Key result
Model combining coronary stenosis, LVEDV, LVEF, TGF-beta, and cTnI predicts LV remodeling with ~0.98 AUC.
Why the study?
The study was conducted to develop a risk prediction model for left ventricular remodeling in patients with acute anterior STEMI.
Does a multiparametric risk prediction model improve prediction of left ventricular remodeling in patients with acute anterior ST-segment elevation myocardial infarction?
Observational (n=333)
No
Does a multiparametric risk prediction model improve prediction of left ventricular remodeling in patients with acute anterior ST-segment elevation myocardial infarction?
A multiparametric risk prediction model incorporating clinical, echocardiographic, and biomarker data provides excellent diagnostic accuracy for predicting left ventricular remodeling after acute anterior STEMI.
May aid post-anterior STEMI risk stratification; leaves open prospective validation before clinical adoption.
BACKGROUND The aim of the present study was to develop a risk prediction model in patients with acute anterior ST-segment elevation myocardial infarction (STEMI). MATERIAL AND METHODS Clinical data from 333 patients with acute anterior STEMI were retrospectively analyzed. Clinical echocardiographic and angiographic data from patients with left ventricular remodeling (LVR) and those without LVR were compared. Factors that influenced risk were identified using multivariate logistic regression analysis. The area under the curve (AUC) of the receiver operating characteristic curve was used to assess the diagnostic performance of the model. RESULTS After 6-month follow-up, 135 of the patients experienced LVR (LVR group), whereas 198 did not (non-LVR group). Results of multivariate analysis showed that the number of stenosed coronary vessels, left ventricular end-diastolic volume (LVEDV), left ventricular ejection fraction (LVEF), transforming growth factor-beta (TGF-ß) at admission, and cardiac troponin I 3 days after admission (3-d cTnI) were all factors predictive of LVR in patients with acute anterior STEMI (all P<0.05). The established prediction model was Y=-20.639+0.711×number of stenosed coronary vessels + 0.137×LVEDV-0.129×LVEF+0.026×TGF-ß at admission + 0.162×3-d cTnI. The estimated AUC of this model was 0.978 (95% confidence interval [CI] 0.955-0.991), significantly superior to the single-factor numbers for stenosed coronary vessel of 0.650 (95% CI 0.597-0.702), LVEDV of 0.876 (95% CI 0.836-0.910), LVEF of 0.684 (95% CI 0.631-0.734), TGF-ß at admission of 0.696 (95% CI 0.644-0.745), cTnI at admission of 0.913 (95% CI 0.877-0.941), and 3-d cTnI of 0.945 (95% CI 0.914-0.967). CONCLUSIONS The established model had excellent diagnostic accuracy for predicting LVR in patients with acute anterior STEMI.
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Liu et al. (2021) conducted an observational in Acute anterior ST-segment elevation myocardial infarction (STEMI) (n=333). Risk prediction model vs. Single-factor predictors was evaluated on Area under the curve (AUC) for predicting left ventricular remodeling (95% CI 0.955-0.991). A risk prediction model incorporating the number of stenosed coronary vessels, LVEDV, LVEF, TGF-beta at admission, and 3-day cTnI demonstrated excellent diagnostic accuracy for predicting left ventricular remodeling with an AUC of 0.978.
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