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Trends in survival and introduction of the 2010 and 2015 guidelines for adult in-hospital cardiac arrest
Journal Pre-proof Trends in Survival and Introduction of the 2010 and 2015 Guidelines for Adult In-Hospital Cardiac Arrest Mathias J. Holmberg, Asger Granfeldt, Saket Girotra, Michael W. Donnino, Lars W. Andersen, for the American Heart Association’s Get With The Guidelines®-Resuscitation Investigators, Paul Chan, Ari Moskowitz, Anne V. Grossestreuer, Dana Edelson, Joseph Ornato, Katherine Berg, Mary Ann Peberdy, Matthew Churpek, Michael Kurz, Monique Anderson Starks, Sarah Perman, Zachary Goldberger
PII:
S0300-9572(20)30529-3
DOI:
https://doi.org/10.1016/j.resuscitation.2020.10.022
Reference:
RESUS 8750
To appear in:
Resuscitation
Received Date:
3 September 2020
Revised Date:
27 September 2020
Accepted Date:
16 October 2020
Please cite this article as: Holmberg MJ, Granfeldt A, Girotra S, Donnino MW, Andersen LW, Chan P, Moskowitz A, Grossestreuer AV, Edelson D, Ornato J, Berg K, Peberdy MA, Churpek M, Kurz M, Starks MA, Perman S, Goldberger Z, Trends in Survival and Introduction of the 2010 and 2015 Guidelines for Adult In-Hospital Cardiac Arrest, Resuscitation (2020), doi: https://doi.org/10.1016/j.resuscitation.2020.10.022
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier.
Trends in Survival and Introduction of the 2010 and 2015 Guidelines for Adult In-Hospital Cardiac Arrest Authors Mathias J. Holmberg, M.D., M.P.H., Ph.D. 1,2,3 , Asger Granfeldt, M.D., Ph.D., D.M.Sc.4,5, Saket Girotra, M.D., S.M. 6 , Michael W. Donnino, M.D. 2,7 , and Lars W. Andersen, M.D., M.P.H., Ph.D., D.M.Sc. 1,2,8,9, for
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the American Heart Association’s Get With The Guidelines®-Resuscitation Investigators*
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* The members of the Get With The Guidelines®-Resuscitation Adult Research Task Force are listed at
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the end of the article
1
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Affiliations
Research Center for Emergency Medicine, Department of Clinical Medicine, Aarhus University and
2 Center for
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Aarhus University Hospital, Aarhus, Denmark
Resuscitation Science, Department of Emergency Medicine, Beth Israel Deaconess Medical
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Center, Boston, MA, USA 3 Department of Cardiology,
Viborg Regional Hospital, Viborg, Denmark
Department of Intensive Care Medicine, Randers Regional Hospital, Randers, Denmark
5
Department of Intensive Care Medicine, Aarhus University Hospital, Aarhus, Denmark
6
Carver College of Medicine, University of Iowa, Iowa City, IA, USA
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4
7
Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel
Deaconess Medical Center, Boston, MA, USA 8
Prehospital Emergency Medical Services, Central Denmark Region, Denmark
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Department of Anesthesiology and Intensive Care, Aarhus University Hospital, Aarhus, Denmark
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Corresponding Author Lars W. Andersen M.D., M.P.H., Ph.D., D.M.Sc. Research Center for Emergency Medicine Department of Clinical Medicine Aarhus University and Aarhus University Hospital Phone: +45 51 78 15 11
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Email: [email protected]
Word Count Abstract: 238
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Word Count Manuscript: 3157 Figures and Tables: 5
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References: 34
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Abstract Aims To examine trends in survival from 2006 to 2018 and to assess whether the introduction of resuscitation guidelines was associated with a change in survival after adult in-hospital cardiac arrest.
Methods
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Using the Get With The Guidelines® – Resuscitation registry, we included adult patients with an in-
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hospital cardiac arrest between 2006 and 2018. The primary outcome was survival to hospital discharge. An interrupted time series analysis was used to compare survival before and after publication of the
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2010 and 2015 resuscitation guidelines.
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Results
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The analysis included 231,739 patients. Survival changed annually by 1.09% (95% CI, 0.74% to 1.43%; P <0.001) from 2006 to 2010, 0.26% (95% CI, –0.11% to 0.64%; P = 0.17) from 2011 to 2015, and –0.43% (95% CI, –0.96% to 0.11%; P = 0.12) from 2016 to 2018. The survival trend was lower within the post-
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2010 compared to the pre-2010 period (risk difference, –0.82% per year; 95% CI, –1.35% to –0.30%; P = 0.002) and within the post-2015 compared to the pre-2015 period (risk difference, –0.69% per year; 95% CI, –1.33% to –0.04%; P = 0.04). There was no immediate change in survival after publication of the 2010
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and 2015 guidelines.
Conclusions
In-hospital cardiac arrest survival increased from 2006 to 2010, after which the trend plateaued. The annual survival trend was lower following publication of the 2010 and 2015 guidelines. Research targeting in-hospital cardiac arrest as a unique entity may be necessary to improve outcomes.
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Keywords: Heart Arrest, Cardiopulmonary Resuscitation, Resuscitation, Mortality, Guidelines,
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Interrupted Time Series
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Introduction The most recent comprehensive report on trends in survival from in-hospital cardiac arrest in the United States was published in 2012, showing an increase in survival from 14% in 2000 to 22% in 2009. 1 The American Heart Association has since revised the Guidelines for Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care (ECC) in 2010 and 2015, including an emphasis on quality of CPR, revisions to the use of cardiac arrest medications, and revisions to post-resuscitation care (Table 1). 2, 3
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However, the association between the 2010 and 2015 resuscitation guidelines and survival from cardiac
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arrest in hospitalized patients has not been well-studied. Additionally, no large study has reported on trends in survival using contemporary data. 1
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In this study, we leveraged the Get With The Guidelines® – Resuscitation (GWTG-R) registry to examine trends in survival from 2006 to 2018 and to assess whether the introduction of the 2010 and
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2015 resuscitation guidelines were associated with a change in survival after adult in-hospital cardiac
Methods
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Study Design and Data Source
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arrest.
This study was an analysis of data from the GWTG-R registry. The GWTG-R registry is a United Statesbased quality-improvement registry of in-hospital cardiac arrest patients, sponsored by the American
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Heart Association. In the GWTG-R registry, cardiac arrest is defined as the presence of no central pulse requiring chest compressions, defibrillation, or both, with a hospital-wide or unit-based emergency response by acute care personnel. Data are collected at each participating site on all in-hospital cardiac arrests without a do-not-resuscitate order. The design, data collection, and reliability of the registry has been described in detail elsewhere. 4, 5 Hospital-level data were obtained from the 2018 American
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Hospital Association Annual Survey6 and linked to the GWTG-R registry by the American Heart Association data management vendor. IQVIA is the data collection coordination center for the American Heart Association and American Stroke Association GWTG programs. Because data were used primarily at the local site for quality improvement, sites were granted a waiver of informed consent under the common rule. The Institutional Review Board at Beth Israel Deaconess Medical Center (Boston, MA, USA) determined that
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research involving the GWTG-R registry does not meet the federal definition of human subject research.
Study Population, Exposure, and Outcomes
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We included adult patients ( 18 years of age) with an index in-hospital cardiac arrest between January 1st, 2006 and December 31st, 2018. Patients with missing data on survival to hospital discharge were
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excluded.
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The exposure of interest was the introduction of the CPR and ECC guidelines, published on November 2nd, 2010 and November 3rd, 2015 by the American Heart Association. 2, 3 The primary outcome was survival to hospital discharge. Secondary outcomes included sustained
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return of spontaneous circulation (ROSC) and survival to hospital discharge with a favorable neurological outcome. Sustained ROSC was defined as the presence of a pulse and no further need for chest compressions for at least 20 minutes. Neurological outcome was measured by the Cerebral Performance
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Category (CPC) score, with a CPC score of 1 or 2 signifying a favorable neurological outcome and a CPC score from 3 to 5 signifying an unfavorable neurological outcome. 7
Statistical Analysis Continuous data are presented as medians with first and third quartiles. Categorical data are presented
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as counts with frequencies. Differences in patient characteristics are reported using standardized differences. To examine whether the introduction of the 2010 and 2015 resuscitation guidelines were associated with a change in survival after adult in-hospital cardiac arrest, we performed an interrupted time series analysis by comparing trends in survival before and after introducing the guidelines. The study period was divided into pre-guideline and post-guideline segments based on the time of
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guideline publication. 2, 3 The pre-2010 guideline period was defined as the time from May 1st, 2006 to
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October 31st, 2010, the post-2010/pre-2015 guideline period was defined as the time from May 1st, 2011 to October 31st, 2015, and the post-2015 guideline period was defined as the time from May 1st, 2016 to
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December 31st, 2018. Since guidelines require implementation before any impact on survival may be
censored from the primary analyses.
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observed, the time period between the pre-guideline and post-guideline segments (six months) were
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The interrupted time series analysis involved fitting a regression model with separate intercept and slopes for each of the time segments. 8-11 The exposure of interest (the introduction of the 2010 and 2015 guidelines) acted as boundaries between the segments. The exposure association was estimated
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by comparing the survival intercept and slope for the post-guideline segment to the existing trends in the pre-guideline segment. A positive difference indicates a beneficial association and a negative difference indicates an unfavorable association between the guidelines and the outcome.
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We developed generalized linear models (GLM) using a modified Poisson regression approach (log link function)12, 13 and linear regression (identity link function)14 , respectively, to estimate the relative and absolute change in intercept and slope from the pre-guideline to post-guideline periods. Generalized estimating equations (GEE) were used to account for clustering of patients within hospitals. Primary results are reported as unadjusted relative risks (RR) and risk differences (RD) with 95% confidence intervals. These analyses were repeated for the secondary outcomes.
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We performed two prespecified subgroup analyses for the primary outcome based on the initial rhythm (shockable or non-shockable rhythm) and by only including patients who achieved sustained ROSC. We also performed five predefined sensitivity analyses. First, patient demographics (age categorized in 5-year bins and sex) were included in the primary model to obtain partly risk-adjusted estimates. Second, although the interrupted time series analysis implicitly accounts for potential confounding 8-11, 15 ,
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we repeated the analysis while adjusting for all patient, event, and hospital characteristics outlined in
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Table 2. Third, we repeated the interrupted time series analysis within a hierarchical regression
framework by estimating changes in intercept and slope from the pre-guideline to the post-guideline
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periods for each hospital. 16, 17 Additional details are provided in the Supplementary Methods. Fourth, we repeated the analysis only including events from hospitals reporting at least one cardiac arrest per year
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to the GWTG-R registry for the full study period (from 2006 to 2015 for the 2010 analysis and from 2011
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to 2018 for the 2015 analysis). Fifth, we accounted for various guideline implementation periods by repeating the analysis without any censored period and a censored period of 12 months. Two post-hoc sensitivity analyses were conducted to assess whether survival trends may have
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changed independently of the introduction of the resuscitation guidelines. First, we tested whether survival to hospital discharge followed a non-linear trend by adding time as quadratic and cubic terms to the pre-2010 and post-2010/pre-2015 segment of the model. Second, we estimated the optimal number
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and location of trend segments using Joinpoint (version 4.7.0.0) statistical software (National Cancer Institute). 18, 19 Additional details are provided in the Supplementary Methods. All analyses were two-sided, with a significance level of P <0.05. There was no adjustment for
multiple comparisons. 20 SAS version 9.4 (SAS Institute, Cary, NC, USA) was used for all analyses, unless otherwise specified.
