BMC cardiovascular disorders · 2026
Predictive value of multivariate models of quantitative myocardial movement parameters for acute myocardial infarction in elderly patients with coronary artery disease.
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Chen Qiang, Li Borui, Zhu Ximei, Jiang Liyan, Liu Chen, Zhu Jing
Аннотация
OBJECTIVE: This study aimed to investigate the association of multivariate models encompassing quantitative myocardial movement parameters with the risk of subsequent acute myocardial infarction (AMI) within 3 months in elderly patients with coronary artery disease (CAD), and to explore their potential predictive value.
METHODS: We conducted a retrospective case-control study involving 280 elderly patients diagnosed with CAD, 110 of whom developed AMI within three months post examination (AMI group) and 170 who did not developed AMI. The two groups underwent echocardiographic measurements of several parameters.
RESULTS: Significant differences were observed in echocardiographic parameters between the AMI and non-AMI groups. Parameters such as ejection fraction, stroke volume, end-systolic volume, end-diastolic volume, and left ventricular wall measurements effectively distinguished patients who developed AMI from those who did not. A joint model yielded an AUC value of 0.985 in the ROC analysis, indicating good predictive performance. Internal validation using bootstrap gave an optimism-corrected AUC of 0.901 (95% CI: 0.872-0.926). The Hosmer‑Leme show test indicated good calibration (χ²=8.32, p = 0.402), and decision curve analysis demonstrated potential clinical usefulness across a range of threshold probabilities.
CONCLUSION: Our results suggest a potential for using multivariate models of myocardial movement parameters to predict the risk of AMI in CAD patients. However, owing to the retrospective design and the lack of external validation, these findings should be considered hypothesis‑generating and require prospective validation in independent cohorts. Incorporation of these echocardiographic measurements into routine medical assessments may offer a potentially effective, non-invasive way to improve early detection and management of AMI in patients with CAD.
METHODS: We conducted a retrospective case-control study involving 280 elderly patients diagnosed with CAD, 110 of whom developed AMI within three months post examination (AMI group) and 170 who did not developed AMI. The two groups underwent echocardiographic measurements of several parameters.
RESULTS: Significant differences were observed in echocardiographic parameters between the AMI and non-AMI groups. Parameters such as ejection fraction, stroke volume, end-systolic volume, end-diastolic volume, and left ventricular wall measurements effectively distinguished patients who developed AMI from those who did not. A joint model yielded an AUC value of 0.985 in the ROC analysis, indicating good predictive performance. Internal validation using bootstrap gave an optimism-corrected AUC of 0.901 (95% CI: 0.872-0.926). The Hosmer‑Leme show test indicated good calibration (χ²=8.32, p = 0.402), and decision curve analysis demonstrated potential clinical usefulness across a range of threshold probabilities.
CONCLUSION: Our results suggest a potential for using multivariate models of myocardial movement parameters to predict the risk of AMI in CAD patients. However, owing to the retrospective design and the lack of external validation, these findings should be considered hypothesis‑generating and require prospective validation in independent cohorts. Incorporation of these echocardiographic measurements into routine medical assessments may offer a potentially effective, non-invasive way to improve early detection and management of AMI in patients with CAD.