Fernando, MD, MSc1,2; Alexandre Tran, MD, MSc3,4*; Wei Cheng, PhD5*; Bram Rochwerg, MD, MSc6,7; Monica Taljaard, PhD3,5; Christian Vaillancourt, MD, MSc2,3,5; Kathryn M. Rowan, PhD8; David A. Harrison, PhD8; Jerry P. Nolan, MBChB9,10, Kwadwo Kyeremanteng, MD, MHA1,5; Daniel I. McIsaac, MD, MPH3,5,11; Gordon H. Guyatt, MD, MSc7,12; Jeffrey J. Perry, MD, MSc2,3,5

*Denotes equal contribution

AFFILIATIONS: From the 1Division of Critical Care, Department of Medicine, University of Ottawa, Ottawa, ON; 2Department of Emergency Medicine, University of Ottawa, Ottawa, ON; 3School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON; 4Department of Surgery, University of Ottawa, Ottawa, ON; 5Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, ON; 6Department of Medicine, Division of Critical Care, McMaster University, Hamilton, ON; 7Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON; 8Intensive Care National Audit and Research Centre, London, UK; 9Department of Anaesthesia and Intensive Care Medicine, Royal United Hospital, Bath, UK; 10Warwick Clinical Trials Unit, University of Warwick, Coventry, UK; 11Department of Anesthesiology and Pain Medicine, University of Ottawa, Ottawa, ON; 12Department of Medicine, McMaster University, Hamilton, ON.

CORRESPONDENCE TO: Dr. Shannon M. Fernando, Department of Critical Care Medicine, The Ottawa Hospital, Civic Campus, 1053 Carling Ave., Ottawa, ON. K1Y 4E9. Email: [email protected]; ORCID: 0000-0003-4549-4289; Twitter: @shanfernands

ABSTRACT WORD COUNT: 343TEXT WORD COUNT: 3,187

KEYWORDS: In-Hospital Cardiac Arrest; Cardiac Arrest; Critical Care; Internal Medicine; Hospital Medicine

COMPETING INTERESTS: All authors have completed the Unified Competing Interest form (available on request from the corresponding author) and declare: 1) No support from any organisation for the submitted work; 2) No financial relationships with any organisations that might have an interest in the submitted work in the previous three years; and 3) No other relationships or activities that could appear to have influenced the submitted work.

CONTRIBUTORS: SMF, AT, and JJP conceived the study idea. SMF, AT, WC, BR, and JJP coordinated the systematic review. SMF and AT designed the search strategy. SMF and AT screened abstracts and full texts. SMF, AT and WC acquired the data and judged risk-of-bias in the studies. KMR, DAH, and JPN provided original data. WC performed the data analyses. BR and GHG created the GRADE evidence profiles. SMF, AT, WC, BR, MT, CV, KMR, DAH, JPN, KK, DIM, GHG, and JJP interpreted the data analysis and critically revised the manuscript.

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All authors have had the opportunity to review the final manuscript, and provided their permission to publish the manuscript. All authors agree to take responsibility for the work. SMF is guarantor. The corresponding author attests that all listed authors meet authorship criteria, and that no others meeting the criteria have been omitted.

FUNDING: None received.

ETHICS APPROVAL: Not applicable.

DATA SHARING: The study protocol was registered with PROSPERO (CRD42018104795). For individual study data, please see electronic supplement.

LICENSE FOR PUBLICATION: The Corresponding Author (Dr. Shannon M. Fernando) has the right to grant on behalf of all authors and does grant on behalf of all authors, a worldwide licence to the Publishers and its licensees in perpetuity, in all forms, formats and media (whether known now or created in the future), to i) publish, reproduce, distribute, display and store the Contribution, ii) translate the Contribution into other languages, create adaptations, reprints, include within collections and create summaries, extracts and/or, abstracts of the Contribution, iii) create any other derivative work(s) based on the Contribution, iv) to exploit all subsidiary rights in the Contribution, v) the inclusion of electronic links from the Contribution to third party material where-ever it may be located; and, vi) licence any third party to do any or all of the above.

TRANSPARENCY: The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

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AUTHOR CONTACT INFORMATION:

1. Shannon M. Fernando, MD, MScResident PhysicianDivision of Critical Care, Department of Medicine, University of OttawaDepartment of Emergency Medicine, University of Ottawa1053 Carling Ave., E-Main, Room 206, Box 227, Ottawa, ON, K1Y 4E9Email: [email protected]

2. Alexandre Tran, MD, MScResident PhysicianDepartment of Surgery, University of Ottawa501 Smyth Road, Ottawa, ON, K1H 8L6Email: [email protected]

3. Wei Cheng, PhDSenior MethodologistClinical Epidemiology Program, Ottawa Hospital Research Institute501 Smyth Road, Box 201B, Ottawa, ON, K1H 8L6Email: [email protected]

4. Bram Rochwerg, MD, MScAssistant ProfessorDivision of Critical Care, Department of Medicine, McMaster UniversityDepartment of Health Research Methods, Evidence and Impact, McMaster University1200 Main Street West, Hamilton, ON, L8N 3Z5Email: [email protected]

5. Monica Taljaard, PhDAssociate ProfessorSchool of Epidemiology and Public Health, University of OttawaSenior ScientistClinical Epidemiology Program, Ottawa Hospital Research Institute501 Smyth Road, Box 511, Ottawa, ON, K1H 8L6Email: [email protected]

6. Christian Vaillancourt, MD, MScProfessorDepartment of Emergency Medicine, University of OttawaSenior ScientistClinical Epidemiology Program, Ottawa Hospital Research InstituteF6, The Ottawa Hospital, Civic Campus1053 Carling Ave., Ottawa, ON, K1Y 4E9Email: [email protected]

7. Kathryn M. Rowan, PhD

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ProfessorIntensive Care National Audit and Research Centre24 High Holborn, London, UK, WC1V 6AZEmail: [email protected]

8. David A. Harrison, PhDHead StatisticianIntensive Care National Audit and Research Centre24 High Holborn, London, UK, WC1V 6AZEmail: [email protected]

9. Jerry P. Nolan, MBChBProfessorClinical Trials Unit, University of WarwickCoventry, UK, CV4 7ALEmail: [email protected]

10. Kwadwo Kyeremanteng, MD, MHAAssistant ProfessorDivision of Critical Care, Department of Medicine, University of OttawaScientistClinical Epidemiology Program, Ottawa Hospital Research Institute501 Smyth Road, Ottawa, ON, K1H 8L6Email: [email protected]

11. Daniel I. McIsaac, MD, MPHAssistant ProfessorDepartment of Anesthesiology and Pain Medicine, University of OttawaClinical Epidemiology Program, Ottawa Hospital Research Institute1053 Carling Ave., Ottawa, ON, K1Y 4E9Email: [email protected]

12. Gordon H. Guyatt, MD, MScDistinguished ProfessorDepartment of Medicine, McMaster UniversityDepartment of Health Research Methods, Evidence, and Impact, McMaster University1200 Main Street West, Hamilton, ON, L8N 3Z5Email: [email protected]

13. Jeffrey J. Perry, MD, MScProfessorDepartment of Emergency Medicine, University of OttawaSenior ScientistClinical Epidemiology Program, Ottawa Hospital Research InstituteF6, The Ottawa Hospital, Civic Campus

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1053 Carling Ave., Ottawa, ON, K1Y 4E9Email: [email protected]

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KEY POINTS:

WHAT IS ALREADY KNOWN ON THIS TOPIC: In-hospital cardiac arrest (IHCA) is

associated with low survival. Much of our clinical understanding of IHCA is extrapolated from

the extensive literature on out-of-hospital cardiac arrest, though IHCA represents a distinct

clinical entity with unique epidemiology. Understanding of pre- and intra-arrest prognostic

factors associated with survival following IHCA is an important area of research, and may

inform clinical decision-making with patients. We conducted a systematic review and meta-

analysis to evaluate this question.

WHAT THIS STUDY ADDS: Among pre-arrest factors, increasing age, male sex, active

malignancy, and chronic kidney disease were associated with reduced survival following IHCA.

Among intra-arrest factors, witnessed arrest, monitored patient, arrest during daytime hours, and

shockable rhythm were associated with increased survival following IHCA, while increased

duration of resuscitation and tracheal intubation were associated with reduced survival. These

findings identify important prognostic factors associated with outcome following IHCA, and

may be utilized in counseling and shared decision-making related to advanced directives with

hospitalized patients.

