Prediction of major adverse cardiovascular events following acute myocardial infarction using electrocardiogram DETERMINE score - Zeyan Liu; Jinglin Cheng; Shu Zhou; Xuexiang Li; Min Yang; Ye Zhang (BMC Cardiovascular Disorders)
Abstract Background Acute myocardial infarction (AMI) remains a major cause of mortality and morbidity globally, with a high incidence of major adverse cardiovascular events (MACE) post-primary percutaneous coronary intervention (PPCI). The DETERMINE score, derived from electrocardiographic (ECG) markers, has shown promise as a predictor of adverse outcomes, but its clinical utility requires further validation. Objective To evaluate the predictive value of the DETERMINE score for MACE and provide early clinical warnings for high-risk patients. Methods This bidirectional cohort study included AMI patients from the Second Affiliated Hospital of Anhui Medical University between 2019 and 2023. The training cohort comprised 545 patients between January 2019 and January 2023, while the validation cohort consisted of 122 patients between February 2023 and July 2023. The primary endpoint was MACE within one-year post-PPCI. The relationship between the DETERMINE score and MACE was analyzed using Cox regression, trend tests, and restricted cubic splines to assess linear and nonlinear associations. Patients were stratified into risk groups based on tertiles or optimal cutoffs, and Kaplan-Meier survival curves compared MACE incidence across groups. Predictive accuracy was evaluated through time-dependent C-index, ROC curves, decision curve analysis, and calibration, and compared to other prognostic scores, including the Selvester, GRACE, and SYNTAX scores, as well as left ventricular ejection fraction (LVEF). Subgroup analyses by sex, age, and culprit artery involvement were also conducted. Results Cox multivariate regression indicated that the DETERMINE score was an independent risk factor for MACE (HR = 1.56, 95% CI 1.38–1.75, P < 0.001). Trend test and RCS showed a positive correlation and non-linear relationship between the DETERMINE score and MACE (P-trend < 0.001, P-overall < 0.001, P-nonlinear: 0.003). Kaplan-Meier survival analysis revealed that, in both the training and validation datasets, groups with a higher DETERMINE score showed a higher cumulative risk of MACE. The DETERMINE score outperformed traditional prognostic scores (Selvester, GRACE, SYNTAX) in terms of predictive accuracy, with an AUROC of 0.840 at 12 months in the training cohort. The score also provided a substantial clinical net benefit, particularly over longer follow-up periods. Subgroup analyses confirmed its predictive power across different demographics and clinical presentations. Conclusion The DETERMINE score has outstanding predictive power for MACE post-PPCI, which can guide the early identification of high-risk patients with poor prognosis of AMI in clinical practice.