Estimating Effectiveness of Cardiac Arrest Interventions

TLDR

Both regions use similar two‑tiered emergency response systems. The study aimed to create a simple, generalizable logistic‑regression model predicting survival after out‑of‑hospital ventricular fibrillation arrest. Using retrospective data from two large cohorts (n=205 and n=1667) of witnessed VF arrests, the authors applied logistic regression to assess survival to hospital discharge. Age, bystander CPR, collapse‑to‑CPR and collapse‑to‑defibrillation intervals (and their interactions) were significant predictors; a simplified interval‑only model performed as well as the full model, showed no site difference, and can be applied to other U.S.

Abstract

The study objective was to develop a simple, generalizable predictive model for survival after out-of-hospital cardiac arrest due to ventricular fibrillation.Logistic regression analysis of two retrospective series (n=205 and n=1667, respectively) of out-of-hospital cardiac arrests was performed on data sets from a Southwestern city (population, 415,000; area, 406 km2) and a Northwestern county (population, 1,038,000; area, 1399 km2). Both are served by similar two-tiered emergency response systems. All arrests were witnessed and occurred before the arrival of emergency responders, and the initial cardiac rhythm observed was ventricular fibrillation. The main outcome measure was survival to hospital discharge. Patient age, initiation of CPR by bystanders, interval from collapse to CPR, interval from collapse to defibrillation, bystander CPR/collapse-to-CPR interval interaction, and collapse-to-CPR/collapse-to-defibrillation interval interaction were significantly associated with survival. There was not a significant difference between observed survival rates at the two sites after control for significant predictors. A simplified predictive model retaining only collapse to CPR and collapse to defibrillation intervals performed comparably to the more complicated explanatory model.The effectiveness of prehospital interventions for out-of-hospital cardiac arrest may be estimated from their influence on collapse to CPR and collapse to defibrillation intervals. A model derived from combined data from two geographically distinct populations did not identify site as a predictor of survival if clinically relevant predictor variables were controlled for. This model can be generalized to other US populations and used to project the local effectiveness of interventions to improve cardiac arrest survival.