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1: Prehosp Emerg Care. 2008 Jul-Sep;12(3):347-51.Click here to read Links

Derivation of clinical predictors of failed rescue shock during out-of-hospital ventricular fibrillation.

Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15213, USA. menegazzijj@upmc.edu

BACKGROUND: Failed rescue shocks have been shown to decrease the likelihood of survival in the treatment of out-of-hospital ventricular fibrillation (VF). Avoidance of failed shocks may improve survival. OBJECTIVE: We sought to derive clinical predictors that could be used by emergency medical services (EMS) personnel to identify a subset of VF patients whose first rescue shock is likely to fail, making them candidates for a cardiopulmonary resuscitation (CPR)-first strategy. METHODS: After gaining institutional review board approval from all three institutions, we merged data from Los Angeles, Pittsburgh, and Royal Oak into a new cardiac arrest database. We used classification and regression tree (CART) analyses to build the model. We defined a failed first rescue shock as one in which there was no return of spontaneous circulation (ROSC); the postshock electrocardiographic (ECG) rhythm was VF, pulseless electrical activity (PEA), or asystole; or subsequent shocks were delivered (indicating that the first shock had failed). RESULTS: The database contains 5,046 cases, of which 1,777 (35%) had VF as the initial ECG rhythm. Sufficient data were present for 748 cases. Using unwitnessed collapse, a response time of >6 minutes, and absence of bystander CPR (BCPR) on EMS arrival as predictors, 35 of 35 (100%, 95% confidence interval [CI] 100-91.4%) cases had failed first rescue shocks. Second shock failure was predicted in 162 of 164 (99%) cases. CONCLUSIONS: Unwitnessed collapse, response time>6 minutes, and absence of BCPR may be useful in predicting which VF patients are likely to have failed first shocks and would thereby benefit from a CPR-first strategy. Stacked rescue shocks most often fail, and this outcome can also be predicted.

PMID: 18584503 [PubMed - indexed for MEDLINE]