Prediction of major adverse cardiovascular events following acute myocardial infarction using electrocardiogram DETERMINE score
Zeyan Liu1,2, Jinglin Cheng3,4, Shu Zhou3
1Department of Emergency Internal Medicine, Second Affiliated Hospital of Anhui Medical University, Hefei, China. jy02893741@163.com.
Insights
The DETERMINE score effectively predicts major adverse cardiovascular events (MACE) after acute myocardial infarction (AMI) treatment. This electrocardiogram-based score aids in early identification of high-risk patients, improving clinical practice.
Area of Science:
- Cardiology
- Clinical Prediction
- Electrocardiography
Background:
- Acute myocardial infarction (AMI) is a leading cause of global mortality.
- Major adverse cardiovascular events (MACE) are common after primary percutaneous coronary intervention (PPCI).
- The DETERMINE score, based on electrocardiogram (ECG) markers, requires further validation for predicting adverse outcomes.
Purpose of the Study:
- To assess the DETERMINE score's ability to predict MACE in AMI patients.
- To validate the DETERMINE score for early risk stratification post-PPCI.
- To compare the DETERMINE score against existing prognostic tools.
Main Methods:
- A bidirectional cohort study of 667 AMI patients (545 training, 122 validation).
- Analysis of MACE within one year post-PPCI using Cox regression and Kaplan-Meier curves.
- Evaluation of predictive accuracy via C-index, ROC curves, and decision curve analysis, comparing with Selvester, GRACE, SYNTAX scores, and LVEF.
Main Results:
- The DETERMINE score is an independent predictor of MACE (HR=1.56, P<0.001).
- A positive, non-linear association exists between the DETERMINE score and MACE risk.
- The DETERMINE score demonstrated superior predictive accuracy (AUROC 0.840) and clinical utility compared to traditional scores.
Conclusions:
- The DETERMINE score exhibits strong predictive power for MACE following PPCI.
- It enables early identification of high-risk AMI patients with poor prognosis.
- The score can significantly enhance clinical decision-making in AMI management.
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.
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