A multiple logistic regression analysis of in-hospital factors related to survival at six months in patients resuscitated from out-of-hospital ventricular fibrillation

Introduction: The impact of the immediate in-hospital post-resuscitation care after out-hospital cardiac arrest is not well known. Based on treatment variables and laboratory findings a multiple logistic regression model was created for the prediction of survival at 6 months from the event. Materials and methods: A retrospective study of the hospital charts of patients successfully resuscitated and treated in one of three community hospitals from 1998 to 2000. In addition to several pre-hospital variables, the mean 72 h values of clinical features such as blood pressure, blood glucose concentration and initiated treatment used, were included in a forward multiple logistic regression model predicting survival at 6 months from the event. Results: The charts of 98 out of a total of 102 patients were sufficiently complete and included in the analysis. Variables independently associated with survival were age, delay before a return of spontaneous circulation, mean blood glucose and serum potassium, and the use of beta-blocking agents during post-resuscitation care. When those patients who were assigned a ‘do not attempt to resuscitate’ (DNAR) order during the first 72 h of treatment were excluded from the analysis blood glucose, blood potassium and the use beta-blocking agents remained independently associated with survival. Conclusion: This study suggests that in-hospital factors are associated with survival from out-of-hospital cardiac arrest. The mean blood glucose and serum potassium during the first 72 h of treatment and the use of beta-blocking agents were significantly and independently associated with survival. [Copyright &y& Elsevier]