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Hemodynamic forces provide incremental predictive value for left ventricular remodeling after STEMI
Miao Hu1, Xiuzheng Yue1, Yinyin Chen2
1Medical Big Data Research Center, Medical Innovation Research Division of PLA General Hospital, Beijing, China; Chinese PLA Medical School, Chinese PLA General Hospital, Beijing, China.
Purpose:
This study aimed to determine the prognostic significance of cardiac magnetic resonance (CMR)-derived Hemodynamic forces (HDF) parameters for adverse left ventricular remodeling (ALVR) in patients following ST-segment elevation myocardial infarction (STEMI) and to compare their predictive value with conventional risk markers.
Methods:
147 STEMI patients from two hospitals underwent CMR within 7 days and at 5 months post-percutaneous coronary intervetion (PCI). ALVR was defined as a ≥ 15% increase in left ventricular end-systolic volume. Baseline clinical, conventional CMR, strain, and HDF parameters were analyzed. Three multivariate logistic regression models were constructed: Model 1 (traditional parameters), Model 1 + strains, and Model 1 + HDF parameters, to assess incremental predictive value for ALVR.
Results:
In the multivariable regression model incorporating traditional parameters, strain, and HDF parameters, infarct percentage (OR: 1.127, 95% CI: 1.048-1.213, P = 0.001) and systolic HDF impulse (OR: 0.757, 95% CI: 0.629-0.911, P = 0.003) remained independent predictors of ALVR. Adding systolic HDF impulse to LVEF and infarct percentage significantly increased the AUC from 0.745 to 0.799 (P < 0.001). In contrast, the inclusion of myocardial global circumferential strain (MyoGCS) did not provide incremental value. Consistent with these findings, the likelihood ratio test confirmed that adding systolic HDF impulse significantly improved model performance (P = 0.004), whereas adding MyoGCS did not (P = 0.310).
Conclusion:
Systolic HDF impulse provides prognostic value beyond conventional markers, including infarct percentage and LVEF, supporting its potential utility for improving post-infarction risk stratification.