Early prediction of prognosis in out-of-hospital cardiac arrest

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Abstract
Of 347 victims of out-of-hospital cardiac arrest 196 (56.5%) died before and 109 (31.4%) after admission to hospital, while 42 patients (12.1%) were discharged alive. The 37 patients (10.7%) discharged without severe hypoxic brain damage were assigned to the group with “good”, the remaining 310 patients to the group with “poor outcome”. From results of stepwise logistic regression, a score was derived to specifically identify victims with poor prognosis (values in brackets=score points; cutpoint: score>3 points): age≤70 (0), 71–80 (1), >80 (2); ECG ventricular fibrillation (0), other (1); no aspiration (0), aspiration (1); pupils round (0), not round (1); gasping (0), apnea (1); bystander resuscitation — yes (0), no (1). Evaluation of the score revealed a specificity of 100% (0.95 confidence interval: 80%–100%) and predictive value of 100% (0.95 confidence interval: 95%–100%). A predictive score for specific identification of victims with poor prognosis can contribute to decision making in out-of-hospital cardiac arrest.