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Results Patient Characteristics The study population included 70,016 patients in the pre-2010 guideline period (2006 to 2010), 89,782 patients in the post-2010/pre-2015 guideline period (2011 to 2015), and 71,941 patients in the post2015 guideline period (2016 to 2018) (Figure 1). The median age was 67 (56, 77) years, 146,400 (58%) patients were male, and 188,624 (82%) patients presented with an initial non-shockable rhythm in the
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full cohort (Table 2).
Survival to Hospital Discharge
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There were 15,114 (22%) survivors in the pre-2010 guideline period, 22,633 (25%) survivors in the post2010/pre-2015 guideline period, and 18,933 (26%) survivors in the post-2015 guideline period. There
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was an increase in survival within the pre-2010 guideline period (RD, 1.09% per year; 95% CI, 0.74% to
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1.43%; P <0.001). However, there was no statistically significant change in survival within the post2010/pre-2015 guideline period (RD, 0.26% per year; 95% CI, –0.11% to 0.64%; P = 0.17) and the post2015 guideline period (RD, –0.43% per year; 95% CI, –0.96% to 0.11%; P = 0.12).
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The annual trend in survival was lower within the post-2010 compared to the pre-2010 guideline period (RD, –0.82% per year; 95% CI, –1.35% to –0.30%; P = 0.02), as well as within the post-2015 compared to the pre-2015 guideline period (RD, –0.69% per year; 95% CI, –1.33% to –0.04%; P = 0.04).
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The immediate change in survival from introducing the resuscitation guidelines did not reach statistical significance for the 2010 guidelines (RD, 0.46%; 95% CI, –0.84% to 1.76%; P = 0.49), nor for the 2015 guidelines (RD, 1.13%; 95% CI, –0.09% to 2.36%; P = 0.07). Additional details are provided in Figure 2 and Table 3. The results remained largely consistent in the subgroup analyses based on the initial rhythm and only including those who achieved sustained ROSC (Supplementary Figure 1).
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Return of Spontaneous Circulation There were 44,422 (64%) patients with ROSC in the pre-2010 guideline period, 63,515 (71%) patients with ROSC in the post-2010/pre-2015 guideline period, and 53,125 (74%) patients with ROSC in the post2015 guideline period. The annual trend in ROSC was lower for the post-2010 compared to the pre-2010 guideline period (RD, –1.42% per year; 95% CI, –2.06% to –0.77%; P <0.001), but was not statistically
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significantly different for the post-2015 compared to the pre-2015 guideline period (RD, –0.37% per
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year; 95% CI, –1.09% to 0.35%; P = 0.31). The immediate change in ROSC from introducing the
resuscitation guidelines did not reach statistical significance for the 2010 guidelines (RD, –0.64%; 95% CI,
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–2.36% to 1. 08%; P = 0.46), nor the 2015 guidelines (RD, 0.76%; 95% CI, –0.63% to 2.15%; P = 0.29).
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Additional details are provided in Table 3 and Supplementary Figure 2.
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Favorable Neurological Outcome
A total of 218,951 (94%) patients had complete data on neurological outcome. There were 11,065 (16%) patients with a favorable neurological outcome in the pre-2010 guideline period, 13,540 (16%) patients
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in the post-2010/pre-2015 guideline period, and 12 071 (18%) patients in the post-2015 guideline period. The annual trend in favorable neurological outcome was not statistically significantly different for either the post-2010 compared to the pre-2010 guideline period (RD, –0.32% per year; 95% CI, –
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0.98% to 0.34%; P = 0.34) and the pre-2015 compared to the post-2015 guideline period (RD, –0.50% per year; 95% CI, –1.32% to 0.33%; P = 0.24). The immediate change in favorable neurological outcome from introducing the resuscitation guidelines reached statistical significance for the 2010 guidelines (RD, – 3.25%; 95% CI, –5.14% to –1.36%; P <0.001), but did not reach statistical significance for the 2015 guidelines (RD, 0.41%; 95% CI, –1.02% to 1.84%; P = 0.58). Additional details are provided in Table 3 and Supplementary Figure 3.
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Sensitivity Analyses The results remained largely consistent in multiple sensitivity analyses (Supplementary Figure 4–5). There was no evidence of a non-linear trend in survival when including time as polynomial terms in the regression model for the pre-2010 (P = 0.80 for quadratic term; P = 0.45 for cubic term) and the post2010/pre-2015 (P = 0.73 for quadratic term; P = 0.05 for cubic term) guideline period. The analyses
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estimating the optimal number and location of trend segments found a single joint point, identified as
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December 2010 or May 2011 depending on the model assumption, to be the most optimal model for
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the time series (Supplementary Figure 6–7 and Supplementary Table 1).
Discussion
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In this study, we used a large United States-based in-hospital cardiac arrest registry to examine whether
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the introduction of the 2010 and 2015 resuscitation guidelines were associated with a change in survival. We found that the annual trend in survival was significantly lower for the post-2010 compared to the pre-2010 guideline period, as well as for the post-2015 compared to the pre-2015 guideline
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period. There was no significant immediate change in survival from introducing the 2010 and 2015 guidelines. The results remained relatively consistent in multiple sensitivity analyses. Furthermore, we found that, while outcomes have improved for cardiac arrest from 2006 to 2010, there has been no
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meaningful improvement since 2010.
To our knowledge, only one previous paper from 2017 has studied the association of resuscitation
guidelines on outcomes in adult patients with in-hospital cardiac arrest. 21 The investigators of that study used the National Inpatient Sample, a publicly available administrative billing database in the United States, to search for cases with cardiac arrest from 2007 to 2010 and 2010 to 2014. Survival was found not to be significantly different between the two time periods. In comparison, we found a significant
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lower annual trend in survival following the introduction of the 2010 guidelines compared to the pre2010 guideline period. The previous study was based on administrative data which are inherently limited by the current coding system and the absence of detailed clinical information. Specifically, the ICD-9 codes used to search for cardiac arrest in administrative databases have been shown not to be valid for capturing patients with in-hospital cardiac arrest and survival rates from such data have been reported to vary markedly. 22, 23 Although modifications to the structure or data collection apparatus of
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prospective registries could also result in erroneous trends in outcomes, to our knowledge, there were
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no major or sudden modifications to the GWTG-R registry during the study period.
Survival to hospital discharge was found to increase significantly from 2006 to 2010, after which the
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trend in survival plateaued, with no significant increase or decrease in survival from 2011 to 2015 and from 2015 to 2018. Moreover, ROSC was found to increase for a longer time period, from 2006 to 2015,
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before plateauing. The results for the pre-2010 period are consistent with a previous publication from
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the GWTG-R registry1 and similar trends after 2010 have recently been shown in pediatric in-hospital cardiac arrest 24 and in out-of-hospital cardiac arrest 25 . Our overall findings were unexpected and the specific reasons for the observations remain unknown. One possible explanation is that the trends in
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survival were directly related to the updates of the resuscitation guidelines. The 2010 and 2015 guidelines were mainly focused on improving acute resuscitation, including changes to the characteristics of CPR (e.g., compression rate and depth) and advanced intra-cardiac arrest interventions
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(e.g., removal of atropine in 2010 and vasopressin in 2015), as well as the inclusion of post-resuscitation care (e.g., therapeutic hypothermia) as a fifth link in the chain of survival (Table 1). However, the increase in ROSC was not coupled to an increase in survival to hospital discharge, despite an anticipated benefit of these updates. Certain recommendations could conceivably have been counterproductive or not effective.
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There is generally very low level of evidence to support therapies for this patient population and the majority of treatment recommendation for patients with in-hospital cardiac arrest are based on observational data or extrapolated from the out-of-hospital cardiac arrest population. 2, 3 Because inhospital cardiac arrest has received relatively little attention, a more plausible explanation for our results could be that we have reached a saturation in our current understanding and treatment of cardiac arrest, such that the trends in survival may have reached a plateau independently of the
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guidelines. This hypothesis is partly supported by our finding of no significant immediate change in
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survival from introducing the guidelines, our sensitivity analysis demonstrating that the trend in survival remained unchanged from the post-2010/pre-2015 to the post-2015 period in hospitals providing data
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to the GWTG-R registry within the entire study period, and the Joint Point regression analysis identifying no joint point in 2015. In general, well-powered randomized clinical trials addressing in-hospital cardiac
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arrest are rare. 26 A recent study found that only 6% of randomized trials addressing post-cardiac arrest
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interventions, published between 1995 and 2019, were specifically conducted in patients with inhospital cardiac arrest. 27 New interventions, quality improvement measures, and dedicated research targeting in-hospital cardiac arrest as a unique disease entity may be necessary to improve outcomes in
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what is emerging as a substantial public health issue. Additionally, there may be a need to more effectively translate guidelines into clinical practice, as is the initiative of the recent American Heart Association’s Guideline Transformation and Optimization program. Based on recent incidence estimates
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in the United States, our findings can be translated into approximately 250,000 deaths from adult inhospital cardiac arrest in 2017. 28 Our primary findings remained relatively consistent in multiple sensitive analyses, including when
adjusting for multiple patient, cardiac arrest, and hospital characteristics, suggesting that the trends in survival were not related to rapid changes in these factors over time. Thus, our findings may have been related to unmeasured baseline characteristics (e.g., severity of illness) and/or resuscitation practices
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that changed with the implementation of the guidelines. However, our study was not designed to identify what specific factors may have affected outcomes. The results of the Joint Point regression analysis, identifying the optimal joint point as December 2010 or May 2011, is in line with our predefined censored period (November 2010 to March 2011) used for the primary analysis supporting our findings, although the lack of a joint point in 2015 suggests that survival had already reached a plateau at this stage. There was also no meaningful improvement in outcomes since 2010 in our
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subgroup analyses, with no significant differences based on initial rhythm. Although certain changes to
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the guidelines were rhythm-based (Table 1), these subgroup results are consistent with a previous paper finding no association between the guideline removal of atropine in 2010 and survival for patients with a
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non-shockable rhythm. 15
Our results should be interpreted in the context of a number of limitations. First, we were unable to
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determine the specific reason for the plateauing trend in survival and the GWTG-R registry does not
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include sufficient data to know whether resuscitation processes complied with cardiac arrest guidelines. Second, additional data, particularly in the post-2015 guideline period may have provided additional power to detect statistically significant differences between the guideline periods. Third, the
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implementation period of six months may have been too short to detect a difference between the time periods. 29, 30 For example, previous studies from the United States and Europe suggest that only 30–40% of hospitals implemented targeted temperature management within 1–2 years following guideline
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publication. 31-33 We partly addressed this limitation in sensitivity analyses assuming an implementation period of zero and 12 months. Fourth, we had limited detailed information on intra- and post-cardiac arrest interventions and were, therefore, not able to describe changes occurring over time for these characteristics. Lastly, the majority of patients with incomplete data on favorable neurological outcome had a cardiac arrest after 2010, which makes the results for this outcome and the observed decrease following the 2010 guidelines, difficult to interpret.