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ABSTRACT:

OBJECTIVES: Survival rates following in-hospital cardiac arrest (IHCA) are low, and

associations between important pre- and intra-arrest factors and likelihood of survival following

IHCA remain uncertain. We summarized the available evidence addressing associations between

pre- and intra-arrest prognostic factors and survival (in-hospital, 28-day, or 30-day) from IHCA.

DESIGN: Systematic review and meta-analysis.

DATA SOURCES: Six databases, including MEDLINE, Embase, and PubMed, from inception

through February 2019. We additionally included primary, unpublished data from the National

Cardiac Arrest Audit (NCAA) database.

STUDY SELECTION CRITERIA: English-language studies investigating pre- and intra-arrest

prognostic factors and survival following IHCA.

DATA EXTRACTION: We followed the PROGnosis RESearch Strategy (PROGRESS) Group

recommendations and used the Critical Appraisal and Data Extraction for Systematic Reviews of

Prediction Modeling Studies (CHARMS) checklist. Two reviewers independently extracted data

and assessed risk of bias using the Quality in Prognosis Studies (QUIPS) tool. Our primary

analysis pooled associations only if they were adjusted for relevant confounders. We used the

GRADE approach to rate our certainty in the evidence.

RESULTS: We included 23 cohort studies in our primary analyses. Of pre-arrest factors, male

sex (odds ratio [OR] 0.84, 95% confidence interval [CI]: 0.73-0.95, moderate certainty), age ≥ 60

years (OR 0.50, 95% CI: 0.40-0.62, low certainty), active malignancy (OR 0.57, 95% CI: 0.45-

0.71, high certainty), and history of chronic kidney disease (OR 0.56, 95% CI: 0.40-0.78, high

certainty) were associated with reduced odds of survival following IHCA. Of intra-arrest factors,

witnessed arrest (OR 2.71; 95% CI: 2.17-3.38, high certainty), monitored arrest (OR 2.23; 95%

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CI: 1.41-3.52, high certainty), arrest during daytime hours (OR 1.41; 95% CI: 1.20-1.66, high

certainty), and initial shockable rhythm (OR 5.28; 95% CI: 3.78-7.39, high certainty) were

associated with increased odds of survival. Intubation during arrest (OR 0.54; 95% CI: 0.42-0.70,

moderate certainty) and duration of resuscitation ≥ 15 minutes (OR 0.12; 95% CI: 0.07-0.19,

high certainty) were associated with reduced odds of survival.

CONCLUSIONS: These findings provide moderate to high certainty evidence addressing the

association between important pre-arrest and intra-arrest prognostic factors and likelihood of

survival following IHCA.

FUNDING: None.

REGISTRATION: PROSPERO CRD42018104795

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INTRODUCTION:

Cardiac arrest refers to cessation of mechanical heart function and effective blood

circulation, and is typically considered as either Out-of-hospital cardiac arrest (OHCA), or in-

hospital cardiac arrest (IHCA).1 2 Although evidence from OHCA is often extrapolated to IHCA,

the epidemiology differs, and the determinants of success are likely to differ accordingly.1 3 In

comparison with OHCA, data on incidence and survival following IHCA are limited. Most

studies indicate an incidence of 1-6 events per 1000 hospital admissions.4 5 Survival to discharge

after IHCA ranges between 12-25%, with some increase recently.1 6 7 One year outcomes are

similar, with only modest increases over the past decade.8

Prognostic factors associated with survival following IHCA are an important focus of

ongoing research.2 Hospitalized patients are increasingly complex, presenting a unique challenge

in the management of IHCA. Clinicians managing IHCA are tasked with rapidly processing the

many factors related to pre-admission status (including age, sex, comorbidities), and factors

related to the arrest itself (including whether the arrest was witnessed or monitored, and initial

rhythm) in order to determine the utility of ongoing cardiopulmonary resuscitation (CPR).

Additionally, clinicians need to discuss expected prognosis following IHCA with patients at the

time of hospital admission in order to inform care plans, and whether to include CPR in the event

of cardiac arrest.3 9 10

A greater understanding of factors associated with the likelihood of success in IHCA

resuscitation may facilitate development of a predictive model that aids in shared decision-

making with patients and families, as well as clinical decision-making at the time of IHCA, and

following return of spontaneous circulation (ROSC). Therefore, we conducted a systematic

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review and meta-analysis to summarize the association between pre- and intra-arrest factors and

survival following IHCA.

METHODS:

We conducted this systematic review and meta-analysis according to recommendations

by the PROGnosis RESearch Strategy (PROGRESS) Group,11-14 and recent guidelines for

systematic reviews and meta-analyses of prognostic factors.15 The Critical Appraisal and Data

Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS) checklist16 was

used to define and frame the study. We registered the review protocol with the PROSPERO

registry (CRD42018104795).

Data Sources and Searches

We searched MEDLINE, PubMed, EMBASE, Scopus, Web of Science, and the

Cochrane Database of Systematic Reviews from inception until February 4, 2019. An

experienced health sciences librarian assisted in developing the search strategy (Supplemental

Figure 1), that was conducted using the terms “cardiac arrest”, combined with terms related to

prognosis research, as recommended.15 We used the Science Citation Index to retrieve reports

citing the relevant articles identified from our search, and then entered them into PubMed, and

conducted further surveillance searches using the “Related Articles” feature.17

Study Selection

We included all English-language full-text articles describing retrospective and

prospective observational studies, randomized controlled trials, and quasi-randomized controlled

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trials. We included studies meeting the following criteria: 1) Enrolled a majority (i.e. ≥ 80%)

adult patients (≥ 16 years) with IHCA; 2) Conducted in the emergency department, hospital

wards, or intensive care unit (ICU); and 3) Evaluated mortality as an outcome of interest (either

in-hospital, 28-day, or 30-day). We excluded studies that evaluated mortality over longer or

unspecified time periods; case reports and case series; studies that included only patients who

received a particular post-arrest therapy (such as therapeutic hypothermia or extracorporeal life

support); studies that included patients with OHCA; and studies that failed to provide model-

adjusted or unadjusted odds ratios (OR) with confidence intervals (CI), or counts for calculating

unadjusted ORs. Where these values could not be obtained from the reported data, we contacted

the corresponding author to obtain the information.

We screened studies using Covidence software (Melbourne, Australia). We imported

titles into Covidence directly from the search databases and removed duplicates. Two reviewers

(SMF and AT) independently screened the titles and abstracts of all identified citations.

Disagreement was resolved by discussion; no third-party adjudication proved necessary. The

same two reviewers subsequently independently assessed full texts of the selected articles

following screening and again resolved by discussion.

Data Extraction and Quality Assessment

Two investigators (SMF and AT) abstracted the following variables: author information,

year of publication, study design, study dates, definition of start points, eligibility criteria,

number of patients included, and incidence of mortality. We used a pre-designed data extraction

sheet (Supplemental Table 2) to minimize transcription errors. Subsequently, for each

prognostic factor, two investigators (SMF and AT) independently collected unadjusted or

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adjusted ORs for survival in each study, where available. Extraction was performed using a

modified version of the CHARMS checklist for prognostic factors (CHARMS-PF).15 16 A third

investigator (WC) verified all extracted data and calculated unadjusted ORs from counts.

Two reviewers (SMF and AT) independently assessed the risk-of-bias for included

studies, using the Quality in Prognosis Studies (QUIPS) tool.18 Disagreements were resolved

through discussion. As our protocol indicates, we had initially intended to utilize a different scale

for quality review, but the QUIPS is recommended for risk-of-bias assessment in reviews of

prognostic factors.15 The QUIPS includes six potential domains for bias and applicability of the

research question: study participation, study attrition, prognostic factor measurement, outcome

measurement, adjustment for other prognostic factors, and statistical analysis and reporting.

