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External Validation of Survival-Predicting Models for Acute Myocardial Infarction with Extracorporeal Cardiopulmonary
Lei Huang1, Tong Li1, Xiao-Min Hu1
1Heart Center, Tianjin Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Artificial Cell Engineering Technology Research Center of Public Health Ministry, Tianjin, China (mainland).
Abstract:
BACKGROUND This study was designed as an external evaluation of potentially relevant models for acute myocardial infarction (AMI) with extracorporeal cardiopulmonary resuscitation (E-CPR). MATERIAL AND METHODS Twenty AMI adults that met criteria were retrospectively analyzed from January 2009 to January 2015. Six possible models - ENCOURAGE, SAVE, ECPR, GRACE, SHOCK, and a simplified risk chart - were identified by literature review and model scores calculated based on original data. Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment, commonly used in intensive care units, served as controls. A receiver operating characteristic curve was used to compare the models' discriminative power for predicting survival to discharge. RESULTS The ECPR model showed the best discriminative performance, with an area under the curve (AUC) of 0.893 (95% confidence interval [CI], 0.733-1.530, p=0.006); the cutoff was 12.5 points, with 66.7% sensitivity and 100% specificity. The "clinical" SHOCK model (including infarct site) showed weaker but still good discriminative power, with an AUC of 0.804 (95% CI, 0.580-1.027, p=0.035); the cutoff was 45.5 points, with 83.3% sensitivity and 71.4% specificity. The remaining models did not show significant discriminative power for predicting survival to discharge. Risk stratifications indicated that a statistically significant difference was observed in the distribution of patients into the ECPR group with different prognoses when stratified by its cutoff (p=0.003), while a trend of significant difference was shown when applied to the SHOCK model (p=0.05). CONCLUSIONS The ECPR and SHOCK models possess important abilities to predict intrahospital outcomes of AMI patients treated with E-CPR.
