Design of a new mortality indicator in acute coronary syndrome on admission to the Intensive Care Unit

Objective: To design a mortality indicator for acute coronary syndrome (ACS) in the intensive care unit (ICU).Design: Multicenter observational descriptive study.Participants: ACS patients admitted to SMI included in the ARIAM-SEMICYUC registry between January 2013 and April 2019. Interventions: None.Main variables of interest: Variables analyzed were demographic, time of access to the health system, and clinical condition. Revascularization therapy, drugs, and mortality were analyzed. A COX regression analysis was performed and subsequently a neural network was designed. An ROC curve was developed to calculate the power of the new score. Finally, the clinical utility or relevance of the ARIAM's indicator will be evaluated using a Fagan test.Results: 17,258 patients were included, with a 3.5% (605) mortality at discharge from the ICU. The variables analyzed with statistical significance (p < 0.001) were entered into the supervised predictive model, an artificial neural network. The new ARIAM's indicator showed a mean of 0.0257 (95% CI: 0.0245-0.0267) in patients discharged from the ICU and 0.27085 (95% CI: 0.2533-0.2886) in those who died, p < 0.001. The ROC area of the model achieved was 0.918 (95% CI: 0.907-0.930). The Fagan test showed that the ARIAM's Indicator shows that the probability of death is 19% (95% CI: 18%-20%) when it is positive and 0.9% (95% CI: 0.8%-1.01%) when it is negative.Conclusions: It is possible to create a new mortality indicator for ACS in the ICU that is more accurate, reproducible, and periodically updated.(c) 2023 Elsevier Espana, S.L.U. y SEMICYUC. All rights reserved.