Data Synthesis

Many of the included studies of IHCA reported from large databases, including the

American Heart Association National Registry of Cardiopulmonary Resuscitation (NRCPR)

(later renamed the Get With The Guidelines [GWTG] Registry), the United Kingdom’s National

Cardiac Arrest Audit (NCAA), and the Swedish Cardiac Arrest Registry (SCAR). For registry or

large databases, we included the report with the largest number of patients for each prognostic

factor. We evaluated the associated websites of these databases and searched through all of their

published studies. We obtained primary, unpublished unadjusted and adjusted ORs from the

NCAA database (April 2011-March 2018) directly from the principal investigators (KMR, DAH,

JPN), and the data they provided exceeds the number of patients in any of the published NCAA

reports.19-21

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We present meta-analyses of adjusted ORs as the primary analysis. At minimum, all

included studies in this primary analysis had to consider the effect of age, initial rhythm, or

etiology of arrest in their analyses, as these variables are known to be importantly associated

with outcome following IHCA.1 2 Meta-analyses of unadjusted values were included as

secondary analyses. OR estimates and the corresponding CIs were meta-analyzed by applying

the Dersimonian-Laird random-effects model22 using Review Manager (Version 5.3,

Copenhagen, Denmark). Heterogeneity was assessed using the I2 statistic, the Chi-squared test

for homogeneity, and visual inspection of the forest plots.

We assessed overall certainty in pooled estimates using the GRADE approach (BR,

GHG).23 The overall certainty in estimates were categorized into one of four levels: high,

moderate, low, or very low. In keeping with GRADE guidance for prognostic studies, cohort

data start as high certainty evidence.23 A GRADE evidence profile was created using the

guideline development tool (gradepro.org).

Patient and Public Involvement

No patients were involved in the definition of the research question, the outcome

measures, interpretation of results, or manuscript creation. Where possible, the results of this

meta-analysis will be disseminated to individual patients and families by the study investigators.

RESULTS:

Search Results

Our search identified 10,356 citations (Figure 1) and following de-duplication, we

screened 7,172 studies, including 83 for full-text review. We included 23 cohorts24-45 in our

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primary meta-analysis of adjusted results, including unpublished results from 90,276 patients in

the NCAA database. Three studies utilized the NRCPR/GWTG database,27 40 42 and two used the

SCAR database.24 41 The secondary analysis included an additional 30 studies.46-75

Study Characteristics

Table 1 presents characteristics of studies included in the primary analysis. Supplemental

Table 2 displays CHARMS-PF detailed characteristics of each study, and Supplemental Table 3

shows consistency between the included studies and the CHARMS-PF checklist requirements.

Of studies included in the primary analysis, 52.2% were from North America, and 26.1% were

from Europe. All included studies used observational designs, and 56.5% retrospective cohort

designs. The majority (56.5%) were multicenter studies. Supplemental Table 6 presents

prognostic factors included in the adjustment analyses of each study.

Risk of Bias and Quality Assessment

Quality assessments, using QUIPS methodology, are displayed in Supplementary Table

7. The majority of studies included were deemed low risk-of-bias for all QUIPS domains. No

studies were rated as high risk-of-bias in any QUIPS domain. Six cohorts were judged to have

moderate risk-of-bias in either study participation, study attrition, or statistical reporting.19 25 28 31

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Results of Synthesis

Table 2 presents pooled adjusted ORs and 95% CIs for the primary analysis, along with

GRADE level of certainty and Supplemental Tables 8-9 shows GRADE evidence profiles.

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Primary Analyses: Pre-Arrest Factors

We evaluated the association between multiple patient demographics and survival from

IHCA. Figure 2 presents forest plots. Male sex was associated with lower odds of survival from

IHCA (OR 0.84. 95% CI: 0.73-0.95, moderate certainty). We evaluated the impact of age at two

different thresholds. Age ≥ 60 years had a pooled OR of 0.50 (95% CI: 0.40-0.62, low certainty)

for survival from IHCA, and age ≥ 70 years had a pooled OR of 0.42 (95% CI: 0.18-0.99, low

certainty).

A history of malignancy was associated with a pooled OR of 0.57 (95% CI: 0.45-0.71,

high certainty) for survival from IHCA; and chronic kidney disease (CKD) had a pooled OR of

0.56 (95% CI: 0.40-0.78, high certainty). Single studies reported associations with congestive

heart failure (CHF) (OR 0.62, 95% CI: 0.56-0.68, moderate certainty),36 chronic obstructive

pulmonary disease (COPD) (OR 0.65, 95% CI: 0.58-0.72, moderate certainty),36 and diabetes

mellitus (OR 0.53, 95% CI: 0.34-0.83, moderate certainty).44 A diagnosis of acute coronary

syndrome (ACS) had a pooled OR of 0.70 (95% CI: 0.28-1.78, low certainty) for survival from

IHCA.

Primary Analyses: Intra-Arrest Factors

We investigated the association between intra-arrest factors and survival from IHCA.

Witnessed IHCA had a pooled OR of 2.71 (95% CI: 2.17-3.38, high certainty) for survival.

Arrests that took place in monitored settings (i.e. patients on telemetry) had a pooled OR 2.23

(95% CI: 1.41-3.52, high certainty) for survival. IHCA that took place during daytime hours

(defined as time periods during which hospitals were fully staffed, and varied between studies)

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had an associated pooled OR of 1.41 (95% CI: 1.20-1.66, high certainty) for survival. Initial

rhythm was categorized as either shockable (ventricular fibrillation or pulseless ventricular

tachycardia), or non-shockable (pulseless electrical activity or asystole). An initial shockable

rhythm during IHCA was associated with a pooled OR of 5.28 (95% CI: 3.78-7.39, high

certainty) for survival. We evaluated the prognostic impact of each rhythm (Supplemental

Figures 14-17), which demonstrated increased associated odds of survival among patients with

any initial shockable rhythm. Tracheal intubation during IHCA was associated with a pooled OR

of 0.54 (95% CI: 0.42-0.70, moderate certainty) for survival. High certainty evidence showed an

OR of duration of resuscitation (i.e. time from arrest to ROSC) ≥ 15 minutes with survival of

0.12 (95% CI: 0.07-0.19).

Secondary Analyses

Secondary analyses presenting pooled unadjusted estimates are presented in the

supplemental material. CHARMS-PF detailed characteristics of studies presenting only

unadjusted results are shown in Supplemental Table 10, and pooled unadjusted results are

displayed in Supplemental Table 11. Forest plots comparing adjusted and unadjusted meta-

analyses of pre- and intra-arrest prognostic factors are shown in Supplemental Figures 2-20.

Importantly, the direction of effect for all unadjusted analyses is concordant with the primary

adjusted analyses.

DISCUSSION:

We conducted a systematic review and meta-analysis in order to evaluate the association

of pre- and intra-arrest factors with survival following IHCA. Pre-arrest factors associated with

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reduced survival include male sex, increasing age, active malignancy, and chronic kidney

disease. Among intra-arrest factors, we found that witnessed arrest, monitored setting, arrest

during working hours, and shockable rhythm were associated with increased survival, while

tracheal intubation during arrest, and prolonged resuscitation were associated with reduced

survival. These findings provide evidence related to the association between important

prognostic factors and odds of survival following IHCA. Therefore, they may have a role in

informed counselling and shared decision-making between clinicians and patients, particularly as

it relates to advanced directives following IHCA.

While pre-arrest factors are typically patient-specific and non-modifiable, they

nonetheless indicate important associations that may aid in prognostication and risk-

stratification. We found moderate certainty evidence that male sex was associated with reduced

odds of survival from IHCA. The existing OHCA literature has investigated the relationship

between patient sex and survival, and also found improved survival among females,76 though the

explanation for this is unclear. Females may benefit from specific hormones (namely estrogen)

and their effect on their cardiovascular risk profile.77 78 Coronary occlusion in females is

associated with stronger vagal activation, and therefore reduced potential for dysrhythmic events,

and decreased oxygen consumption.79 Our study suggests that this sex difference evidence in

OHCA extends to IHCA, though the underlying mechanisms remain obscure.

We found that increasing age and prevalence of certain comorbidities (malignancy and

CKD) were associated with reduced odds of survival from IHCA. Hirlekar et al. previously

demonstrated the relationship between increasing age and mortality from IHCA in the SCAR.80

In addition to the higher prevalence of comorbidities in this population, elderly patients undergo

less aggressive intervention, and survival from IHCA appears to decrease in a dose-response

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fashion.81 We also found that patients with active cancer had lower associated survival from

IHCA. The GWTG registry found that approximately 14% of patients in their cohort had

advanced cancer, and that survival was markedly lower in this population, even when accounting

for resuscitation performance and patient-directed limits in care.82 Both increasing age and

comorbidity burden are tied to the construct of frailty, which describes a state of physiologic

decline and vulnerability.83 Future research should aim to investigate the association between

frailty and outcomes following IHCA, in order to more accurately prognosticate among

hospitalized patients.84

We investigated intra-arrest factors to further understand variables that influence

prognosis following IHCA. We found high certainty evidence that patients who had IHCA in a

monitored setting (i.e. with telemetry) had increased odds of survival. This is not only due to

immediate recognition, but also potentially because patients on continuous telemetry are more

likely to have advanced hemodynamic monitoring devices in place.3 Witnessed arrest was also

associated with improved survival following IHCA, as compared to unwitnessed arrest, also

based on high certainty evidence. This finding has been consistently demonstrated in the OHCA

literature,85 and likely reflects reduced latency to CPR. Interestingly, we also found that IHCA

during hospital working hours was associated with improved survival. Hospital staffing

(physicians, nursing, and allied-health workers) is reduced during nights and weekends, and such

trends have been associated with increased mortality.86 87

Other important intra-arrest variables were found to be associated with survival.

