Predicting the outcomes for out-of-hospital cardiac arrest patients using multiple biomarkers and suspension microarray assays

Abstract

Predicting the prognosis for cardiac arrest is still challenging. Combining biomarkers from diverse pathophysiological pathways may provide reliable indicators for the severity of injury and predictors of long-term outcomes. We investigated the feasibility of using a multimarker strategy with key independent biomarkers to improve the prediction of outcomes in cardiac arrest. Adult out-of-hospital cardiac arrest patients with sustained return of spontaneous circulation were prospectively enrolled in this study. Blood samples were taken at 2 and 24 hours after cardiac arrest. Suspension microarray assays were used to test 21 different biomarkers. A total of 99 patients were enrolled, 45 of whom survived to hospital discharge. We identified 11 biomarkers that, when combined with clinical variables and factors of APACHE II score and history of arrhythmia, were independent determinants for outcome of in-hospital mortality (concordance = 0.9249, standard error = 0.0779). Three biomarkers combined with APACHE II and age were independent determinants for favorable neurological outcome at hospital discharge (area under the receiver-operator characteristic curve, 0.938; 95% confidence interval, 0.854 similar to 1.0). In conclusion, a systemic multiple biomarker approach using suspension microarray assays can identify independent predictors and model the outcomes of cardiac arrest patients during the post-cardiac arrest period.