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Conclusions We found no evidence to support an association of guideline publication with overall improvement in survival from in-hospital cardiac arrest. Survival to hospital discharge increased from 2006 to 2010, after which the trend in survival plateaued. The annual trend in survival was significantly lower following publication of the 2010 and 2015 CPR and ECC guidelines. A continued clinical focus, new interventions,
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and dedicated research targeting adult in-hospital cardiac arrest as a unique disease entity may be
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necessary to improve outcomes in this patient population.
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Get With The Guidelines® – Resuscitation Investigators Besides the author Saket Girotra, M.D., S.M., members of the Get With The Guidelines®-Resuscitation Adult Research Task Force include:
Paul Chan, M.D., M.Sc., Ari Moskowitz, M.D., Anne V. Grossestreuer, Ph.D., Dana Edelson, M.D., M.S., Joseph Ornato, M.D., Katherine Berg, M.D., Mary Ann Peberdy, M.D., Matthew Churpek, M.D., M.P.H.,
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Ph.D., Michael Kurz, M.D., M.S.-H.E.S., Monique Anderson Starks, M.D., M.H.S., Sarah Perman, M.D.,
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M.S.C.E., and Zachary Goldberger, M.D., M.S.
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Credit Author Statement
Mathias J. Holmberg and Lars W. Andersen were responsible for the data acquisition, performed the
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statistical analyses, and drafted the manuscript. All authors contributed to the design of the study,
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interpreted the results, and critically revised the manuscript. All authors approved the final manuscript as submitted and agrees to be accountable for all aspects of the submitted work.
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Conflicts of Interest
There was no specific funding for this study. Dr. Donnino is supported by grants 5K24HL127101-04 and 5R01HL136705-03 from the National Heart, Lung, and Blood Institute.
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Lars W. Andersen and Michael Donnino are compensated by the American Heart Association (AHA) through the International Liason Commmitee on Resuscitation (ILCOR) for work related to systematic reviews used for guideline development. Lars W. Andersen serves as a statistical reviewer for JAMA. There are otherwise no disclosures.
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Acknowledgements Mathias J. Holmberg and Lars W. Andersen were responsible for the data acquisition, performed the statistical analyses, and drafted the manuscript. All authors contributed to the design of the study, interpreted the results, and critically revised the manuscript. All authors approved the final manuscript as submitted and agrees to be accountable for all aspects of the submitted work. We thank Dr. Garrett Fitzmaurice, Sc.D. (Department of Biostatistics, Harvard T.H. Chan School of
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Public Health, Boston, MA, USA) for providing statistical advice.
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Epidemiol. Aug 2005;162(3):199-200. doi:10.1093/aje/kwi188 15.Holmberg MJ, Moskowitz A, Wiberg S, et al. Guideline removal of atropine and survival after adult inhospital cardiac arrest with a non-shockable rhythm. Resuscitation. Apr 2019;137:69-77. doi:10.1016/j.resuscitation.2019.02.002
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16.Hu FB, Goldberg J, Hedeker D, Flay BR, Pentz MA. Comparison of population-averaged and subjectspecific approaches for analyzing repeated binary outcomes. Am J Epidemiol. Apr 1998;147(7):694703. doi:10.1093/oxfordjournals.aje.a009511 17.Hubbard AE, Ahern J, Fleischer NL, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology. Jul 2010;21(4):467-74. doi:10.1097/EDE.0b013e3181caeb90
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18.Joinpoint Regression Program. Version Version 4.7.0.0. Statistical Methodology and Application
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Branch, Surveillance Research Program, National Cancer Institute; February 2019.
19.Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications
0258(20000215)19:3<335::aid-sim336>3.0.co;2-z
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to cancer rates. Stat Med. Feb 2000;19(3):335-51. doi:10.1002/(sici)1097-
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20.Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. Jan 1990;1(1):43-6.
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21.Mallikethi-Reddy S, Akintoye E, Rubenfire M, Briasoulis A, Grines CL, Afonso L. Nationwide survival after inhospital cardiac arrest before and after 2010 cardiopulmonary resuscitation guidelines: 20072014. Int J Cardiol. Dec 2017;249:231-233. doi:10.1016/j.ijcard.2017.09.199
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22.Khera R, Spertus JA, Starks MA, et al. Administrative Codes for Capturing In-Hospital Cardiac Arrest. JAMA Cardiol. Nov 2017;2(11):1275-1277. doi:10.1001/jamacardio.2017.2904 23.DeZorzi C, Boyle B, Qazi A, et al. Administrative Billing Codes for Identifying Patients With
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Cardiac Arrest. J Am Coll Cardiol. Apr 2019;73(12):1598-1600. doi:10.1016/j.jacc.2019.01.030 24.Holmberg MJ, Wiberg S, Ross CE, et al. Trends in Survival After Pediatric In-Hospital Cardiac Arrest in the United States. Circulation. Oct 2019;140(17):1398-1408. doi:10.1161/CIRCULATIONAHA.119.041667
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25.Granfeldt A, Holmberg MJ, Donnino MW, Andersen LW, Group CS. 2015 Guidelines for Cardiopulmonary Resuscitation and Survival after Adult and Pediatric Out-of-Hospital Cardiac Arrest. Eur Heart J Qual Care Clin Outcomes. Mar 2020;doi:10.1093/ehjqcco/qcaa027 26.Andersen LW, Holmberg MJ, Berg KM, Donnino MW, Granfeldt A. In-Hospital Cardiac Arrest: A Review. JAMA. Mar 2019;321(12):1200-1210. doi:10.1001/jama.2019.1696 27.Andersen LW, Lind PC, Vammen L, Hoybye M, Holmberg MJ, Granfeldt A. Adult Post-Cardiac Arrest
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Interventions: A Scoping Review of Randomized Clinical Trials. Submitted to Resuscitation. 2019;
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28.Holmberg M, Ross C, Fitzmaurice G, et al. Annual Incidence of Adult and Pediatric In-Hospital Cardiac Arrest in the United States. Circulation: Cardiovascular Quality and Outcomes. 2019;
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29.Bigham BL, Koprowicz K, Aufderheide TP, et al. Delayed prehospital implementation of the 2005 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiac
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care. Prehosp Emerg Care. Jul-Sep 2010;14(3):355-60. doi:10.3109/10903121003770639
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30.Berdowski J, Schmohl A, Tijssen JG, Koster RW. Time needed for a regional emergency medical system to implement resuscitation Guidelines 2005--The Netherlands experience. Resuscitation. Dec 2009;80(12):1336-41. doi:10.1016/j.resuscitation.2009.08.011
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31.Laver SR, Padkin A, Atalla A, Nolan JP. Therapeutic hypothermia after cardiac arrest: a survey of practice in intensive care units in the United Kingdom. Anaesthesia. Sep 2006;61(9):873-7. doi:10.1111/j.1365-2044.2006.04552.x
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32.Merchant RM, Soar J, Skrifvars MB, et al. Therapeutic hypothermia utilization among physicians after resuscitation from cardiac arrest. Crit Care Med. Jul 2006;34(7):1935-40. doi:10.1097/01.CCM.0000220494.90290.92
33.Sander M, von Heymann C, Spies C. Implementing the International Liaison Committee on Resuscitation guidelines on hypothermia after cardiac arrest. The German experience: still a long way to go? Crit Care. 2006;10(2):407. doi:10.1186/cc4882
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34.Andersen LW, Granfeldt A, Callaway CW, et al. Association Between Tracheal Intubation During Adult In-Hospital Cardiac Arrest and Survival. JAMA. 02 2017;317(5):494-506.
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doi:10.1001/jama.2016.20165
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Figures and Tables 308,885 Adult in-hospital cardiac arrests between May 2006 and December 2018
57,371
Excluded 54,969 Non-index events 2402 Missing data on primary outcome
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Censored 7149 2010 guideline analysis 12,626 2015 guideline analysis
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231,739 In-hospital cardiac arrests included for the primary analyses
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19,775
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251,514 In-hospital cardiac arrests meeting all inclusion and exclusion criteria
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Figure 1. Inclusion and exclusion criteria for the primary analysis. Between May 2006 and December 2018, 308,885 adult in-hospital cardiac arrests were registered in the
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Get With The Guidelines® – Resuscitation registry. A total of 251,514 patients met all the inclusion and
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none of the exclusion criteria, of which 231,739 patients were included for the primary analyses.
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Figure 2. Interrupted time series for survival to hospital discharge
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The open circles represent survival per quarter. The solid lines represent the estimated trend in survival
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and 2015 resuscitation guidelines.
