Pérez-Castellanos A, Martínez-Sellés M, Uribarri A, Devesa-Cordero C, Sánchez-Salado JC, Ariza-Solé A, Sousa I, Juárez M, Fernández-Avilés F. Development and External Validation of an Early Prognostic Model for Survivors of Out-of-hospital Cardiac Arrest.
REVISTA ESPANOLA DE CARDIOLOGIA (ENGLISH ED.) 2019;
72:535-542. [PMID:
30001950 DOI:
10.1016/j.rec.2018.05.022]
[Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2017] [Accepted: 05/14/2018] [Indexed: 06/08/2023]
Abstract
INTRODUCTION AND OBJECTIVES
Despite therapeutic hypothermia, unconscious survivors of out-of-hospital cardiac arrest have a high risk of death or poor neurologic function. Our objective was to assess the usefulness of the variables obtained in the early moments after resuscitation in the prediction of 6-month prognosis.
METHODS
A multicenter study was performed in 3 intensive cardiac care units. The analysis was done in 153 consecutive survivors of out-of-hospital cardiac arrest who underwent targeted temperature management between January 2007 and July 2015. Significant neurological sequelae at 6 months were considered to be present in patients with Cerebral Performance Categories Scale > 2. An external validation was performed with data from 91 patients admitted to a third hospital in the same time interval.
RESULTS
Among the 244 analyzed patients (median age, 60 years; 77.1% male; 50.0% in the context of acute myocardial ischemia), 107 patients (43.8%) survived with good neurological status at 6 months. The prediction model included 5 variables (Shockable rhythm, Age, Lactate levels, Time Elapsed to return of spontaneous circulation, and Diabetes - SALTED) and provided an area under the curve of 0.90 (95%CI, 0.85-0.95). When external validation was performed, the predictive model showed a sensitivity of 73.5%, specificity of 78.6%, and area under the curve of 0.82 (95%CI, 0.73-0.91).
CONCLUSIONS
A predictive model that includes 5 clinical and easily accessible variables at admission can help to predict the probability of survival without major neurological damage following out-of-hospital cardiac arrest.
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