Unsurprisingly, we found high certainty evidence that initial rhythm was associated with

outcome following IHCA. Shockable rhythms (ventricular fibrillation/ventricular tachycardia)

were associated with higher odds of survival, as they are more likely to accompany a primary

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cardiac cause, and because of the effectiveness of early defibrillation. In the OHCA literature,

survival from a shockable rhythm greatly exceeds survival following PEA or asystole.73 88 Our

results demonstrate that this is also the case in IHCA. We found that prolonged duration of

resuscitation (≥ 15 minutes) was associated with reduced survival from IHCA. As the duration of

resuscitation increases, the likelihood of response to cardiac arrest interventions decreases, and

the prolonged ischemic time will likely result in irreversible organ dysfunction, even if ROSC is

eventually achieved.2

Finally, although based on moderate certainty evidence, we found that tracheal intubation

during IHCA was associated with lower odds of survival. This may be due to “resuscitation time

bias”, as prolonged resuscitation may be associated with both an increased number of

interventions, and worse outcome.89 However, this same finding was seen in a large cohort study

that controlled for duration of resuscitation.46 Two recent randomized trials in OHCA found that

insertion of supraglottic airway devices resulted in at least comparable, if not superior, survival

and neurological outcome as endotracheal intubation.90 91 Future randomized trials on tracheal

intubation during IHCA may provide more data on the optimal airway management strategy

during IHCA.

This review was performed using a comprehensive search and included studies with

overall low risk-of-bias, followed recent recommendations for meta-analysis of prognostic

studies,15 evaluated a number of pre- and intra-arrest prognostic factors for IHCA, and used

GRADE methodology to contextualize our findings based on our overall certainty in estimates.

The majority of estimates were based on moderate or high certainty evidence. Most notably, we

were able to include previously unpublished results from the NCAA database, and were able to

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meta-analyze this data with published work from the NRCPC/GWTG, SCAR, and other

databases to provide the best estimates of prognostic factor association.

This review has some limitations. Most notably, our meta-analysis included only

observational studies, and therefore only provides associations between individual prognostic

factors and survival from IHCA. Given the limitations of the literature, we were unable to

analyze how the combination of these factors may be used to influence clinical decision-making.

Therefore, clinicians should exercise great caution in combining these findings in order to make

clinical decisions related to initiation or termination of IHCA. These results may ultimately be

used to guide future large observational studies to derive a clinical prediction instrument for

practical application. Secondly, we evaluated short-term survival as our primary outcome, as this

was the outcome most commonly reported in the literature.3 However, association of these

prognostic factors with neurological outcome at discharge or long-term survival is unknown and

potentially more important to patients and caregivers. While neurological outcome was evaluated

in some included studies, different scales were used, thus not allowing meta-analysis. Third,

many of the factors we evaluated (namely age, sex, and comorbidities) are non-modifiable.

Despite this, understanding of their impact is still valuable, and the non-modifiable nature of

these prognostic factors is important to emphasize to patients when discussing advanced

directives related to CPR following IHCA. Finally, heterogeneity (by I2) was markedly high in

meta-analyses of several prognostic factors. While high heterogeneity suggests that we cannot be

certain of the magnitude of effect size, the direction of effect size was very clear for each factor,

and visual inspection of forest plots did not reveal important inconsistency amongst included

studies. The factors accounting for heterogeneity are not immediately clear. There is clinical

heterogeneity between studies with regard to some of the prognostic factors (for example,

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“monitoring” was referred to as continuous telemetry in some studies, while in others it included

telemetry in addition to pulse oximetry). However, it is more likely that unknown confounders

may have influenced the point estimates for individual studies. Reliance upon the I2 statistic

alone for quantifying the amplitude of heterogeneity in meta-analyses is problematic,92 and in

fact, in our analyses the I2 increased with the addition of the highly precise NCAA data.

CONCLUSION:

We evaluated pre- and intra-arrest factors associated with survival following IHCA.

Among pre-arrest factors, male sex, increasing age, active malignancy, and chronic kidney

disease were associated with reduced survival. Among intra-arrest factors, witnessed arrest,

monitored setting, IHCA during working hours, and shockable rhythm were associated with

increased survival from IHCA, while tracheal intubation during arrest, and prolonged

resuscitation were associated with reduced survival. These findings provide comprehensive

evidence related to the association between important prognostic factors and odds of survival

following IHCA.

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FIGURE AND TABLE LEGENDS:

Table 1: Characteristics of the 23 included cohorts.

Table 2: Pre- and Intra-arrest prognostic factors and associated odds of survival following in-hospital cardiac arrest. Abbreviations: OR = odds ratio; CI = confidence interval; COPD = Chronic obstructive pulmonary disease

Figure 1: Flow chart summarizing evidence search and study selection.

Figure 2: Forest plots depicting pre-arrest factors and associated odds of survival following in-hospital cardiac arrest.

Figure 3: Forest plots depicting intra-arrest factors and associated odds of survival following in-hospital cardiac arrest.

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Table 1: Characteristics of the 23 included cohorts.

Description Number of Studies (%)Continent of StudyNorth America 12 (52.2)Europe 6 (26.1)Asia 4 (17.4)Australia 1 (4.3)Year of Publication1990-1994 2 (8.7)1995-1999 3 (13.0)2000-2004 5 (21.7)2005-2009 2 (8.7)2010-2014 5 (21.7)2015-2019 8 (34.8)Study DesignProspective Cohort 10 (43.5)Retrospective Cohort 13 (56.5)SitesSingle-Center 10 (43.5)Multi-Center 13 (56.5)

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Table 2: Pre- and Intra-arrest prognostic factors and associated odds of survival following in-hospital cardiac arrest. Abbreviations: OR = odds ratio; CI = confidence interval; COPD = Chronic obstructive pulmonary disease

Model-Adjusted DataStudies OR 95% CI P ǂ I2 GRADE Certainty*

Pre-Arrest FactorsDemographicsMale Sex 7 0.84 0.73-0.95 0.007 66% ModerateAge ≥ 60 3 0.50 0.40-0.62 <0.001 50% LowAge ≥ 70 2 0.42 0.18-0.99 0.050 69% LowComorbidities at AdmissionActive Malignancy 4 0.57 0.45-0.71 <0.001 71% HighCongestive Heart Failure 1 0.62 0.56-0.68 <0.001 NA ModerateChronic Kidney Disease 5 0.56 0.40-0.78 0.001 92% HighCOPD 1 0.65 0.58-0.72 <0.001 NA ModerateDiabetes Mellitus 1 0.53 0.34-0.83 0.005 NA ModerateAdmission DiagnosisAcute Coronary Syndrome 2 0.70 0.28-1.78 0.460 99% LowSepsis 1 0.80 0.70-0.91 0.001 NA Moderate

Intra-Arrest FactorsWitnessed Arrest 4 2.71 2.17-3.38 <0.001 68% HighMonitored Patient 6 2.23 1.41-3.52 <0.001 97% HighArrest During Daytime Hours 5 1.41 1.20-1.66 <0.001 94% HighVentricular Tachycardia 4 3.76 2.95-4.78 <0.001 85% HighVentricular Fibrillation 4 3.68 2.68-5.05 <0.001 94% HighAsystole 4 0.42 0.32-0.56 <0.001 12% HighPulseless Electrical Activity 2 0.59 0.27-1.27 0.180 77% HighShockable Rhythm 12 5.28 3.78-7.39 <0.001 96% HighIntubation During Arrest 5 0.54 0.42-0.70 <0.001 73% ModerateResuscitation Duration ≥ 15 min. 2 0.12 0.07-0.19 <0.001 27% Highǂ: P-values obtained from the test for overall effect.*Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) certainty of estimates in studies of prognosis, as described in Iorio et al., BMJ, 2015.

