Abstract
Background
Although several Utstein variables are known to independently improve survival, how
they moderate the effect of emergency medical service (EMS) response times on survival
is unknown.
Objectives
To quantify how public location, witnessed status, bystander CPR, and bystander AED
shock individually and jointly moderate the effect of EMS response time delays on
OHCA survival.
Methods
This retrospective cohort study was a secondary analysis of the Resuscitation Outcomes
Consortium Epistry-Cardiac Arrest database (December 2005 to June 2015). We included
all adult, non-traumatic, non-EMS witnessed, and EMS-treated OHCAs from eleven sites
across the US and Canada. We trained a logistic regression model with standard Utstein
control variables and interaction terms between EMS response time and the four aforementioned
OHCA characteristics.
Results
102,216 patients were included. Three of the four characteristics – witnessed OHCAs
(OR = 0.962), bystander CPR (OR = 0.968) and public location (OR = 0.980) – increased
the negative effect of a one-minute delay on the odds of survival. In contrast, a
bystander AED shock decreased the negative effect of a one-minute response time delay
on the odds of survival (OR = 1.064). The magnitude of the effect of a one-minute
delay in EMS response time on the odds of survival ranged from 1.3% to 9.8% (average:
5.3%), depending on the underlying OHCA characteristics.
Conclusions
Delays in EMS response time had the largest reduction in survival odds for OHCAs that
did not receive a bystander AED shock but were witnessed, occurred in public, and/or
received bystander CPR. A bystander AED shock appears to be protective against a delay
in EMS response time.
Keywords
Abbreviations:
AED (Automated external defibrillator), AUC (area under the receiver operating characteristic curve), CI (confidence interval), CPR (cardiopulmonary resuscitation), EMS (emergency medical services), OHCA (out-of-hospital cardiac arrest), OR (odds ratio), PAD (public access defibrillation), ROC (resuscitation outcomes consortium)To read this article in full you will need to make a payment
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References
- Ventricular tachyarrhythmias after cardiac arrest in public versus at home.New Engl J Med. 2011; 364: 313-321
- Predictors of survival from out-of-hospital cardiac arrest: a systematic review and meta-analysis.Circ Cardiovasc Qual Outcomes. 2010; 3: 63-81
- Improved survival after out-of-hospital cardiac arrest is associated with an increase in proportion of emergency crew--witnessed cases and bystander cardiopulmonary resuscitation.Cirtulation. 2008; 118: 389-396
- Early cardiopulmonary resuscitation in out-of-hospital cardiac arrest.N Engl J Med. 2015; 372: 2307-2315
- Association of bystander cardiopulmonary resuscitation and survival according to ambulance response times after out-of-hospital cardiac arrest.Circulation. 2016; 134: 2095-2104
- The effect of ambulance response time on survival following out-of-hospital cardiac arrest: An analysis from the German resuscitation registry.Deutsches Ärzteblatt Int. 2018; 115: 541
- Effect of reducing ambulance response times on deaths from out of hospital cardiac arrest: cohort study.BMJ. 2001; 322: 1385-1388
- Ontario Prehospital Advanced Life Support Study G. Optimal defibrillation response intervals for maximum out-of-hospital cardiac arrest survival rates.Ann Emerg Med. 2003; 42: 242-250
- Relationship between emergency medical services response time and bystander intervention in patients with out-of-hospital cardiac arrest.J Am Heart Assoc. 2018; 7e007568
- Estimating effectiveness of cardiac arrest interventions: a logistic regression survival model.Circulation. 1997; 96: 3308-3313
- Predicting survival from out-of-hospital cardiac arrest: a graphic model.Ann Emerg Med. 1993; 22: 1652-1658
- Modifiable factors associated with improved cardiac arrest survival in a multicenter basic life support/defibrillation system: OPALS study phase I results.Ann Emergency Med. 1999; 33: 44-50
- Role of ambulance response times in the survival of patients with outof-hospital cardiac arrest.Emerg Med J. 2011; 28: 703-707
- The PulsePoint Respond mobile device application to crowdsource basic life support for patients with out-of-hospital cardiac arrest: Challenges for optimal implementation.Resuscitation. 2016; 98: 20-26
- Effectiveness of a community based out-of-hospital cardiac arrest (OHCA) interventional bundle: results of a pilot study.Resuscitation. 2020; 146: 220-228
- Adult Basic Life Support: 2020 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations.Circulation. 2020;
- Effect of Optimized Versus Guidelines-Based Automated External Defibrillator Placement on Out-of-Hospital Cardiac Arrest Coverage: An In Silico Trial.J Am Heart Assoc. 2020; 9e016701
- Improving bystander defibrillation in out-of-hospital cardiac arrests at home.Eur Heart J: Acute Cardiovascular Care. 2020; (2048872619891675)
Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Version 1 and 2. National Heart, Lung, and Blood Institute. https://biolincc.nhlbi.nih.gov/studies/roc_cardiac_epistry_1_2/. Published 2018. Accessed 2019.
Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Version 3. National Heart, Lung, and Blood Institute. https://biolincc.nhlbi.nih.gov/studies/roc_cardiac_epistry_3/ Published 2018. Accessed 2019.
- Multiple imputation by chained equations: what is it and how does it work?.Int J Methods Psychiatric Res. 2011; 20: 40-49
- Multiple imputation: a flexible tool for handling missing data.JAMA. 2015; 314: 1966-1967
- Multiple imputation for nonresponse in surveys. vol. 81. John Wiley & Sons, 2004
Team RC. R: A language and environment for statistical computing; 2013.
- Applied logistic regression. 398. John Wiley & Sons, 2013
- Simultaneous inference in general parametric models.Biometrical J Biometrische Zeitschrift. 2008; 50: 346-363
- Public-access defibrillation and survival after out-of-hospital cardiac arrest.N Engl J Med. 2004; 351: 637-646
- Cardiac arrest detection through artificial intelligence-based surveillance camera: a working prototype.Resuscitation. 2018; 130e114
- Contactless cardiac arrest detection using smart devices.NPJ Digital Med. 2019; 2: 1-8
- Wearable devices for ambulatory cardiac monitoring: JACC state-of-the-art review.J Am Coll Cardiol. 2020; 75: 1582-1592
- Key components of a community response to out-of-hospital cardiac arrest.Nature Rev Cardiol. 2019; 16: 407-416
- Optimizing a drone network to deliver automated external defibrillators.Circulation. 2017; 135: 2454-2465
- Improving Access to automated external defibrillators in rural and remote settings: a drone delivery feasibility study.J Am Heart Assoc. 2020; 9e016687
- Regional variation in out-of-hospital cardiac arrest incidence and outcome.JAMA. 2008; 300: 1423-1431
Article info
Publication history
Published online: October 19, 2021
Accepted:
October 7,
2021
Received in revised form:
September 6,
2021
Received:
June 2,
2021
Identification
Copyright
© 2021 Elsevier B.V. All rights reserved.
