Identifying prognostic factors in patients with cardiogenic shock undergoing VA-ECMO treatment: insights from ECLS-SHOCK using machine learning

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Abstract Background/Introduction Venoarterial extracorporeal membrane oxygenation (VA-ECMO) has not been shown to reduce short-term mortality in patients with acute myocardial infarction complicated by cardiogenic shock. However, whether some patients might benefit from VA-ECMO remains to be cleared. Purpose To identify the impact of VA-ECMO therapy on outcomes by leveraging the potential of machine learning. Methods The ECLS-SHOCK trial is a randomized controlled trial where patients with acute myocardial infarction complicated by cardiogenic shock for whom early revascularization was planned were randomly assigned to receive early VA-ECMO plus usual medical treatment or usual medical treatment alone. The primary outcome was death from any cause at 30 days. Extreme gradient boosting (XGBoost) was used to develop a model for the prediction of 30-day all-cause mortality and to assess the influence of VA-ECMO on outcomes. Results Overall, 209 patients were randomized to the VA-ECMO and 208 to control. Baseline characteristics between groups were well balanced (median age 63 years, 81% male, 67% presenting with ST-segment elevation myocardial infarction). At 30-days 100 patients in the VA-ECMO and 102 in the control group were dead. The final XGBoost model contained 27 variables and the 10 most influential variables are shown in Fig. 1. On derivation the model predicted mortality with an AUC of 1.00 and on validation with an AUC of 0.80 (95% CI 0.71 to 0.89), with a sensitivity of 95% (95% CI 88% to 100%) and a specificity of 55% (40% to 69%), resulting in a positive predictive value of 65% and a negative predictive value of 92% at a Youden-derived cut-off. Importantly, neither the VA-ECMO therapy nor its complications were among the most influential factors of the model with a relative importance of 1.1% for VA-ECMO therapy and 0.25% for peripheral vascular complications and bleeding complications even being discarded by the model. Conclusion In patients with acute myocardial infarction complicated by cardiogenic shock the influence of VA-ECMO therapy on 30-day mortality, even when investigated with complex machine learning models, is negligibly low.