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Confidential: For Review OnlyFigure 1: Flow chart summarizing evidence search and study selection.

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Figure 2: Forest plots depicting pre-arrest factors and associated odds of survival following in-hospital cardiac arrest.

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Figure 3: Forest plots depicting intra-arrest factors and associated odds of survival following in-hospital cardiac arrest.

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Survival Following In-Hospital Cardiac Arrest - Systematic Review – Supplement

1

Fernando SM, Tran A, Cheng W, Rochwerg B, Taljaard M, Vaillancourt C, Rowan KM, Harrison DA, Nolan JP, Kyeremanteng K, McIsaac DI, Guyatt GH, Perry JJ. Pre- and Intra-Arrest Factors Associated with Survival Following Adult In-Hospital Cardiac Arrest – A Systematic Review and Meta-Analysis ELECTRONIC APPENDIX

Supplemental Table 1: Standardized Data Extraction Sheet ...............................................4

Supplemental Table 2: CHARMS-PF Checklist Detailed Characteristics of the 23 Included Cohorts..................................................................................................................6

Supplemental Table 3 – CHARMS-PF Checklist of Key Items in 23 Included Studies...10

Supplemental Table 4: Pre-Arrest Factors Evaluated in the 23 Included Cohorts ............11

Supplemental Table 5: Intra-Arrest Factors Evaluated in the 23 Included Cohorts ..........12

Supplemental Table 6: Prognostic Factors Included in Adjustment for Mortality in the 23 Included Cohorts................................................................................................................13

Supplemental Table 7: QUIPS Quality Assessment for Risk of Bias of the 23 Included Cohorts...............................................................................................................................14

Supplemental Table 8: GRADE Certainty of Prognostic Estimates – Pre-Arrest Factors 15

Supplemental Table 9: GRADE Certainty of Prognostic Estimates – Intra-Arrest Factors...........................................................................................................................................17

Supplemental Table 10: CHARMS-PF Checklist Detailed Characteristics of the 30 Studies with Unadjusted Values Only ...............................................................................19

Supplemental Table 11: Results of Meta-Analysis of Unadjusted Analyses for Prediction of Survival Following In-Hospital Cardiac Arrest. ...........................................................25

Supplemental Figure 2: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Male Sex and Survival Following In-Hospital Cardiac Arrest. ......26

Supplemental Figure 3: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Age and Survival Following In-Hospital Cardiac Arrest. ..............27

Supplemental Figure 4: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Malignancy and Survival Following In-Hospital Cardiac Arrest. ..28

Supplemental Figure 5: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Congestive Heart Failure and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................29

Supplemental Figure 6: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Chronic Kidney Disease and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................30

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Supplemental Figure 7: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Chronic Obstructive Pulmonary Disease and Survival Following In-Hospital Cardiac Arrest. ....................................................................................................31

Supplemental Figure 8: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Diabetes Mellitus and Survival Following In-Hospital Cardiac Arrest. ................................................................................................................................32

Supplemental Figure 9: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Acute Coronary Syndrome and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................33

Supplemental Figure 10: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Sepsis and Survival Following In-Hospital Cardiac Arrest. ...........34

Supplemental Figure 11: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Witnessed Arrest and Survival Following In-Hospital Cardiac Arrest. ................................................................................................................................35

Supplemental Figure 12: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Monitored Arrest and Survival Following In-Hospital Cardiac Arrest. ................................................................................................................................36

Supplemental Figure 13: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Arrest During Daytime Hours and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................37

Supplemental Figure 14: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Ventricular Tachycardia and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................38

Supplemental Figure 15: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Ventricular Fibrillation and Survival Following In-Hospital Cardiac Arrest. ................................................................................................................................39

Supplemental Figure 16: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Asystole and Survival Following In-Hospital Cardiac Arrest. .......40

Supplemental Figure 17: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Pulseless Electric Activity and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................41

Supplemental Figure 18: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Shockable Rhythm and Survival Following In-Hospital Cardiac Arrest. ................................................................................................................................42

Supplemental Figure 19: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Endotracheal Intubation and Survival Following In-Hospital Cardiac Arrest. ...................................................................................................................43

Supplemental Figure 20: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Resuscitation Duration > 15 minutes and Survival Following In-Hospital Cardiac Arrest. ....................................................................................................44

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Supplemental Figure 1: Electronic Search Strategies.

Databases Searched: EMBASE Classic + Embase PubMed/Medline Scopus Web of Science Cochrane Central Register of Controlled Trials (CENTRAL)

EMBASE Classic + EMBASE 1947 to Week 6 2019Date of Search: February 4, 2019 __ Search Strategy Results1 cardiac arrest.mp. 487102 cardiac arrest.tw. 459433 predict*.ti. 406857 4 model*.ti. 6412305 utility.ti. 410336 scor*.ti. 807307 validat*.ti. 947668 risk*.ti. 6018289 prognos*.ti. 18731110 associat*.ti. 90628211 factor*.ti. 78285212 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 325225913 1 or 2 4871014 12 and 13 8740

PubMed/MEDLINE 1946 to Week 6 2019Date of Search: February 4, 2019 __ Search Strategy Results1 cardiac arrest.mp. 312962 cardiac arrest.tw. 298763 predict*.ti. 2858734 model*.ti. 5314845 utility.ti. 282336 scor*.ti. 541907 validat*.ti. 669768 risk*.ti. 4390259 prognos*.ti. 13970510 associat*.ti. 74696211 factor*.ti. 66749112 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 260654313 1 or 2 3129614 12 and 13 4925

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Supplemental Table 1: Standardized Data Extraction Sheet

Data to be Extracted Notes to ReviewerBasic Study Information

Study TitleJournal/ConferenceConference Abstract vs. Full-textYear of PublicationLanguage If published in language other than

English - ExcludeAuthor List first author onlyCorrespondence EmailStudy DesignProspective vs. RetrospectiveNumber of SitesCountry/Countries of Study

Eligibility AssessmentDoes the study include only adult patients (i.e. ≥ 16 years of age)?

If “No” – Exclude

Does the study only include patients with in-hospital cardiac arrest (IHCA)?


Does the study include patients from any of the following: A) Emergency Department; B) Intensive Care Unit; C) Hospital Wards


Does the study provide original data related to pre-arrest and intra-arrest variables of interest?


Does the study provide short-term mortality outcome data (i.e. in-hospital, or 30-day)?


Does the study include cases of out-of-hospital cardiac arrest?

If “Yes” – Exclude

Does the study only include patients receiving a particular post-arrest investigation (e.g. computed tomography) or treatment (e.g. therapeutic hypothermia, extracorporeal life support)?

If “Yes” – Exclude

Is the data presented in the study completely included in another report?

If “Yes” – Exclude, include only study with the largest number of patients

Are the unadjusted or adjusted odds ratios stated, or can they be derived?

If “No” – Contact Corresponding Author, if no response after three attempts, then exclude

Prognostic FactorsIn what setting were prognostic factors calculated?

e.g. Emergency Department, ICU

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OutcomeHow was mortality defined (i.e. timing of outcome)?

i.e. in-hospital or 30-day

Study PopulationFrom which setting were patients recruited?

e.g. Emergency Department, Hospital Wards, ICU

Was population was included?Were elderly patients included?Were patients with a ‘Do Not Resuscitate’ (or similar) order included?Were pregnant patients included?Were patients with any other co-morbidity included/excluded?