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over time with 95% confidence intervals. The dashed vertical lines represent the publication of the 2010
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Table 1. Key changes to the American Heart Association guidelines 2005 Guidelines
2010 Guidelines
2015 Guidelines
Approach
Airway-Breathing-Circulation
Circulation-Airway-Breathing
No change
Depth
1½–2 inches
At least 2 inches
At least 2 inches while avoiding excessive depth
Compression
100/min
At least 100/min
100/min to 120/min
Algorithm
High-quality CPR assumed provided
Simplified to emphasize highquality CPR
No change
Basic Life Support
Advanced Cardiac Life Support May replace 1st/2nd dose of epinephrine
No change
No advantages as a substitute to epinephrine
Epinephrine
Not stratified by rhythm
No change
As soon as possible for nonshockable rhythms
Amiodarone and Lidocaine
Amiodarone or lidocaine acceptable for refractory VF
Amiodarone is the first-line agent; lidocaine may be considered if unavailable
Atropine
Included as a treatment for PEA Excluded as a treatment for PEA No change and asystole and asystole
Intubation
Confirm placement with exhaled CO2 detector
ECPR
Not included
Approach
Not included
Angiography
Not included
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Amiodarone or lidocaine acceptable for refractory VF/pVT
Ultrasound added as option to confirm placement
Not included
Consider ECPR in select patients with refractory cardiac arrest
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Confirm placement with waveform capnography
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Post-resuscitation care
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Vasopressin
Added as fifth link in the chain of survival
No change
Recommended for patients with Recommended for patients with myocardial infarction cardiac etiology
32–34C for 12–24 hours for comatose victims with VF/nonVF
32–34C for 12–24 hours for all comatose victims
32–36C for 24 hours for all comatose victims
Oxygenation
Not included
Titration to oxygen saturation 94%
No change
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Hypothermia
Page 25 of 31
Table 2. Patient, event, and hospital characteristics Pre-2010 a
2010-2015 b
Post-2015 c
SD
SD
(N = 70 016)
(N = 89 782)
(N = 71 941)
2010 d
2015 e
67 (55, 78)
67 (56, 77)
67 (56, 76)
–0.02
–0.01
Male
40 625 (58)
52 154 (58)
42 035 (58)
<0.01
0.01
Female
29 390 (42)
37 612 (42)
29 895 (42)
<0.01
–0.01
Cardiac
23 203 (33)
32 782 (37)
Non-cardiac
31 435 (45)
37 887 (42)
Cardiac
4624 (7)
5848 (7)
Non-cardiac f
8280 (12) 2384 (3)
Demographics Age (median, IQR)
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Sex
Illness category
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Medical
0.07
0.02
30 967 (43)
–0.05
0.02
4250 (6)
<0.01
–0.03
9706 (11)
6943 (10)
–0.03
–0.04
3265 (4)
2625 (4)
0.01
<0.01
11 492 (16)
13 320 (15)
10 153 (14)
–0.04
–0.02
Heart failure prior admission
13 343 (19)
18 736 (21)
16 372 (23)
0.05
0.04
MI this admission
10 835 (16)
12 269 (14)
10 045 (14)
–0.05
0.01
MI prior admission
10 177 (15)
11 864 (13)
9600 (13)
–0.04
<0.01
Acute CNS non-stroke event
5080 (7)
5518 (6)
6339 (9)
–0.04
0.10
Baseline depression in CNS function
8303 (12)
7227 (8)
5431 (8)
–0.13
–0.02
Diabetes mellitus
21 395 (31)
28 734 (32)
25 000 (35)
0.03
0.06
Hepatic insufficiency
5176 (7)
6337 (7)
6395 (9)
–0.01
0.07
Hypotension
18 776 (27)
20 622 (23)
19 942 (28)
–0.09
0.11
Major trauma
3055 (4)
4150 (5)
3812 (5)
0.01
0.03
Pre-existing conditionsg Cardiac
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Heart failure this admission
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Trauma
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Surgical
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26 977 (38)
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Non-cardiac
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Metabolic or electrolyte abnormality
10 462 (15)
15 714 (18)
18 244 (25)
0.07
0.19
Metastatic or hematologic malignancy
8732 (12)
10 038 (11)
7630 (11)
–0.04
–0.02
Pneumonia
9376 (13)
12 089 (14)
9930 (14)
<0.01
0.01
Renal insufficiency
23 282 (33)
30 915 (35)
25 704 (36)
0.03
0.02
Respiratory insufficiency
29 145 (42)
38 277 (43)
33847 (47)
0.02
0.09
Septicemia
11 777 (17)
15 086 (17)
11 055 (15)
<0.01
–0.04
Emergency Department
7142 (10)
10 241 (11)
9819 (14)
0.04
0.07
Intensive Care Unit
33 992 (49)
43 358 (48)
33 783 (47)
–0.01
–0.03
Without telemetry
12 053 (17)
14 049 (16)
–0.04
<0.01
With telemetry
10 941 (16)
13 625 (15)
10 323 (14)
–0.01
–0.02
Otherh
5855 (8)
8432 (9)
6796 (9)
0.04
<0.01
27 631 (31)
21 983 (31)
<0.01
–0.01
48 484 (69)
62 151 (69)
49 958 (69)
<0.01
<0.01
22 159 (32)
27 166 (31)
21 633 (30)
–0.03
<0.01
47 132 (68)
61 819 (69)
49 384 (70)
0.03
–0.01
58 369 (83)
78 184 (87)
63 431 (88)
0.11
0.03
11 646 (17)
11 548 (13)
8481 (12)
–0.11
–0.03
Yes
60 234 (86)
76 576 (85)
60 752 (85)
–0.02
–0.02
No
9781 (14)
13 169 (15)
11 032 (15)
0.02
0.02
19 072 (27)
19 410 (22)
19 206 (27)
–0.13
0.12
Location and Time of Event
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Time of weeki
21 532 (31)
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Weekend Weekday Time of dayj
Daytime
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Nighttime
ro 11 173 (16)
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Floor
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Location
Arrest Characteristics Witnessed Yes
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No
Monitored
Interventions in place at arrest Vasoactive agents k
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Mechanical ventilation
26 912 (38)
36 377 (41)
34 047 (47)
0.04
0.14
Intra-arterial catheter
7812 (11)
9411 (10)
7324 (10)
–0.02
–0.01
Asystole
22 269 (34)
23 214 (29)
16 525 (25)
–0.13
–0.07
Pulseless electrical activity
30 334 (47)
44 015 (54)
37 539 (58)
0.12
0.06
Pulseless ventricular tachycardia
5051 (8)
6052 (7)
4953 (8)
–0.02
0.01
Ventricular fibrillation
7363 (11)
7879 (10)
5952 (9)
–0.06
–0.02
Major
23 884 (35)
31 252 (37)
23 494 (35)
Minor
35 029 (51)
44 613 (52)
Non-teaching
9509 (14)
9520 (11)
Military
1506 (2)
825 (1)
Non-profit
49 351 (76)
Government
4982 (8)
Initial rhythm
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Hospital characteristics Teaching status
–0.05
35 327 (53)
–0.01
–0.01
8377 (12)
–0.09
0.03
338 (1)
–0.10
–0.05
62 940 (77)
50 005 (79)
–0.01
–0.01
9409 (11)
7162 (11)
0.12
–0.02
8681 (13)
8902 (11)
5464 (9)
–0.08
–0.08
66 281 (100)
84 041 (100)
66 103 (100)
–0.05
–0.07
33 (<1)
83 (<1)
152 (<1)
0.02
0.03
9161 (13)
15 510 (18)
11 108 (17)
0.12
–0.05
19 683 (29)
22 418 (26)
16 994 (25)
–0.07
–0.03
North-Central
14 203 (21)
17 725 (21)
14 096 (21)
–0.01
<0.01
South-Central
14 199 (21)
18 116 (21)
14 050 (21)
<0.01
–0.02
West
11 301 (16)
11 922 (14)
10 950 (16)
–0.08
0.06
1 – 249
11 981 (18)
12 868 (15)
10 611 (16)
–0.08
0.01
250 – 499
27 166 (40)
34 264 (40)
25 982 (39)
–0.01
–0.04
Hospital location
Rural
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Urban
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Private
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Ownership
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0.02
Geographic location North-East
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South-East
Number of hospital beds
Page 28 of 31
>500
28 193 (42)
37 780 (44)
29 939 (45)
0.04
–0.01
Abbreviations: SD, standardized difference; IQR, interquartile range; MI, myocardial infarction; CNS, central nervous system. Standardized differences “<0.01” represent values >–0.01 and <0.01. a Defined as
the time from May 1, 2006 to October 31, 2010
b Defined as
the time from May 1, 2011 to October 31, 2015
c
Defined as the time from May 1, 2016 to December 31, 2018 between the pre -2010 and post-2010 period
e Standardized difference
between the pre -2015 and post-2015 period
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d Standardized difference
Includes patients with an obstetric admission have been provided elsewhere 34
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g Definitions
h Ambulatory and outpatient areas, delivery suite, rehabilitation facility, skilled nursing
facility, mental health facility, same-day
to 7:00am to 10:59pm, Night refers to 11:00pm to 6:59am
j Weekday refers k Continuous
to Monday 7:00am to Friday 10:59pm, Weeken d refers to Friday 11:00pm to Monday 6:59am
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i Day refers
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surgical area, operating room, post-anesthesia recovery room, or interventional unit
infusion of dobutamine, dopamine > 3 mcg/kg/min, epinephrine, nitroglycerin, norepinephrine, phenylephrine,
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vasopressin, or other vasoactive agents
Page 29 of 31
Table 3. Interrupted time series model Risk differences
Relative risk P-value
(95% CI)
P-value (95% CI)
Survival to hospital discharge Trends 1.09% (0.74, 1.43)
<0.001
1.05 (1.04, 1.07)
<0.001
Post-2010/pre-2015 slope
0.26% (–0.11, 0.64)
0.17
1.01 (1.00, 1.03)
0.17
Post-2015 slope
–0.43% (–0.96, 0.11)
0.12
0.98 (0.96, 1.00)
0.11
Pre-post 2010 slope difference
–0.82% (–1.35, –0.30)
0.002
0.96 (0.94, 0.98)
Pre-post 2015 slope difference
–0.69% (–1.33, –0.04)
0.04
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Pre-2010 slope
0.46% (–0.84, 1.76)
2015 guideline level change
1.13% (–0.09, 2.36)
Return of spontaneous circulation
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Trends Pre-2010 slope
<0.001 0.03
0.49
1.02 (0.96, 1.07)
0.59
0.07
1.04 (1.00, 1.09)
0.07
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2010 guideline level change
0.97 (0.95, 1.00)
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Immediate change
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Difference in trends
2.25% (1.76, 2.74)
<0.001
1.04 (1.03, 1.04)
<0.001
0.83% (0.41, 1.26)
<0.001
1.01 (1.01, 1.02)
<0.001
0.47% (–0.11, 1.04)
0.11
1.01 (1.00, 1.01)
0.11
Pre-post 2010 slope difference
–1.42% (–2.06, –0.77)
<0.001
0.98 (0.97, 0.99)
<0.001
Pre-post 2015 slope difference
–0.37% (–1.09, 0.35)
0.31
0.99 (0.98, 1.00)
0.27
2010 guideline level change
–0.64% (–2.36, 1.08)
0.46
0.99 (0.96, 1.01)
0.36
2015 guideline level change
0.76% (–0.63, 2.15)
0.29
1.01 (0.99, 1.03)
0.31
Pre-2010 slope
0.86% (0.47, 1.24)
<0.001
1.05 (1.03, 1.08)
<0.001
Post-2010/pre-2015 slope
0.54% (0.03, 1.05)
0.04
1.03 (1.00, 1.07)
0.04
Post-2010/pre-2015 slope
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Post-2015 slope
Difference in trends
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Immediate change
Favorable neurological outcome Trends
Page 30 of 31
Post-2015 slope
0.04% (–0.61, 0.70)
0.90
1.00 (0.97, 1.04)
0.90
Pre-post 2010 slope difference
–0.32% (–0.98, 0.34)
0.34
0.98 (0.94, 1.02)
0.33
Pre-post 2015 slope difference
–0.50% (–1.32, 0.33)
0.24
0.97 (0.93, 1.02)
0.21
2010 guideline level change
–3.25% (–5.14, –1.36)
<0.001
0.82 (0.73, 0.92)
0.001
2015 guideline level change
0.41% (–1.02, 1.84)
0.58
1.02 (0.94, 1.11)
0.60
Difference in trends
Immediate change
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Pre-slope refers to the annual trend in survival prior to introducing the 2010 and 2015 resuscitation guidelines. Post-slope refers to the annual trend in survival after introducing the 2010 and 2015 resuscitation guidelines. Level change refers to the
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immediate change in survival after introducing the guidelines . Pre-post slope difference refers to the difference in survival
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trend from the pre-guideline to post-guideline period.
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PII:
S0300-9572(20)30529-3
DOI:
https://doi.org/10.1016/j.resuscitation.2020.10.022
Reference:
RESUS 8750
To appear in:
Resuscitation
Received Date:
3 September 2020
Revised Date:
27 September 2020
Accepted Date:
16 October 2020
Please cite this article as: Holmberg MJ, Granfeldt A, Girotra S, Donnino MW, Andersen LW, Chan P, Moskowitz A, Grossestreuer AV, Edelson D, Ornato J, Berg K, Peberdy MA, Churpek M, Kurz M, Starks MA, Perman S, Goldberger Z, Trends in Survival and Introduction of the 2010 and 2015 Guidelines for Adult In-Hospital Cardiac Arrest, Resuscitation (2020), doi: https://doi.org/10.1016/j.resuscitation.2020.10.022
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2020 Published by Elsevier.
