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

of

the American Heart Association’s Get With The Guidelines®-Resuscitation Investigators*

ro

* The members of the Get With The Guidelines®-Resuscitation Adult Research Task Force are listed at

-p

the end of the article

1

re

Affiliations

Research Center for Emergency Medicine, Department of Clinical Medicine, Aarhus University and

2 Center for

lP

Aarhus University Hospital, Aarhus, Denmark

Resuscitation Science, Department of Emergency Medicine, Beth Israel Deaconess Medical

ur na

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

Jo

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

ro

of

Email: [email protected]

Word Count Abstract: 238

-p

Word Count Manuscript: 3157 Figures and Tables: 5

Jo

ur na

lP

re

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

of

Using the Get With The Guidelines® – Resuscitation registry, we included adult patients with an in-

ro

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

-p

2010 and 2015 resuscitation guidelines.

re

Results

lP

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-

ur na

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

Jo

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,

Jo

ur na

lP

re

-p

ro

of

Interrupted Time Series

Page 4 of 31

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

of

However, the association between the 2010 and 2015 resuscitation guidelines and survival from cardiac

ro

arrest in hospitalized patients has not been well-studied. Additionally, no large study has reported on trends in survival using contemporary data. 1

-p

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

re

2015 resuscitation guidelines were associated with a change in survival after adult in-hospital cardiac

Methods

ur na

Study Design and Data Source

lP

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

Jo

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

Page 5 of 31

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

ro

of

research involving the GWTG-R registry does not meet the federal definition of human subject research.

Study Population, Exposure, and Outcomes

-p

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

re

excluded.

lP

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

ur na

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

Jo

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

Page 6 of 31

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

of

guideline publication. 2, 3 The pre-2010 guideline period was defined as the time from May 1st, 2006 to

ro

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

-p

December 31st, 2018. Since guidelines require implementation before any impact on survival may be

censored from the primary analyses.

re

observed, the time period between the pre-guideline and post-guideline segments (six months) were

lP

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

ur na

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.

Jo

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.

Page 7 of 31

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 ,

of

we repeated the analysis while adjusting for all patient, event, and hospital characteristics outlined in

ro

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

-p

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

re

to the GWTG-R registry for the full study period (from 2006 to 2015 for the 2010 analysis and from 2011

lP

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

ur na

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

Jo

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.

Page 8 of 31

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

ro

of

full cohort (Table 2).

Survival to Hospital Discharge

-p

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

re

was an increase in survival within the pre-2010 guideline period (RD, 1.09% per year; 95% CI, 0.74% to

lP

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).

ur na

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).

Jo

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).

Page 9 of 31

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

of

significantly different for the post-2015 compared to the pre-2015 guideline period (RD, –0.37% per

ro

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,

-p

–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).

re

Additional details are provided in Table 3 and Supplementary Figure 2.

lP

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

ur na

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, –

Jo

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.

Page 10 of 31

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

of

estimating the optimal number and location of trend segments found a single joint point, identified as

ro

December 2010 or May 2011 depending on the model assumption, to be the most optimal model for

-p

the time series (Supplementary Figure 6–7 and Supplementary Table 1).

Discussion

re

In this study, we used a large United States-based in-hospital cardiac arrest registry to examine whether

lP

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

ur na

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

Jo

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

Page 11 of 31

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

of

prospective registries could also result in erroneous trends in outcomes, to our knowledge, there were

ro

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

-p

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,

re

before plateauing. The results for the pre-2010 period are consistent with a previous publication from

lP

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

ur na

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

Jo

(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.

Page 12 of 31

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

of

guidelines. This hypothesis is partly supported by our finding of no significant immediate change in

ro

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

-p

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

re

arrest are rare. 26 A recent study found that only 6% of randomized trials addressing post-cardiac arrest

lP

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

ur na

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

Jo

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

Page 13 of 31

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

of

subgroup analyses, with no significant differences based on initial rhythm. Although certain changes to

ro

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

-p

non-shockable rhythm. 15

Our results should be interpreted in the context of a number of limitations. First, we were unable to

re

determine the specific reason for the plateauing trend in survival and the GWTG-R registry does not

lP

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

ur na

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

Jo

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.

Page 14 of 31

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,

of

and dedicated research targeting adult in-hospital cardiac arrest as a unique disease entity may be

Jo

ur na

lP

re

-p

ro

necessary to improve outcomes in this patient population.