Odds Ratio Index Factor 1Pre-/Intra-arrest factor evaluated e.g. age, sex, witnessed, shockableTotal number of patientsTotal number of Mortality+ PatientsTotal number of Mortality- patientsTotal number of Factor+ patientsTotal number of Factor- patientsUnadjusted Odds RatioAdjusted Odds RatioConfounders included in model adjustment

Odds Ratio Index Factor 2Pre-/Intra-arrest factor evaluated e.g. age, sex, witnessed, shockableTotal number of patientsTotal number of Mortality+ PatientsTotal number of Mortality- patientsTotal number of Factor+ patientsTotal number of Factor- patientsUnadjusted Odds RatioAdjusted Odds RatioConfounders included in model adjustment

Author ContactContact author? If more information needed, indicate here

to contact author

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Supplemental Table 2: CHARMS-PF Checklist Detailed Characteristics of the 23 Included Cohorts (Adapted from Riley et al., BMJ, 2019). Abbreviations: CPR = Cardiopulmonary Resuscitation; ED = Emergency Department; ICU = Intensive Care Unit; IHCA = In-Hospital Cardiac Arrest OHCA = Out-of-Hospital Cardiac Arrest; OR = Operating Room

Author (Year) Journal Type of Study Sites Country Years Sample Size

Survived to Hospital Discharge

% Survival Inclusion Criteria

Exclusion Criteria

Al-Dury (2017) Am J Emerg Med

Retrospective Cohort Study

66 Sweden 2006-2015 14933 4181 28.0 Patients 18 years or older, suffering IHCA, receiving CPR

Ballew (1994) Arch Intern Med


1 USA 1990-1991 313 50 16.0 > or = 18, ICD diagnosis of cardiac arrest OR completion of cardiac arrest form, received CPR

<18, OHCA, arrest in non-ward location (ED, OR, recovery room, or cardiac cath lab)

Bialecki (1995) Chest Retrospective Cohort Study

1 USA 1989-1991 242 40 16.5 Adult patients with attempt at CPR following cardiac arrest in-hospital

Brady (2011) Resuscitation Prospective Cohort Study

USA 2000-2008 74213 13224 17.8 Adult patients experiencing cardiac arrest in-hospital

Brindley (2002) CMAJ Retrospective Cohort Study

3 Canada 1997-1999 247 28 11.3 > or = 18, received CPR

Admitted to ICU, non-ward location (ED, OR), incomplete record

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Chan (2013) Am J Emerg Med


2 Hong Kong 2008 431 23 5.3 Adult patients with in-hospital resuscitation following cardiac arrest

Chen (2016) J Chin Med Assoc


1 Taiwan 2012 382 45 11.8 Adult patients with in-hospital resuscitation following cardiac arrest

OHCA, 'Do Not Resuscitate' order

Cleverley (2013)

Resuscitation Retrospective Cohort Study

6 Canada 2002-2006 668 66 9.9 > or = 18. receiving CPR

Catheterization laboratory, CCU, ICU, OR arrests

Danciu (2004) Resuscitation Retrospective Cohort Study

1 USA 2000-2002 219 33 15.1 Adult patients with attempt at CPR following cardiac arrest in-hospital

de Vos (1999) Arch Intern Med


1 Netherlands 1988-1994 553 120 21.7 Adult patients with attempt at CPR following cardiac arrest in-hospital

OHCA, 2nd IHCA during same hospitalization

Doig (2000) Clin Invest Med

Prospective Cohort Study

1 Canada 1992-1994 239 51 21.3 Adult patients with attempt at CPR following cardiac arrest in-hospital

Dumot (2001) Arch Intern Med


1 USA 1994-1995 445 104 23.4 ≥18 years, receiving CPR for IHCA

<18 years, ‘Do Not Resuscitate’ order

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Hessulf (2018) Int J Cardiol Retrospective Cohort Study

66 Sweden 2006-2015 17747 5058 28.5 Patients 18 years or older, suffering IHCA, receiving CPR

Larkin (2010) Resuscitation Prospective Cohort Study

366 USA 2000-2004 49130 7812 15.9 Adult patients experiencing cardiac arrest in-hospital

Li (2018) Am J Emerg Med


3 China 2012-2016 320 68 21.3 Adult patients with acute coronary syndrome, complicated by cardiac arrest

OHCA, 'Do Not Resuscitate' order

Marwick (1991) Resuscitation Prospective Cohort Study

1 Australia 1984-1987 710 193 27.2 Patients attended to by Cardiac Arrest Team

Respiratory arrests

Meaney (2010) Crit Care Med



Ohlsson (2014) Resuscitation Prospective Cohort Study

1 Sweden 2007-2010 287 58 20.2 Prospectively enrolled following cardiac arrest

Pediatric cases, ‘Do Not Resuscitate’ order, missing data

Peberdy (2008) JAMA Prospective Cohort Study


Shao (2016) Resuscitation Prospective Cohort Study

12 China 2014 2712 247 9.1 ≥ 14 years, pulseless, receiving CPR

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Skrifvars (2007)

Resuscitation Prospective Cohort Study

5 Finland 1994-2003 1578 463 29.3 Patients attended to by Cardiac Arrest Team

Zoch (2000) Arch Intern Med


2 USA 1983-1991 948 305 32.2 Patients attended to by Cardiac Arrest Team

UK NCAA (2019)


185 United Kingdom 2013-2018 90276 37328 41.4 Patients attended to by Cardiac Arrest Team

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Supplemental Table 3 – CHARMS-PF Checklist of Key Items in 23 Included Studies (Adapted from Moons et al., PLoS Med, 2014).

Source of data: N (%)Case Control 0 (0.0)Observational Cohort 17 (73.9)Randomized Trial 0 (0.0)Registry Data 6 (26.1)

Participants:Indicated participant eligibility and recruitment method 23 (100.0)Provided participant description 23 (100.0)

Provided study dates 23 (100.0)Outcomes to be predicted:

Definition and method for measurement of outcomes 23 (100.0) Was the same outcome definition used in all participants? 23 (100.0)

Were the outcomes assessed without knowledge of the candidate prognostic factors? 10 (43.5) Provided time of outcome occurrence or summary of duration of follow-up 23 (100.0)

Prognostic factors (index and comparator prognostic factors): Indicated number and type of prognostic factors 23 (100.0)

Provided definition and method for measurement of prognostic factors 23 (100.0 Timing of prognostic factor measurement (e.g. prior to IHCA, during IHCA, etc.) 23 (100.0)

Were prognostic factors assessed blinded for outcome? 10 (43.5) Specified handling of prognostic factors in analysis (e.g. continuous, categorized) 23 (100.0)

Sample size: Was a sample size calculation conducted and, if so, how? 3 (13.0) Indicated number of participants and number of outcomes or events 23 (100.0)

Number of outcomes considered in relation to the number of prognostic factors 23 (100.0)Missing data:

Reported number of participants with any missing value 17 (73.9) Reported number of participants with missing data for each prognostic factor 17 (73.9) Provided details of attrition 11 (47.8)

Reported handling of missing data 15 (65.2)Analysis:

Indicated modeling method utilized 23 (100.0) Reported method for selection of factors for inclusion in multivariable model 23 (100.0)

Reported method of handling each continuous prognostic factor 16 (69.6)Results:

Reported unadjusted and adjusted prognostic effect estimates 23 (100.0) Provided the set of adjustment factors used 23 (100.0)

Interpretation and discussion: Provided interpretation of presented results 23 (100.0)

Compared results with other studies, including strengths and limitations 23 (100.0)

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Supplemental Table 4: Pre-Arrest Factors Evaluated in the 23 Included Cohorts. Abbreviations: ACS = Acute Coronary Syndrome; CHF = Congestive Heart Failure; CKD = Chronic Kidney Disease; COPD = Chronic Obstructive Pulmonary Disease

Study Age ≥ 60 Age ≥ 70 Sex Malignancy CHF CKD COPD Diabetes ACS SepsisAl Dury (2017) xBallew (1994)Bialecki (1995)Brady (2011)Brindley (2002) xChan (2013)Chen (2016) xCleverly (2013)Danciu (2004) xde Vos (1999) x xDoig (2000)Dumot (2001)Hessulf (2018) x x x x xLarkin (2010) x x x xLi (2018) xMarwick (1991) x xMeaney (2010)Ohlsson (2014) xPeberdy (2008)Shao (2016) x xSkrifvars (2007) x x x xZoch (2000)UK NCAA (2019) x x

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Supplemental Table 5: Intra-Arrest Factors Evaluated in the 23 Included Cohorts. Abbreviations: ACS = Acute Coronary Syndrome; CHF = Congestive Heart Failure; CKD = Chronic Kidney Disease; COPD = Chronic Obstructive Pulmonary Disease

Study Witnessed Monitored Daytime VT VF Asystole PEA Shockable Intubation DurationAl Dury (2017)Ballew (1994) x xBialecki (1995) x x xBrady (2011) x xBrindley (2002) xChan (2013) x xChen (2016) xCleverly (2013) x x x x x xDanciu (2004) xde Vos (1999) xDoig (2000) xDumot (2001) xHessulf (2018) x x x x xLarkin (2010) x x x x xLi (2018) xMarwick (1991) x xMeaney (2010) x xOhlsson (2014) x xPeberdy (2008) x xShao (2016) xSkrifvars (2007) x x xZoch (2000) xUK NCAA (2019) x x x x x x x