Trends in Survival and Introduction of the 2010 and 2015 Guidelines for Adult In-Hospital Cardiac Arrest Authors Mathias J. Holmberg, M.D., M.P.H., Ph.D. 1,2,3 , Asger Granfeldt, M.D., Ph.D., D.M.Sc.4,5, Saket Girotra, M.D., S.M. 6 , Michael W. Donnino, M.D. 2,7 , and Lars W. Andersen, M.D., M.P.H., Ph.D., D.M.Sc. 1,2,8,9, for
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the American Heart Association’s Get With The Guidelines®-Resuscitation Investigators*
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* The members of the Get With The Guidelines®-Resuscitation Adult Research Task Force are listed at
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the end of the article
1
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Affiliations
Research Center for Emergency Medicine, Department of Clinical Medicine, Aarhus University and
2 Center for
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Aarhus University Hospital, Aarhus, Denmark
Resuscitation Science, Department of Emergency Medicine, Beth Israel Deaconess Medical
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Center, Boston, MA, USA 3 Department of Cardiology,
Viborg Regional Hospital, Viborg, Denmark
Department of Intensive Care Medicine, Randers Regional Hospital, Randers, Denmark
5
Department of Intensive Care Medicine, Aarhus University Hospital, Aarhus, Denmark
6
Carver College of Medicine, University of Iowa, Iowa City, IA, USA
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4
7
Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Beth Israel
Deaconess Medical Center, Boston, MA, USA 8
Prehospital Emergency Medical Services, Central Denmark Region, Denmark
9
Department of Anesthesiology and Intensive Care, Aarhus University Hospital, Aarhus, Denmark
Page 1 of 31
Corresponding Author Lars W. Andersen M.D., M.P.H., Ph.D., D.M.Sc. Research Center for Emergency Medicine Department of Clinical Medicine Aarhus University and Aarhus University Hospital Phone: +45 51 78 15 11
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Email: [email protected]
Word Count Abstract: 238
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Word Count Manuscript: 3157 Figures and Tables: 5
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References: 34
Page 2 of 31
Abstract Aims To examine trends in survival from 2006 to 2018 and to assess whether the introduction of resuscitation guidelines was associated with a change in survival after adult in-hospital cardiac arrest.
Methods
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Using the Get With The Guidelines® – Resuscitation registry, we included adult patients with an in-
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hospital cardiac arrest between 2006 and 2018. The primary outcome was survival to hospital discharge. An interrupted time series analysis was used to compare survival before and after publication of the
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2010 and 2015 resuscitation guidelines.
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Results
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The analysis included 231,739 patients. Survival changed annually by 1.09% (95% CI, 0.74% to 1.43%; P <0.001) from 2006 to 2010, 0.26% (95% CI, –0.11% to 0.64%; P = 0.17) from 2011 to 2015, and –0.43% (95% CI, –0.96% to 0.11%; P = 0.12) from 2016 to 2018. The survival trend was lower within the post-
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2010 compared to the pre-2010 period (risk difference, –0.82% per year; 95% CI, –1.35% to –0.30%; P = 0.002) and within the post-2015 compared to the pre-2015 period (risk difference, –0.69% per year; 95% CI, –1.33% to –0.04%; P = 0.04). There was no immediate change in survival after publication of the 2010
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and 2015 guidelines.
Conclusions
In-hospital cardiac arrest survival increased from 2006 to 2010, after which the trend plateaued. The annual survival trend was lower following publication of the 2010 and 2015 guidelines. Research targeting in-hospital cardiac arrest as a unique entity may be necessary to improve outcomes.
Page 3 of 31
Keywords: Heart Arrest, Cardiopulmonary Resuscitation, Resuscitation, Mortality, Guidelines,
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Interrupted Time Series
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Introduction The most recent comprehensive report on trends in survival from in-hospital cardiac arrest in the United States was published in 2012, showing an increase in survival from 14% in 2000 to 22% in 2009. 1 The American Heart Association has since revised the Guidelines for Cardiopulmonary Resuscitation (CPR) and Emergency Cardiovascular Care (ECC) in 2010 and 2015, including an emphasis on quality of CPR, revisions to the use of cardiac arrest medications, and revisions to post-resuscitation care (Table 1). 2, 3
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However, the association between the 2010 and 2015 resuscitation guidelines and survival from cardiac
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arrest in hospitalized patients has not been well-studied. Additionally, no large study has reported on trends in survival using contemporary data. 1
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In this study, we leveraged the Get With The Guidelines® – Resuscitation (GWTG-R) registry to examine trends in survival from 2006 to 2018 and to assess whether the introduction of the 2010 and
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2015 resuscitation guidelines were associated with a change in survival after adult in-hospital cardiac
Methods
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Study Design and Data Source
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arrest.
This study was an analysis of data from the GWTG-R registry. The GWTG-R registry is a United Statesbased quality-improvement registry of in-hospital cardiac arrest patients, sponsored by the American
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Heart Association. In the GWTG-R registry, cardiac arrest is defined as the presence of no central pulse requiring chest compressions, defibrillation, or both, with a hospital-wide or unit-based emergency response by acute care personnel. Data are collected at each participating site on all in-hospital cardiac arrests without a do-not-resuscitate order. The design, data collection, and reliability of the registry has been described in detail elsewhere. 4, 5 Hospital-level data were obtained from the 2018 American
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Hospital Association Annual Survey6 and linked to the GWTG-R registry by the American Heart Association data management vendor. IQVIA is the data collection coordination center for the American Heart Association and American Stroke Association GWTG programs. Because data were used primarily at the local site for quality improvement, sites were granted a waiver of informed consent under the common rule. The Institutional Review Board at Beth Israel Deaconess Medical Center (Boston, MA, USA) determined that
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research involving the GWTG-R registry does not meet the federal definition of human subject research.
Study Population, Exposure, and Outcomes
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We included adult patients ( 18 years of age) with an index in-hospital cardiac arrest between January 1st, 2006 and December 31st, 2018. Patients with missing data on survival to hospital discharge were
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excluded.
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The exposure of interest was the introduction of the CPR and ECC guidelines, published on November 2nd, 2010 and November 3rd, 2015 by the American Heart Association. 2, 3 The primary outcome was survival to hospital discharge. Secondary outcomes included sustained
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return of spontaneous circulation (ROSC) and survival to hospital discharge with a favorable neurological outcome. Sustained ROSC was defined as the presence of a pulse and no further need for chest compressions for at least 20 minutes. Neurological outcome was measured by the Cerebral Performance
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Category (CPC) score, with a CPC score of 1 or 2 signifying a favorable neurological outcome and a CPC score from 3 to 5 signifying an unfavorable neurological outcome. 7
Statistical Analysis Continuous data are presented as medians with first and third quartiles. Categorical data are presented
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as counts with frequencies. Differences in patient characteristics are reported using standardized differences. To examine whether the introduction of the 2010 and 2015 resuscitation guidelines were associated with a change in survival after adult in-hospital cardiac arrest, we performed an interrupted time series analysis by comparing trends in survival before and after introducing the guidelines. The study period was divided into pre-guideline and post-guideline segments based on the time of
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guideline publication. 2, 3 The pre-2010 guideline period was defined as the time from May 1st, 2006 to
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October 31st, 2010, the post-2010/pre-2015 guideline period was defined as the time from May 1st, 2011 to October 31st, 2015, and the post-2015 guideline period was defined as the time from May 1st, 2016 to
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December 31st, 2018. Since guidelines require implementation before any impact on survival may be
censored from the primary analyses.
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observed, the time period between the pre-guideline and post-guideline segments (six months) were
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The interrupted time series analysis involved fitting a regression model with separate intercept and slopes for each of the time segments. 8-11 The exposure of interest (the introduction of the 2010 and 2015 guidelines) acted as boundaries between the segments. The exposure association was estimated
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by comparing the survival intercept and slope for the post-guideline segment to the existing trends in the pre-guideline segment. A positive difference indicates a beneficial association and a negative difference indicates an unfavorable association between the guidelines and the outcome.
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We developed generalized linear models (GLM) using a modified Poisson regression approach (log link function)12, 13 and linear regression (identity link function)14 , respectively, to estimate the relative and absolute change in intercept and slope from the pre-guideline to post-guideline periods. Generalized estimating equations (GEE) were used to account for clustering of patients within hospitals. Primary results are reported as unadjusted relative risks (RR) and risk differences (RD) with 95% confidence intervals. These analyses were repeated for the secondary outcomes.
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We performed two prespecified subgroup analyses for the primary outcome based on the initial rhythm (shockable or non-shockable rhythm) and by only including patients who achieved sustained ROSC. We also performed five predefined sensitivity analyses. First, patient demographics (age categorized in 5-year bins and sex) were included in the primary model to obtain partly risk-adjusted estimates. Second, although the interrupted time series analysis implicitly accounts for potential confounding 8-11, 15 ,
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we repeated the analysis while adjusting for all patient, event, and hospital characteristics outlined in
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Table 2. Third, we repeated the interrupted time series analysis within a hierarchical regression
framework by estimating changes in intercept and slope from the pre-guideline to the post-guideline
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periods for each hospital. 16, 17 Additional details are provided in the Supplementary Methods. Fourth, we repeated the analysis only including events from hospitals reporting at least one cardiac arrest per year
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to the GWTG-R registry for the full study period (from 2006 to 2015 for the 2010 analysis and from 2011
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to 2018 for the 2015 analysis). Fifth, we accounted for various guideline implementation periods by repeating the analysis without any censored period and a censored period of 12 months. Two post-hoc sensitivity analyses were conducted to assess whether survival trends may have
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changed independently of the introduction of the resuscitation guidelines. First, we tested whether survival to hospital discharge followed a non-linear trend by adding time as quadratic and cubic terms to the pre-2010 and post-2010/pre-2015 segment of the model. Second, we estimated the optimal number
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and location of trend segments using Joinpoint (version 4.7.0.0) statistical software (National Cancer Institute). 18, 19 Additional details are provided in the Supplementary Methods. All analyses were two-sided, with a significance level of P <0.05. There was no adjustment for
multiple comparisons. 20 SAS version 9.4 (SAS Institute, Cary, NC, USA) was used for all analyses, unless otherwise specified.
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Results Patient Characteristics The study population included 70,016 patients in the pre-2010 guideline period (2006 to 2010), 89,782 patients in the post-2010/pre-2015 guideline period (2011 to 2015), and 71,941 patients in the post2015 guideline period (2016 to 2018) (Figure 1). The median age was 67 (56, 77) years, 146,400 (58%) patients were male, and 188,624 (82%) patients presented with an initial non-shockable rhythm in the
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full cohort (Table 2).
