Predicting survival from out-of-hospital cardiac arrest: a multivariate analysis

Abstract

From 954 attempts to resuscitate patients from out-of-hospital cardiac arrest two datasets were derived, namely 861 cases of cardiac arrest and 906 cases of either cardiac or primary respiratory arrest. For each dataset, multivariate analysis was performed by fitting a number of explanatory variables with respect to the outcomes of admission to hospital and discharge home in logistic regression models. There were numerous interactions between these variables. Being conscious at the time of the arrival of the ambulance crew and subsequently having cardiac arrest strongly predicted survival, as did both the presence of a witness to the arrest and the initiation of cardiopulmonary resuscitation (CPR) by a bystander; this latter effect was a marker for early CPR. The strongest predictor of a poor outcome was delay to CPR or delay to advanced cardiac life support.