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Supplemental Table 6: Prognostic Factors Included in Adjustment for Mortality in the 23 Included Cohorts. Abbreviations: CPR = Cardiopulmonary resuscitation; STEMI = ST-Elevation Myocardial Infarction

Study – Author (Year) Prognostic Factors Included in Adjusted AnalysesAl Dury (2017) age; sex; initial rhythm, etiology of arrest; comorbiditiesBallew (1994) age; sex; initial rhythm; etiology of arrestBialecki (1995) age; sex; initial rhythm; etiology of arrest; location of arrest; event duration;

intubation; laboratory valuesBrady (2011) age; sex; initial rhythm; etiology of arrest; ethnicity; time of day; weekend;

illness category; location; comorbidities; pharmacological interventions; time to first shock; event duration; interval between admit and event; total number of arrests this visit

Brindley (2002) age; sex; initial rhythm; etiology of arrest; location; witnessed arrestChan (2013) age; sex; initial rhythm; etiology of arrest; location; witnessed arrest; time of

day; intubation; pharmacological interventionsChen (2016) age; sex; initial rhythm; pharmacological interventions; event durationCleverly (2013) age; sex; initial rhythm; time of dayDanciu (2004) age; sex; initial rhythm; etiology of arrest; witnessed arrest; time of day;

event durationde Vos (1999) age; sex; initial rhythm; comorbidities; functional status before admissionDoig (2000) age; sex; initial rhythm; etiology of arrest; witnessed arrest; pharmacological

interventions; time to defibrillation; functional statusDumot (2001) age; sex; initial rhythm, time of day; event duration; intubation;

pharmacological interventions; Hessulf (2018) age; sex; initial rhythm; etiology of arrest; location; time of day;

comorbidities; witnessed arrest; monitoredLarkin (2010) age; sex; initial rhythm; comorbidities; location; intubation; pharmacological

interventions; witnessed arrest; monitored; total number of arrests this visitLi (2018) age; sex; initial rhythm; location; event duration; smoker; prior percutaneous

coronary interventionMarwick (1991) age; sex; initial rhythm; location; witnessed; pharmacological interventions;

time to CPR; time to defibrillationMeaney (2010) age; sex; initial rhythm; location; witnessed; monitored; pharmacological

interventionsOhlsson (2014) age; sex; initial rhythm; heart rate; STEMIPeberdy (2008) age; sex; initial rhythm; location; witnessed; monitored; pharmacological

interventions; duration of event; delay in CPR; hospital size; use of epinephrine

Shao (2016) age; sex; initial rhythm; location; delay in CPRSkrifvars (2007) age; sex; initial rhythm; etiology of arrest; witnessed; time of day; location;

comorbidities; Zoch (2000) age; sex; initial rhythm; etiology of arrest; location; monitoredUK NCAA (2019) age; sex; initial rhythm; time of day; location;

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Supplemental Table 7: QUIPS Quality Assessment for Risk of Bias of the 23 Included Cohorts. Abbreviations: PF = Prognostic Factor; ROB = Risk of bias

StudyStudy

ParticipationStudy

AttritionPF

MeasurementOutcome

Measurement AdjustmentStatisticalReporting

Al Dury (2017) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBBallew (1994) Low ROB Moderate ROB Low ROB Low ROB Low ROB Moderate ROBBialecki (1995) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBBrady (2011) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBBrindley (2002) Moderate ROB Low ROB Low ROB Low ROB Low ROB Low ROBChan (2013) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBChen (2016) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBCleverly (2013) Moderate ROB Moderate ROB Low ROB Low ROB Low ROB Moderate ROBDanciu (2004) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBde Vos (1999) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBDoig (2000) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBDumot (2001) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBHessulf (2018) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBLarkin (2010) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBLi (2018) Moderate ROB Low ROB Low ROB Low ROB Low ROB Low ROBMarwick (1991) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBMeaney (2010) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBOhlsson (2014) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBPeberdy (2008) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBShao (2016) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBSkrifvars (2007) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBZoch (2000) Low ROB Low ROB Low ROB Low ROB Low ROB Low ROBUK NCAA (2019) Moderate ROB Low ROB Low ROB Low ROB Low ROB Low ROB

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Supplemental Table 8: GRADE Certainty of Prognostic Estimates – Pre-Arrest Factors (Adapted from Iorio et al., BMJ, 2015).

Certainty assessment№ of studies

Study design Risk of bias

Inconsistency Indirectness Imprecision Other considerations

impact Certainty Importance

Male sex

7 observational studies

not serious a

not serious b not serious serious c none Pooled Odds Ratio = 0.84 (95% CI 0.73-0.95)

⨁⨁⨁◯MODERATE

CRITICAL

Age


serious d not serious b not serious serious c none Pooled Odds Ratio = 0.42 (95% CI 0.18-0.99)

⨁⨁◯◯LOW

CRITICAL

History of Malignancy


not serious

not serious b not serious not serious none Pooled Odds Ratio = 0.57 (95% CI 0.45-0.71)

⨁⨁⨁⨁HIGH

CRITICAL

History of Congestive Heart Failure


not serious

not serious not serious serious e none Pooled Odds Ratio = 0.62 (95% CI 0.56-0.68)


CRITICAL

History of Chronic Kidney Disease


not serious


⨁⨁⨁⨁HIGH

CRITICAL

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History of Chronic Obsrtuctive Pulmonary Disease


not serious



CRITICAL

History of Diabetes Mellitus


not serious



CRITICAL

Diagnosis of Acute Coronary Syndrome


not serious

serious f not serious serious c none Pooled Odds Ratio = 0.70 (95% CI 0.28-1.78)

⨁⨁◯◯LOW

CRITICAL

Diagnosis of Sepsis


not serious



CRITICAL

Explanationsa. The majority of weight in pooled estimate (>65%) comes from low RoB studies, the one moderate RoB study is consistent with the others. b. Despite a high I-squared there is high degree of overlap amongst point estimates and confidence intervals. c. Wide confidence intervals do not rule out important prognostic factor or no impact of this factor. d. Majority of pooled estimate weight comes from studies at moderate RoB. e. Small amount of study data and studies reporting on this variable. f. High Isquared with non-overlapping point estimates and discrepant findings amongst included studies.

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Supplemental Table 9: GRADE Certainty of Prognostic Estimates – Intra-Arrest Factors (Adapted from Iorio et al., BMJ, 2015).





Witnessed Arrest


not serious a


⨁⨁⨁⨁HIGH

CRITICAL

Monitored Patient


not serious a


⨁⨁⨁⨁HIGH

CRITICAL

Arrest during 'Daytime' Hours


not serious a


⨁⨁⨁⨁HIGH

CRITICAL

Initial Shockable Rhythm


not serious a

not serious b not serious not serious strong association

Pooled Odds Ratio = 4.80 (95% CI 3.47-6.64)

⨁⨁⨁⨁HIGH

CRITICAL

Intubation During Resuscitation


not serious

not serious b serious c not serious none Pooled Odds Ratio = 0.54


CRITICAL

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(95% CI 0.42-0.70)

Duration of Resuscitation > 15 minutes


serious d

not serious not serious not serious strong association

Pooled Odds Ratio = 0.12 (95% CI 0.07-0.19)

⨁⨁⨁⨁HIGH

CRITICAL

Explanationsa. The majority of pooled estimate weight comes from low risk of bias studies. The one moderate risk of bias study is consistent with the low risk of bias studies. b. Despite a high I-squared there is high degree of overlap between point estimates and confidence intervals. c. Variable timing of intubation, unclear other confounding variables contributing to whether patient is intubated or not. d. The majority of pooled estimate weight comes from data at moderate risk of bias.