Survival to Hospital Discharge
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There were 15,114 (22%) survivors in the pre-2010 guideline period, 22,633 (25%) survivors in the post2010/pre-2015 guideline period, and 18,933 (26%) survivors in the post-2015 guideline period. There
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was an increase in survival within the pre-2010 guideline period (RD, 1.09% per year; 95% CI, 0.74% to
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1.43%; P <0.001). However, there was no statistically significant change in survival within the post2010/pre-2015 guideline period (RD, 0.26% per year; 95% CI, –0.11% to 0.64%; P = 0.17) and the post2015 guideline period (RD, –0.43% per year; 95% CI, –0.96% to 0.11%; P = 0.12).
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The annual trend in survival was lower within the post-2010 compared to the pre-2010 guideline period (RD, –0.82% per year; 95% CI, –1.35% to –0.30%; P = 0.02), as well as within the post-2015 compared to the pre-2015 guideline period (RD, –0.69% per year; 95% CI, –1.33% to –0.04%; P = 0.04).
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The immediate change in survival from introducing the resuscitation guidelines did not reach statistical significance for the 2010 guidelines (RD, 0.46%; 95% CI, –0.84% to 1.76%; P = 0.49), nor for the 2015 guidelines (RD, 1.13%; 95% CI, –0.09% to 2.36%; P = 0.07). Additional details are provided in Figure 2 and Table 3. The results remained largely consistent in the subgroup analyses based on the initial rhythm and only including those who achieved sustained ROSC (Supplementary Figure 1).
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Return of Spontaneous Circulation There were 44,422 (64%) patients with ROSC in the pre-2010 guideline period, 63,515 (71%) patients with ROSC in the post-2010/pre-2015 guideline period, and 53,125 (74%) patients with ROSC in the post2015 guideline period. The annual trend in ROSC was lower for the post-2010 compared to the pre-2010 guideline period (RD, –1.42% per year; 95% CI, –2.06% to –0.77%; P <0.001), but was not statistically
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significantly different for the post-2015 compared to the pre-2015 guideline period (RD, –0.37% per
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year; 95% CI, –1.09% to 0.35%; P = 0.31). The immediate change in ROSC from introducing the
resuscitation guidelines did not reach statistical significance for the 2010 guidelines (RD, –0.64%; 95% CI,
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–2.36% to 1. 08%; P = 0.46), nor the 2015 guidelines (RD, 0.76%; 95% CI, –0.63% to 2.15%; P = 0.29).
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Additional details are provided in Table 3 and Supplementary Figure 2.
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Favorable Neurological Outcome
A total of 218,951 (94%) patients had complete data on neurological outcome. There were 11,065 (16%) patients with a favorable neurological outcome in the pre-2010 guideline period, 13,540 (16%) patients
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in the post-2010/pre-2015 guideline period, and 12 071 (18%) patients in the post-2015 guideline period. The annual trend in favorable neurological outcome was not statistically significantly different for either the post-2010 compared to the pre-2010 guideline period (RD, –0.32% per year; 95% CI, –
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0.98% to 0.34%; P = 0.34) and the pre-2015 compared to the post-2015 guideline period (RD, –0.50% per year; 95% CI, –1.32% to 0.33%; P = 0.24). The immediate change in favorable neurological outcome from introducing the resuscitation guidelines reached statistical significance for the 2010 guidelines (RD, – 3.25%; 95% CI, –5.14% to –1.36%; P <0.001), but did not reach statistical significance for the 2015 guidelines (RD, 0.41%; 95% CI, –1.02% to 1.84%; P = 0.58). Additional details are provided in Table 3 and Supplementary Figure 3.
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Sensitivity Analyses The results remained largely consistent in multiple sensitivity analyses (Supplementary Figure 4–5). There was no evidence of a non-linear trend in survival when including time as polynomial terms in the regression model for the pre-2010 (P = 0.80 for quadratic term; P = 0.45 for cubic term) and the post2010/pre-2015 (P = 0.73 for quadratic term; P = 0.05 for cubic term) guideline period. The analyses
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estimating the optimal number and location of trend segments found a single joint point, identified as
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December 2010 or May 2011 depending on the model assumption, to be the most optimal model for
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the time series (Supplementary Figure 6–7 and Supplementary Table 1).
Discussion
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In this study, we used a large United States-based in-hospital cardiac arrest registry to examine whether
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the introduction of the 2010 and 2015 resuscitation guidelines were associated with a change in survival. We found that the annual trend in survival was significantly lower for the post-2010 compared to the pre-2010 guideline period, as well as for the post-2015 compared to the pre-2015 guideline
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period. There was no significant immediate change in survival from introducing the 2010 and 2015 guidelines. The results remained relatively consistent in multiple sensitivity analyses. Furthermore, we found that, while outcomes have improved for cardiac arrest from 2006 to 2010, there has been no
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meaningful improvement since 2010.
To our knowledge, only one previous paper from 2017 has studied the association of resuscitation
guidelines on outcomes in adult patients with in-hospital cardiac arrest. 21 The investigators of that study used the National Inpatient Sample, a publicly available administrative billing database in the United States, to search for cases with cardiac arrest from 2007 to 2010 and 2010 to 2014. Survival was found not to be significantly different between the two time periods. In comparison, we found a significant
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lower annual trend in survival following the introduction of the 2010 guidelines compared to the pre2010 guideline period. The previous study was based on administrative data which are inherently limited by the current coding system and the absence of detailed clinical information. Specifically, the ICD-9 codes used to search for cardiac arrest in administrative databases have been shown not to be valid for capturing patients with in-hospital cardiac arrest and survival rates from such data have been reported to vary markedly. 22, 23 Although modifications to the structure or data collection apparatus of
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prospective registries could also result in erroneous trends in outcomes, to our knowledge, there were
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no major or sudden modifications to the GWTG-R registry during the study period.
Survival to hospital discharge was found to increase significantly from 2006 to 2010, after which the
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trend in survival plateaued, with no significant increase or decrease in survival from 2011 to 2015 and from 2015 to 2018. Moreover, ROSC was found to increase for a longer time period, from 2006 to 2015,
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before plateauing. The results for the pre-2010 period are consistent with a previous publication from
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the GWTG-R registry1 and similar trends after 2010 have recently been shown in pediatric in-hospital cardiac arrest 24 and in out-of-hospital cardiac arrest 25 . Our overall findings were unexpected and the specific reasons for the observations remain unknown. One possible explanation is that the trends in
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survival were directly related to the updates of the resuscitation guidelines. The 2010 and 2015 guidelines were mainly focused on improving acute resuscitation, including changes to the characteristics of CPR (e.g., compression rate and depth) and advanced intra-cardiac arrest interventions
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(e.g., removal of atropine in 2010 and vasopressin in 2015), as well as the inclusion of post-resuscitation care (e.g., therapeutic hypothermia) as a fifth link in the chain of survival (Table 1). However, the increase in ROSC was not coupled to an increase in survival to hospital discharge, despite an anticipated benefit of these updates. Certain recommendations could conceivably have been counterproductive or not effective.
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There is generally very low level of evidence to support therapies for this patient population and the majority of treatment recommendation for patients with in-hospital cardiac arrest are based on observational data or extrapolated from the out-of-hospital cardiac arrest population. 2, 3 Because inhospital cardiac arrest has received relatively little attention, a more plausible explanation for our results could be that we have reached a saturation in our current understanding and treatment of cardiac arrest, such that the trends in survival may have reached a plateau independently of the
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guidelines. This hypothesis is partly supported by our finding of no significant immediate change in
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survival from introducing the guidelines, our sensitivity analysis demonstrating that the trend in survival remained unchanged from the post-2010/pre-2015 to the post-2015 period in hospitals providing data
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to the GWTG-R registry within the entire study period, and the Joint Point regression analysis identifying no joint point in 2015. In general, well-powered randomized clinical trials addressing in-hospital cardiac
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arrest are rare. 26 A recent study found that only 6% of randomized trials addressing post-cardiac arrest
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interventions, published between 1995 and 2019, were specifically conducted in patients with inhospital cardiac arrest. 27 New interventions, quality improvement measures, and dedicated research targeting in-hospital cardiac arrest as a unique disease entity may be necessary to improve outcomes in
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what is emerging as a substantial public health issue. Additionally, there may be a need to more effectively translate guidelines into clinical practice, as is the initiative of the recent American Heart Association’s Guideline Transformation and Optimization program. Based on recent incidence estimates
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in the United States, our findings can be translated into approximately 250,000 deaths from adult inhospital cardiac arrest in 2017. 28 Our primary findings remained relatively consistent in multiple sensitive analyses, including when
adjusting for multiple patient, cardiac arrest, and hospital characteristics, suggesting that the trends in survival were not related to rapid changes in these factors over time. Thus, our findings may have been related to unmeasured baseline characteristics (e.g., severity of illness) and/or resuscitation practices
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that changed with the implementation of the guidelines. However, our study was not designed to identify what specific factors may have affected outcomes. The results of the Joint Point regression analysis, identifying the optimal joint point as December 2010 or May 2011, is in line with our predefined censored period (November 2010 to March 2011) used for the primary analysis supporting our findings, although the lack of a joint point in 2015 suggests that survival had already reached a plateau at this stage. There was also no meaningful improvement in outcomes since 2010 in our
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subgroup analyses, with no significant differences based on initial rhythm. Although certain changes to
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the guidelines were rhythm-based (Table 1), these subgroup results are consistent with a previous paper finding no association between the guideline removal of atropine in 2010 and survival for patients with a
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non-shockable rhythm. 15
Our results should be interpreted in the context of a number of limitations. First, we were unable to
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determine the specific reason for the plateauing trend in survival and the GWTG-R registry does not
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include sufficient data to know whether resuscitation processes complied with cardiac arrest guidelines. Second, additional data, particularly in the post-2015 guideline period may have provided additional power to detect statistically significant differences between the guideline periods. Third, the
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implementation period of six months may have been too short to detect a difference between the time periods. 29, 30 For example, previous studies from the United States and Europe suggest that only 30–40% of hospitals implemented targeted temperature management within 1–2 years following guideline
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publication. 31-33 We partly addressed this limitation in sensitivity analyses assuming an implementation period of zero and 12 months. Fourth, we had limited detailed information on intra- and post-cardiac arrest interventions and were, therefore, not able to describe changes occurring over time for these characteristics. Lastly, the majority of patients with incomplete data on favorable neurological outcome had a cardiac arrest after 2010, which makes the results for this outcome and the observed decrease following the 2010 guidelines, difficult to interpret.
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Conclusions We found no evidence to support an association of guideline publication with overall improvement in survival from in-hospital cardiac arrest. Survival to hospital discharge increased from 2006 to 2010, after which the trend in survival plateaued. The annual trend in survival was significantly lower following publication of the 2010 and 2015 CPR and ECC guidelines. A continued clinical focus, new interventions,
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and dedicated research targeting adult in-hospital cardiac arrest as a unique disease entity may be
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necessary to improve outcomes in this patient population.
