Modified shock index as a clinical predictor of in-hospital mortality in patients with acute coronary syndrome

Introduction Acute coronary syndrome (ACS) is a highly prevalent pathology worldwide and in our country, being the leading cause of mortality and disability globally. Multiple scales have been developed to estimate the risk of complications and mortality associated with the development of ischemic heart disease; however, many of these require para-clinical tests, which in low-resource settings demand time that could potentially delay decision-making in patients at elevated risk of mortality. The modified shock index (MSI) is a widely used tool to predict the risk of mortality in patients with medical and surgical pathologies. Some observational studies have shown that the modified shock index could be useful in predicting in hospital mortality in patients with acute coronary syndrome; however, there are no studies in our population that evaluate its utility in this scenario. Purpose To evaluate the ability of the MSI to predict the risk of in-hospital mortality in patients with acute coronary syndrome. Methods A retrospective cohort study design was used, employing secondary data provided by a Tertiary care hospital in Colombia. Patients older than 18 years who were admitted to the emergency service with a diagnosis of acute coronary syndrome, underwent coronary arteriography, and had obstructive coronary artery disease were included. Patients with incomplete clinical records, other types of circulatory shock, or cardiogenic shock at emergency department admission were excluded. Results A total of 404 individuals were recruited, with an in-hospital mortality rate of 8.9%. Receiver operating characteristic (ROC) curve analysis showed that an MSI ≥ 0.99 had good performance for predicting in-hospital mortality, with an area under the curve (AUC) of 0.86 (95% CI: 0.81–0.92). The optimal cutoff point was 0.99, determined by a Youden index of 59.4, with a sensitivity of 72.2% (95% CI: 58–86) and a specificity of 86.9% (95% CI: 84–90). The positive predictive value (PPV) was 35.1% (95% CI: 25–45), while the negative predictive value (NPV) reached 97.0% (95% CI: 95–99). Conclusions The MSI showed good discriminatory ability to predict in-hospital mortality in the evaluated population, even after adjustment for potential confounding variables. This suggests that the MSI could be incorporated into the comprehensive risk assessment battery for patients with ACS, particularly to identify those at higher 12 risk of death who may benefit from early intervention. This single-center retrospective cohort study has limited external validity; therefore, new multicenter studies are needed to confirm the usefulness of the MSI in different populations.