Page 15 of 31

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.,

of

Ph.D., Michael Kurz, M.D., M.S.-H.E.S., Monique Anderson Starks, M.D., M.H.S., Sarah Perman, M.D.,

ro

M.S.C.E., and Zachary Goldberger, M.D., M.S.

-p

Credit Author Statement

Mathias J. Holmberg and Lars W. Andersen were responsible for the data acquisition, performed the

re

statistical analyses, and drafted the manuscript. All authors contributed to the design of the study,

lP

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.

ur na

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.

Jo

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.

Page 16 of 31

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

Jo

ur na

lP

re

-p

ro

of

Public Health, Boston, MA, USA) for providing statistical advice.

Page 17 of 31

References 1. Girotra S, Nallamothu BK, Spertus JA, et al. Trends in survival after in-hospital cardiac arrest. N Engl J Med. Nov 2012;367(20):1912-20. doi:10.1056/NEJMoa1109148 2. Field JM, Hazinski MF, Sayre MR, et al. Part 1: executive summary: 2010 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. Nov 2010;122(18 Suppl 3):S640-56. doi:10.1161/CIRCULATIONAHA.110.970889

of

3. Neumar RW, Shuster M, Callaway CW, et al. Part 1: Executive Summary: 2015 American Heart

ro

Association Guidelines Update for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. Nov 2015;132(18 Suppl 2):S315-67. doi:10.1161/CIR.0000000000000252

-p

4. Peberdy MA, Kaye W, Ornato JP, et al. Cardiopulmonary resuscitation of adults in the hospital: a

Resuscitation. Sep 2003;58(3):297-308.

re

report of 14720 cardiac arrests from the National Registry of Cardiopulmonary Resuscitation.

lP

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,

ur na

2020. http://www.ahadata.com/aha-annual-survey-database-asdb/ 7. Perkins GD, Jacobs IG, Nadkarni VM, et al. Cardiac Arrest and Cardiopulmonary Resuscitation Outcome Reports: Update of the Utstein Resuscitation Registry Templates for Out-of-Hospital

Jo

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

Page 18 of 31

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

of

2015;350:h2750.

ro

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.

-p

11.Penfold RB, Zhang F. Use of interrupted time series analysis in evaluating health care quality

doi:10.1016/j.acap.2013.08.002

re

improvements. Acad Pediatr. 2013 Nov-Dec 2013;13(6 Suppl):S38-44.

lP

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

ur na

correlated binary data. Stat Methods Med Res. Dec 2013;22(6):661-70. doi:10.1177/0962280211427759

14.Spiegelman D, Hertzmark E. Easy SAS calculations for risk or prevalence ratios and differences. Am J

Jo

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

Page 19 of 31

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

of

18.Joinpoint Regression Program. Version Version 4.7.0.0. Statistical Methodology and Application

ro

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

-p

to cancer rates. Stat Med. Feb 2000;19(3):335-51. doi:10.1002/(sici)1097-

re

20.Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. Jan 1990;1(1):43-6.

lP

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

ur na

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

Jo

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

Page 20 of 31

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

of

Interventions: A Scoping Review of Randomized Clinical Trials. Submitted to Resuscitation. 2019;

ro

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;

-p

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

re

care. Prehosp Emerg Care. Jul-Sep 2010;14(3):355-60. doi:10.3109/10903121003770639

lP

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

ur na

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

Jo

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

Page 21 of 31

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.

Jo

ur na

lP

re

-p

ro

of

doi:10.1001/jama.2016.20165

Page 22 of 31

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

ro

Censored 7149 2010 guideline analysis 12,626 2015 guideline analysis

re

231,739 In-hospital cardiac arrests included for the primary analyses

-p

19,775

of

251,514 In-hospital cardiac arrests meeting all inclusion and exclusion criteria

lP

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

ur na

Get With The Guidelines® – Resuscitation registry. A total of 251,514 patients met all the inclusion and

Jo

none of the exclusion criteria, of which 231,739 patients were included for the primary analyses.

Page 23 of 31

of ro -p

Figure 2. Interrupted time series for survival to hospital discharge

re

The open circles represent survival per quarter. The solid lines represent the estimated trend in survival

Jo

ur na

and 2015 resuscitation guidelines.

lP

over time with 95% confidence intervals. The dashed vertical lines represent the publication of the 2010

Page 24 of 31

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