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Get With The Guidelines® – Resuscitation Investigators Besides the author Saket Girotra, M.D., S.M., members of the Get With The Guidelines®-Resuscitation Adult Research Task Force include:
Paul Chan, M.D., M.Sc., Ari Moskowitz, M.D., Anne V. Grossestreuer, Ph.D., Dana Edelson, M.D., M.S., Joseph Ornato, M.D., Katherine Berg, M.D., Mary Ann Peberdy, M.D., Matthew Churpek, M.D., M.P.H.,
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Ph.D., Michael Kurz, M.D., M.S.-H.E.S., Monique Anderson Starks, M.D., M.H.S., Sarah Perman, M.D.,
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M.S.C.E., and Zachary Goldberger, M.D., M.S.
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Credit Author Statement
Mathias J. Holmberg and Lars W. Andersen were responsible for the data acquisition, performed the
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statistical analyses, and drafted the manuscript. All authors contributed to the design of the study,
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interpreted the results, and critically revised the manuscript. All authors approved the final manuscript as submitted and agrees to be accountable for all aspects of the submitted work.
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Conflicts of Interest
There was no specific funding for this study. Dr. Donnino is supported by grants 5K24HL127101-04 and 5R01HL136705-03 from the National Heart, Lung, and Blood Institute.
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Lars W. Andersen and Michael Donnino are compensated by the American Heart Association (AHA) through the International Liason Commmitee on Resuscitation (ILCOR) for work related to systematic reviews used for guideline development. Lars W. Andersen serves as a statistical reviewer for JAMA. There are otherwise no disclosures.
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Acknowledgements Mathias J. Holmberg and Lars W. Andersen were responsible for the data acquisition, performed the statistical analyses, and drafted the manuscript. All authors contributed to the design of the study, interpreted the results, and critically revised the manuscript. All authors approved the final manuscript as submitted and agrees to be accountable for all aspects of the submitted work. We thank Dr. Garrett Fitzmaurice, Sc.D. (Department of Biostatistics, Harvard T.H. Chan School of
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Public Health, Boston, MA, USA) for providing statistical advice.
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5. Peberdy MA, Ornato JP, Larkin GL, et al. Survival from in-hospital cardiac arrest during nights and weekends. JAMA. Feb 2008;299(7):785-92. doi:10.1001/jama.299.7.785 6. American Hospital Association. AHA Annual Survey Database Fiscal Year 2013. Accessed February 21,
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Cardiac Arrest: A Statement for Healthcare Professionals From a Task Force of the International Liaison Committee on Resuscitation (American Heart Association, European Resuscitation Council, Australian and New Zealand Council on Resuscitation, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, Resuscitation Council of Southern Africa, Resuscitation Council of Asia); and the American Heart Association Emergency Cardiovascular Care Committee and the
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Council on Cardiopulmonary, Critical Care, Perioperative and Resuscitation. Resuscitation. Nov 2015;96:328-40. doi:10.1016/j.resuscitation.2014.11.002 8. Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol. 02 2017;46(1):348-355. doi:10.1093/ije/dyw098 9. Kontopantelis E, Doran T, Springate DA, Buchan I, Reeves D. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ. Jun
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10.Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther. Aug 2002;27(4):299-309.
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11.Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality
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12.Zou G. A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. Apr 2004;159(7):702-6.
13.Zou GY, Donner A. Extension of the modified Poisson regression model to prospective studies with
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14.Spiegelman D, Hertzmark E. Easy SAS calculations for risk or prevalence ratios and differences. Am J
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Epidemiol. Aug 2005;162(3):199-200. doi:10.1093/aje/kwi188 15.Holmberg MJ, Moskowitz A, Wiberg S, et al. Guideline removal of atropine and survival after adult inhospital cardiac arrest with a non-shockable rhythm. Resuscitation. Apr 2019;137:69-77. doi:10.1016/j.resuscitation.2019.02.002
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16.Hu FB, Goldberg J, Hedeker D, Flay BR, Pentz MA. Comparison of population-averaged and subjectspecific approaches for analyzing repeated binary outcomes. Am J Epidemiol. Apr 1998;147(7):694703. doi:10.1093/oxfordjournals.aje.a009511 17.Hubbard AE, Ahern J, Fleischer NL, et al. To GEE or not to GEE: comparing population average and mixed models for estimating the associations between neighborhood risk factors and health. Epidemiology. Jul 2010;21(4):467-74. doi:10.1097/EDE.0b013e3181caeb90
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19.Kim HJ, Fay MP, Feuer EJ, Midthune DN. Permutation tests for joinpoint regression with applications
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20.Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. Jan 1990;1(1):43-6.
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21.Mallikethi-Reddy S, Akintoye E, Rubenfire M, Briasoulis A, Grines CL, Afonso L. Nationwide survival after inhospital cardiac arrest before and after 2010 cardiopulmonary resuscitation guidelines: 20072014. Int J Cardiol. Dec 2017;249:231-233. doi:10.1016/j.ijcard.2017.09.199
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22.Khera R, Spertus JA, Starks MA, et al. Administrative Codes for Capturing In-Hospital Cardiac Arrest. JAMA Cardiol. Nov 2017;2(11):1275-1277. doi:10.1001/jamacardio.2017.2904 23.DeZorzi C, Boyle B, Qazi A, et al. Administrative Billing Codes for Identifying Patients With
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Cardiac Arrest. J Am Coll Cardiol. Apr 2019;73(12):1598-1600. doi:10.1016/j.jacc.2019.01.030 24.Holmberg MJ, Wiberg S, Ross CE, et al. Trends in Survival After Pediatric In-Hospital Cardiac Arrest in the United States. Circulation. Oct 2019;140(17):1398-1408. doi:10.1161/CIRCULATIONAHA.119.041667
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25.Granfeldt A, Holmberg MJ, Donnino MW, Andersen LW, Group CS. 2015 Guidelines for Cardiopulmonary Resuscitation and Survival after Adult and Pediatric Out-of-Hospital Cardiac Arrest. Eur Heart J Qual Care Clin Outcomes. Mar 2020;doi:10.1093/ehjqcco/qcaa027 26.Andersen LW, Holmberg MJ, Berg KM, Donnino MW, Granfeldt A. In-Hospital Cardiac Arrest: A Review. JAMA. Mar 2019;321(12):1200-1210. doi:10.1001/jama.2019.1696 27.Andersen LW, Lind PC, Vammen L, Hoybye M, Holmberg MJ, Granfeldt A. Adult Post-Cardiac Arrest
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28.Holmberg M, Ross C, Fitzmaurice G, et al. Annual Incidence of Adult and Pediatric In-Hospital Cardiac Arrest in the United States. Circulation: Cardiovascular Quality and Outcomes. 2019;
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29.Bigham BL, Koprowicz K, Aufderheide TP, et al. Delayed prehospital implementation of the 2005 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiac
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care. Prehosp Emerg Care. Jul-Sep 2010;14(3):355-60. doi:10.3109/10903121003770639
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30.Berdowski J, Schmohl A, Tijssen JG, Koster RW. Time needed for a regional emergency medical system to implement resuscitation Guidelines 2005--The Netherlands experience. Resuscitation. Dec 2009;80(12):1336-41. doi:10.1016/j.resuscitation.2009.08.011
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31.Laver SR, Padkin A, Atalla A, Nolan JP. Therapeutic hypothermia after cardiac arrest: a survey of practice in intensive care units in the United Kingdom. Anaesthesia. Sep 2006;61(9):873-7. doi:10.1111/j.1365-2044.2006.04552.x
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32.Merchant RM, Soar J, Skrifvars MB, et al. Therapeutic hypothermia utilization among physicians after resuscitation from cardiac arrest. Crit Care Med. Jul 2006;34(7):1935-40. doi:10.1097/01.CCM.0000220494.90290.92
33.Sander M, von Heymann C, Spies C. Implementing the International Liaison Committee on Resuscitation guidelines on hypothermia after cardiac arrest. The German experience: still a long way to go? Crit Care. 2006;10(2):407. doi:10.1186/cc4882
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34.Andersen LW, Granfeldt A, Callaway CW, et al. Association Between Tracheal Intubation During Adult In-Hospital Cardiac Arrest and Survival. JAMA. 02 2017;317(5):494-506.
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doi:10.1001/jama.2016.20165
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Figures and Tables 308,885 Adult in-hospital cardiac arrests between May 2006 and December 2018
57,371
Excluded 54,969 Non-index events 2402 Missing data on primary outcome
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Censored 7149 2010 guideline analysis 12,626 2015 guideline analysis
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231,739 In-hospital cardiac arrests included for the primary analyses
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19,775
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251,514 In-hospital cardiac arrests meeting all inclusion and exclusion criteria
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Figure 1. Inclusion and exclusion criteria for the primary analysis. Between May 2006 and December 2018, 308,885 adult in-hospital cardiac arrests were registered in the
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Get With The Guidelines® – Resuscitation registry. A total of 251,514 patients met all the inclusion and
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none of the exclusion criteria, of which 231,739 patients were included for the primary analyses.
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Figure 2. Interrupted time series for survival to hospital discharge
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The open circles represent survival per quarter. The solid lines represent the estimated trend in survival
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and 2015 resuscitation guidelines.
