ESTIMATING EFFECTIVENESS OF CARDIAC-ARREST INTERVENTIONS - A LOGISTIC-REGRESSION SURVIVAL MODEL

Background The study objective was to develop a simple, generalizable predictive model for survival after out-of-hospital cardiac arrest due to ventricular fibrillation. Methods and Results Logistic regression analysis of two retrospective series (n = 205 and n = 1667, respective ly) of out-of-hospital cardiac arrests was performed on data sets from a Southwestern city (population, 415000; area, 406 km(2)) and a North western county (population, 1038000; area, 1399 km(2)). Both are serve d by similar two-tiered emergency response systems. AU arrests were wi tnessed and occurred before the arrival of emergency responders, and t he initial cardiac rhythm observed was ventricular fibrillation. The m ain outcome measure was survival to hospital discharge. Patient age. i nitiation of CPR by bystanders. interval from collapse to CPR, interva l from collapse to defibrillation, bystander CPR/collapse-to-CPR inter val interaction, and collapse-to-CPR/collapse-to-defibrillation interv al interaction were significantly associated with survival. There was not a significant difference between observed survival rates at the tw o sites after control for significant predictors. A simplified predict ive model retaining only collapse to CPR and collapse to defibrillatio n intervals performed comparably to the more complicated explanatory m odel. Conclusions The effectiveness of prehospital interventions for o ut-of-hospital cardiac arrest may be estimated from their influence on collapse to CPR and collapse to defibrillation intervals. A model der ived from combined data from two geographically distinct populations d id not identify site as a predictor of survival if clinically relevant predictor variables were controlled for. This model can be generalize d to other US populations and used to project the local effectiveness of interventions to improve cardiac arrest survival.