Predicting survival with good neurological recovery at hospital admission after successful resuscitation of out-of-hospital cardiac arrest: the OHCA score

Abstract

Aims: Out-of-hospital cardiac arrest (OHCA) is common and carries a bleak prognosis. Early prediction of unfavourable outcomes is difficult but crucial to improve resource allocation. The aim of this study was to develop a simple tool for predicting survival with good neurological function in the overall population of patients with successfully resuscitated cardiac arrest.

Methods and results: We used logistic regression analysis to identify clinical and laboratory variables that were both readily available at admission and predictive of poor outcomes (death or severe neurological impairment) in a development cohort of 130 consecutive OHCA patients admitted to a French intensive care unit (ICU) between 1999 and 2003. To test the prediction score built from these variables, we used a validation cohort of 210 patients recruited in four French ICUs between 2003 and 2005. Initial rhythm, estimated no-flow and low-flow intervals, blood lactate, and creatinine levels determined using whole blood analyzers were independently associated with poor outcomes and were used to build a continuous severity score. Goodness-of-fit tests indicated good performance (P=0.79 in the development cohort and P=0.13 in the validation cohort). The area under the receiver-operating characteristics curve was 0.82 in the development cohort and 0.88 in the validation cohort.

Conclusion: The outcome can be accurately predicted after OHCA using variables that are readily available at ICU admission.