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over time with 95% confidence intervals. The dashed vertical lines represent the publication of the 2010
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Table 1. Key changes to the American Heart Association guidelines 2005 Guidelines
2010 Guidelines
2015 Guidelines
Approach
Airway-Breathing-Circulation
Circulation-Airway-Breathing
No change
Depth
1½–2 inches
At least 2 inches
At least 2 inches while avoiding excessive depth
Compression
100/min
At least 100/min
100/min to 120/min
Algorithm
High-quality CPR assumed provided
Simplified to emphasize highquality CPR
No change
Basic Life Support
Advanced Cardiac Life Support May replace 1st/2nd dose of epinephrine
No change
No advantages as a substitute to epinephrine
Epinephrine
Not stratified by rhythm
No change
As soon as possible for nonshockable rhythms
Amiodarone and Lidocaine
Amiodarone or lidocaine acceptable for refractory VF
Amiodarone is the first-line agent; lidocaine may be considered if unavailable
Atropine
Included as a treatment for PEA Excluded as a treatment for PEA No change and asystole and asystole
Intubation
Confirm placement with exhaled CO2 detector
ECPR
Not included
Approach
Not included
Angiography
Not included
ro
-p
Amiodarone or lidocaine acceptable for refractory VF/pVT
Ultrasound added as option to confirm placement
Not included
Consider ECPR in select patients with refractory cardiac arrest
re
Confirm placement with waveform capnography
lP
Post-resuscitation care
of
Vasopressin
Added as fifth link in the chain of survival
No change
Recommended for patients with Recommended for patients with myocardial infarction cardiac etiology
32–34C for 12–24 hours for comatose victims with VF/nonVF
32–34C for 12–24 hours for all comatose victims
32–36C for 24 hours for all comatose victims
Oxygenation
Not included
Titration to oxygen saturation 94%
No change
Jo
ur na
Hypothermia
Page 25 of 31
Table 2. Patient, event, and hospital characteristics Pre-2010 a
2010-2015 b
Post-2015 c
SD
SD
(N = 70 016)
(N = 89 782)
(N = 71 941)
2010 d
2015 e
67 (55, 78)
67 (56, 77)
67 (56, 76)
–0.02
–0.01
Male
40 625 (58)
52 154 (58)
42 035 (58)
<0.01
0.01
Female
29 390 (42)
37 612 (42)
29 895 (42)
<0.01
–0.01
Cardiac
23 203 (33)
32 782 (37)
Non-cardiac
31 435 (45)
37 887 (42)
Cardiac
4624 (7)
5848 (7)
Non-cardiac f
8280 (12) 2384 (3)
Demographics Age (median, IQR)
of
Sex
Illness category
ro
Medical
0.07
0.02
30 967 (43)
–0.05
0.02
4250 (6)
<0.01
–0.03
9706 (11)
6943 (10)
–0.03
–0.04
3265 (4)
2625 (4)
0.01
<0.01
11 492 (16)
13 320 (15)
10 153 (14)
–0.04
–0.02
Heart failure prior admission
13 343 (19)
18 736 (21)
16 372 (23)
0.05
0.04
MI this admission
10 835 (16)
12 269 (14)
10 045 (14)
–0.05
0.01
MI prior admission
10 177 (15)
11 864 (13)
9600 (13)
–0.04
<0.01
Acute CNS non-stroke event
5080 (7)
5518 (6)
6339 (9)
–0.04
0.10
Baseline depression in CNS function
8303 (12)
7227 (8)
5431 (8)
–0.13
–0.02
Diabetes mellitus
21 395 (31)
28 734 (32)
25 000 (35)
0.03
0.06
Hepatic insufficiency
5176 (7)
6337 (7)
6395 (9)
–0.01
0.07
Hypotension
18 776 (27)
20 622 (23)
19 942 (28)
–0.09
0.11
Major trauma
3055 (4)
4150 (5)
3812 (5)
0.01
0.03
Pre-existing conditionsg Cardiac
ur na
Heart failure this admission
lP
Trauma
re
Surgical
-p
26 977 (38)
Jo
Non-cardiac
Page 26 of 31
Metabolic or electrolyte abnormality
10 462 (15)
15 714 (18)
18 244 (25)
0.07
0.19
Metastatic or hematologic malignancy
8732 (12)
10 038 (11)
7630 (11)
–0.04
–0.02
Pneumonia
9376 (13)
12 089 (14)
9930 (14)
<0.01
0.01
Renal insufficiency
23 282 (33)
30 915 (35)
25 704 (36)
0.03
0.02
Respiratory insufficiency
29 145 (42)
38 277 (43)
33847 (47)
0.02
0.09
Septicemia
11 777 (17)
15 086 (17)
11 055 (15)
<0.01
–0.04
Emergency Department
7142 (10)
10 241 (11)
9819 (14)
0.04
0.07
Intensive Care Unit
33 992 (49)
43 358 (48)
33 783 (47)
–0.01
–0.03
Without telemetry
12 053 (17)
14 049 (16)
–0.04
<0.01
With telemetry
10 941 (16)
13 625 (15)
10 323 (14)
–0.01
–0.02
Otherh
5855 (8)
8432 (9)
6796 (9)
0.04
<0.01
27 631 (31)
21 983 (31)
<0.01
–0.01
48 484 (69)
62 151 (69)
49 958 (69)
<0.01
<0.01
22 159 (32)
27 166 (31)
21 633 (30)
–0.03
<0.01
47 132 (68)
61 819 (69)
49 384 (70)
0.03
–0.01
58 369 (83)
78 184 (87)
63 431 (88)
0.11
0.03
11 646 (17)
11 548 (13)
8481 (12)
–0.11
–0.03
Yes
60 234 (86)
76 576 (85)
60 752 (85)
–0.02
–0.02
No
9781 (14)
13 169 (15)
11 032 (15)
0.02
0.02
19 072 (27)
19 410 (22)
19 206 (27)
–0.13
0.12
Location and Time of Event
re
Time of weeki
21 532 (31)
lP
Weekend Weekday Time of dayj
Daytime
ur na
Nighttime
ro 11 173 (16)
-p
Floor
of
Location
Arrest Characteristics Witnessed Yes
Jo
No
Monitored
Interventions in place at arrest Vasoactive agents k
Page 27 of 31
Mechanical ventilation
26 912 (38)
36 377 (41)
34 047 (47)
0.04
0.14
Intra-arterial catheter
7812 (11)
9411 (10)
7324 (10)
–0.02
–0.01
Asystole
22 269 (34)
23 214 (29)
16 525 (25)
–0.13
–0.07
Pulseless electrical activity
30 334 (47)
44 015 (54)
37 539 (58)
0.12
0.06
Pulseless ventricular tachycardia
5051 (8)
6052 (7)
4953 (8)
–0.02
0.01
Ventricular fibrillation
7363 (11)
7879 (10)
5952 (9)
–0.06
–0.02
Major
23 884 (35)
31 252 (37)
23 494 (35)
Minor
35 029 (51)
44 613 (52)
Non-teaching
9509 (14)
9520 (11)
Military
1506 (2)
825 (1)
Non-profit
49 351 (76)
Government
4982 (8)
Initial rhythm
of
Hospital characteristics Teaching status
–0.05
35 327 (53)
–0.01
–0.01
8377 (12)
–0.09
0.03
338 (1)
–0.10
–0.05
62 940 (77)
50 005 (79)
–0.01
–0.01
9409 (11)
7162 (11)
0.12
–0.02
8681 (13)
8902 (11)
5464 (9)
–0.08
–0.08
66 281 (100)
84 041 (100)
66 103 (100)
–0.05
–0.07
33 (<1)
83 (<1)
152 (<1)
0.02
0.03
9161 (13)
15 510 (18)
11 108 (17)
0.12
–0.05
19 683 (29)
22 418 (26)
16 994 (25)
–0.07
–0.03
North-Central
14 203 (21)
17 725 (21)
14 096 (21)
–0.01
<0.01
South-Central
14 199 (21)
18 116 (21)
14 050 (21)
<0.01
–0.02
West
11 301 (16)
11 922 (14)
10 950 (16)
–0.08
0.06
1 – 249
11 981 (18)
12 868 (15)
10 611 (16)
–0.08
0.01
250 – 499
27 166 (40)
34 264 (40)
25 982 (39)
–0.01
–0.04
Hospital location
Rural
ur na
Urban
lP
Private
-p
re
Ownership
ro
0.02
Geographic location North-East
Jo
South-East
Number of hospital beds
Page 28 of 31
>500
28 193 (42)
37 780 (44)
29 939 (45)
0.04
–0.01
Abbreviations: SD, standardized difference; IQR, interquartile range; MI, myocardial infarction; CNS, central nervous system. Standardized differences “<0.01” represent values >–0.01 and <0.01. a Defined as
the time from May 1, 2006 to October 31, 2010
b Defined as
the time from May 1, 2011 to October 31, 2015
c
Defined as the time from May 1, 2016 to December 31, 2018 between the pre -2010 and post-2010 period
e Standardized difference
between the pre -2015 and post-2015 period
f
of
d Standardized difference
Includes patients with an obstetric admission have been provided elsewhere 34
ro
g Definitions
h Ambulatory and outpatient areas, delivery suite, rehabilitation facility, skilled nursing
facility, mental health facility, same-day
to 7:00am to 10:59pm, Night refers to 11:00pm to 6:59am
j Weekday refers k Continuous
to Monday 7:00am to Friday 10:59pm, Weeken d refers to Friday 11:00pm to Monday 6:59am
re
i Day refers
-p
surgical area, operating room, post-anesthesia recovery room, or interventional unit
infusion of dobutamine, dopamine > 3 mcg/kg/min, epinephrine, nitroglycerin, norepinephrine, phenylephrine,
Jo
ur na
lP
vasopressin, or other vasoactive agents
Page 29 of 31
Table 3. Interrupted time series model Risk differences
Relative risk P-value
(95% CI)
P-value (95% CI)
Survival to hospital discharge Trends 1.09% (0.74, 1.43)
<0.001
1.05 (1.04, 1.07)
<0.001
Post-2010/pre-2015 slope
0.26% (–0.11, 0.64)
0.17
1.01 (1.00, 1.03)
0.17
Post-2015 slope
–0.43% (–0.96, 0.11)
0.12
0.98 (0.96, 1.00)
0.11
Pre-post 2010 slope difference
–0.82% (–1.35, –0.30)
0.002
0.96 (0.94, 0.98)
Pre-post 2015 slope difference
–0.69% (–1.33, –0.04)
0.04
of
Pre-2010 slope
0.46% (–0.84, 1.76)
2015 guideline level change
1.13% (–0.09, 2.36)
Return of spontaneous circulation
lP
Trends Pre-2010 slope
<0.001 0.03
0.49
1.02 (0.96, 1.07)
0.59
0.07
1.04 (1.00, 1.09)
0.07
re
2010 guideline level change
0.97 (0.95, 1.00)
-p
Immediate change
ro
Difference in trends
2.25% (1.76, 2.74)
<0.001
1.04 (1.03, 1.04)
<0.001
0.83% (0.41, 1.26)
<0.001
1.01 (1.01, 1.02)
<0.001
0.47% (–0.11, 1.04)
0.11
1.01 (1.00, 1.01)
0.11
Pre-post 2010 slope difference
–1.42% (–2.06, –0.77)
<0.001
0.98 (0.97, 0.99)
<0.001
Pre-post 2015 slope difference
–0.37% (–1.09, 0.35)
0.31
0.99 (0.98, 1.00)
0.27
2010 guideline level change
–0.64% (–2.36, 1.08)
0.46
0.99 (0.96, 1.01)
0.36
2015 guideline level change
0.76% (–0.63, 2.15)
0.29
1.01 (0.99, 1.03)
0.31
Pre-2010 slope
0.86% (0.47, 1.24)
<0.001
1.05 (1.03, 1.08)
<0.001
Post-2010/pre-2015 slope
0.54% (0.03, 1.05)
0.04
1.03 (1.00, 1.07)
0.04
Post-2010/pre-2015 slope
ur na
Post-2015 slope
Difference in trends
Jo
Immediate change
Favorable neurological outcome Trends
Page 30 of 31
Post-2015 slope
0.04% (–0.61, 0.70)
0.90
1.00 (0.97, 1.04)
0.90
Pre-post 2010 slope difference
–0.32% (–0.98, 0.34)
0.34
0.98 (0.94, 1.02)
0.33
Pre-post 2015 slope difference
–0.50% (–1.32, 0.33)
0.24
0.97 (0.93, 1.02)
0.21
2010 guideline level change
–3.25% (–5.14, –1.36)
<0.001
0.82 (0.73, 0.92)
0.001
2015 guideline level change
0.41% (–1.02, 1.84)
0.58
1.02 (0.94, 1.11)
0.60
Difference in trends
Immediate change
of
Pre-slope refers to the annual trend in survival prior to introducing the 2010 and 2015 resuscitation guidelines. Post-slope refers to the annual trend in survival after introducing the 2010 and 2015 resuscitation guidelines. Level change refers to the
ro
immediate change in survival after introducing the guidelines . Pre-post slope difference refers to the difference in survival
Jo
ur na
lP
re
-p
trend from the pre-guideline to post-guideline period.
Page 31 of 31