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Supplemental Table 10: CHARMS-PF Checklist Detailed Characteristics of the 30 Studies with Unadjusted Values Only (Adapted from Riley et al., BMJ, 2019). Abbreviations: CPR = Cardiopulmonary Resuscitation; ED = Emergency Department; ICU = Intensive Care Unit; IHCA = In-Hospital Cardiac Arrest OHCA = Out-of-Hospital Cardiac Arrest; OR = Operating Room

Author (Year)

Journal Type of Study

Sites Country Years Sample Size

Survived to Hospital Discharge

% Survival Inclusion Criteria

Exclusion Criteria

Andersen (2017)

JAMA Prospective Cohort Study

668 USA 2000-2014

108079 24256 22.4 Adult patients experiencing cardiac arrest in-hospital

Andreasson (1998)


1 Sweden 1994-1995

170 73 42.9 ≥ 18 years, arrested and received CPR in-hospital

Bedell (1983)

N Engl J Med Prospective Cohort Study

1 USA 1981-1982

294 41 13.9 Adult patients with attempt at CPR following cardiac arrest in-hospital

Cohn (2004)

Int Med J Retrospective Cohort Study

1 Australia 2001-2003

105 22 21.0 ≥ 18, received CPR

Admitted to ICU, non-ward location (ED, OR), incomplete record

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Cooper (2006)


1 United Kingdom

1993-2003

2121 338 15.9 Adult patients with in-hospital resuscitation following cardiac arrest

Age < 20, 'Do Not Resuscitate' order

Dodek (1998)


1 Canada 1989-1990


Ebell (1997)

Med Decis Making


3 USA 1992-1993

656 35 5.3 Identified from CPR log at hospital

George (1989)

Am J Med Prospective Cohort Study

1 USA 1985 140 34 24.3 Consecutive patients requiring CPR in-hospital

Huang (2002)


1 Taiwan 1999-2000

103 18 17.5 Age <17, OHCA

Karetzky (1995)

Arch Intern Med Retrospective Cohort Study

1 USA 1990-1992

668 55 8.2 Patients 18 years or older, suffering IHCA, receiving CPR

Ventilation without compressions

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Marik (1997)

J Crit Care Retrospective Cohort Study

1 USA 1991-1995


Ofoma (2018)

J Am Coll Cardiol


470 USA 2000-2014

151071 28097 18.6 Adult patients experiencing cardiac arrest in-hospital

O'Keeffe (1991)

Q J Med Retrospective Cohort Study

1 Ireland 274 25 9.1 All patients receiving CPR in-hospital

Patrick (1998)


1 New Zealand

1995-1996

133 35 26.3 Prospectively enrolled following cardiac arrest

Peters (2007)

Am J Crit Care Prospective Cohort Study

1 Australia 2004 128 41 32.0 Patients attended to by Cardiac Arrest Team, Loss of pulse

OHCA, respiratory arrest, DNR

Piscator (2016)


1 Sweden 2014 174 41 23.6 All cases identified through the hospital's cardiac arrest sheet

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Radeschi (2017)


36 Italy 2011-2014

1539 228 14.8 Adult patients with in-hospital resuscitation following cardiac arrest

OHCA

Rakic (2005)

Croat Med J Prospective Cohort Study

1 Croatia 2003 120 27 22.5 Patients attended to by Cardiac Arrest Team

Roberts (1990)

Chest Retrospective Cohort Study

1 Canada 1985-1986

310 30 9.7 All patients receiving CPR in-hospital

Arrests occurring the ER, OR

Robinson (1994)

Chest Retrospective Cohort Study

1 USA 1989 83 24 28.9 Patients 18 years or older, suffering IHCA, receiving CPR

Arrests occurring the ER, OR; OHCA

Rosenberg (1992)

Arch Intern Med Retrospective Cohort Study

2 USA 1988-1989

300 70 23.3 Absence of pulse and initiation of CPR

Arrests occurring the ER, OR; OHCA; Seizure

Rozenbaum (1988)

Crit Care Med Prospective Cohort Study

1 Israel 1986 71 13 18.3 Patients 18 years or older, suffering IHCA, receiving CPR

Repeat arrests

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Sandroni (2004)


1 Italy 2000-2002

114 37 32.5 >18; Patients attended to by Cardiac Arrest Team

OHCA; OR; outpatient

Schultz (1996)


1 USA 1988-1991

266 24 9.0 Patients 18 years or older, suffering IHCA, receiving CPR

Skogvoll (1999)

Acta Anaesthesiologica Scandinavica


1 Norway 1990-1994

244 43 17.6 Patients attended to by Cardiac Arrest Team

Sowden (1984)

Anaesthesia Retrospective Cohort Study

1 United Kingdom

108 23 21.3 Patients experiencing cardiac arrest in-hospital

Taffett (1988)

JAMA Retrospective Cohort Study

1 USA 1984-1985


Tortolani (1990)


1 USA 470 68 14.5 Patients attended to by Cardiac Arrest Team; unresponsive; apneic; pulseless

Respiratory arrests; syncope

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van Walraven (1999)

Arch Intern Med Prospective Cohort Study

5 Canada 1989-1995


<16; Terminal illness; Absence of CPR >15 mins from arrest; trauma; exanguination; OR; detectable pulse

van Walraven (2000)

JAMA Prospective Cohort Study

1 USA 1987-1996


NICU

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Supplemental Table 11: Results of Meta-Analysis of Unadjusted Analyses for Prediction of Survival Following In-Hospital Cardiac Arrest. Abbreviations: CHF = Congestive Heart Failure; CI = confidence interval; COPD = Chronic Obstructive Pulmonary Disease; OR = Odds ratio

Studies OR 95% CI P ǂ I2

Pre-Arrest FactorsDemographicsMale Sex 29 1.01 0.93-1.10 0.810 61%Age ≥ 60 10 0.52 0.37-0.71 <0.001 98%Age ≥ 70 12 0.41 0.30-0.55 <0.001 66%Comorbidities at AdmissionActive Malignancy 17 0.51 0.42-0.62 <0.001 50%CHF 10 0.83 0.62-1.10 0.200 92%Chronic Kidney Disease 14 0.64 0.49-0.85 0.002 90%COPD 6 0.92 0.50-1.70 0.260 79%Diabetes Mellitus 9 0.85 0.71-1.03 0.090 77%Admission DiagnosisAcute Coronary Syndrome 10 1.17 0.80-1.72 0.410 96%Sepsis 8 0.49 0.29-0.83 0.009 46%

Intra-Arrest FactorsWitnessed Arrest 18 4.04 2.94-5.55 <0.001 84%Monitored Patient 14 2.28 1.58-3.28 <0.001 97%Arrest During Daytime Hours 13 1.45 1.27-1.67 <0.001 96%Ventricular Tachycardia 11 3.82 2.76-5.28 <0.001 95%Ventricular Fibrillation 11 3.47 2.69-4.47 <0.001 94%Asystole 21 0.35 0.31-0.41 <0.001 72%Pulseless Electrical Activity 19 0.43 0.36-0.50 <0.001 80%Shockable Rhythm 38 5.77 5.03-6.61 <0.001 87%Intubation During Arrest 10 0.17 0.10-0.29 <0.001 87%Resuscitation Duration ≥ 15 min. 8 0.14 0.10-0.20 <0.001 78%ǂ: P-values obtained from the test for overall effect.

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Supplemental Figure 2: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Male Sex and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 3: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Age and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 4: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Malignancy and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 5: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Congestive Heart Failure and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 6: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Chronic Kidney Disease and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 7: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Chronic Obstructive Pulmonary Disease and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 8: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Diabetes Mellitus and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 9: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Acute Coronary Syndrome and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 10: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Sepsis and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 11: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Witnessed Arrest and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 12: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Monitored Arrest and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 13: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Arrest During Daytime Hours and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

* Note: Contrasts between time intervals of arrest were different across studies: Bialecki (7-15 vs. 15-7), Brindley (7-15 vs. 15-23 for adjusted analysis, 7-15 vs. 15-7 for unadjusted analysis), Chan (7-14 vs. 14-7), Chen (8-20 vs. 20-8), Cooper (7-15 vs. 15-7), Danciu (6-18 vs. 18-6), Dumot (6-24 vs. 0-6), Hessulf (8-20 M-F vs. other), Ofoma (7-23 M-F vs. other), Peberdy (7-23 vs. 23-7), Rakic (8-16 vs. 16-8), Skrifvars (mixture of 8-17 and 8-15:45 M-F vs. other) , UK NCAA (8-20 vs. 20-8)

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Supplemental Figure 14: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Ventricular Tachycardia and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 15: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Ventricular Fibrillation and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 16: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Asystole and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 17: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Pulseless Electric Activity and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 18: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Shockable Rhythm and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 19: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Endotracheal Intubation and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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Supplemental Figure 20: Forest Plots of Adjusted and Unadjusted Analyses for Association Between Resuscitation Duration > 15 minutes and Survival Following In-Hospital Cardiac Arrest. Abbreviations: CI = Confidence Interval; OR = Odds Ratio; SE = Standard Error

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