Abstract P160: Prognostic Indicators and Outcome Prediction Model for Patients With Return of Spontaneous Circulation (ROSC) From Caldiopulmonary Arrest(CPA): Osaka Utstein Project
Introduction: Although some prognostic indicators for patients with out-of-hospital cardiopulmonary arrest (CPA) have been proposed, a mathematical model with high predictive value has not been established. The purpose of the present study was to determine the most important indicators of prognosis in patients with return of spontaneous circulation (ROSC) from CPA, and to develop a best outcome prediction model.
Methods: All patients were prospectively recorded based on the Utstein style in Osaka during 2 years (2005–2006). The criteria for inclusion were a witnessed cardiac arrest, an age of higher than 17 years old, a presumed cardiac origin of the arrest, and successful ROSC. Multivariate logistic regression (MLR) analysis was used to identify independent factors for a good outcome and to develop the best prediction model according to the Akaike Information Criterion (AIC) in patients with initial rhythm of VF or PEA/Asystole (PEA/Asys) separately. The dependant variables were favorable outcome (cerebral-performance category (CPC):1–2) and poor outcome (CPC: 3–5) at one month after the event. Eight explaining pre-hospital variables were used, concerning patient characteristics and resuscitation. External validation was performed on an independent set of Utstein data in 2007.
Results: The 285 patients in VF and 577 patients in PEA/Asys were included. Favorable outcome were 32.7 % (91/282) in VF, and 5.7% (33/575) in PEA/Asys, respectively. MLR found as the most important prognostic indicators, age (p=0.09), time from the collapse to ROSC (TROSC) (p<0.01), presence of pre-hospital ROSC (PROSC) (p=0.15) in VF, and age (p=0.027), TROSC (p<0.01), PROSC (p<0.01), conversion to VF (p=0.012) in PEA/Asys. Two hundred ten patients in VF and 417 patients in PEA/Asys were included in external validation data set. The area under the ROC curve were 0.867 in VF, and 0.873 in PEA/Asys on the external validation data.
Conclusions: The most important prognostic indicators of patients with ROSC from VF were age, TROSC, and PROSC, those from PEA/Asys were age, TROSC, PROSC, and conversion to VF. The model based on those indicators showed high predictive value for CPA patients with ROSC.