ArticleEuropean journal of medical research2025
A nomogram risk prediction model for ischemic mitral regurgitation after primary percutaneous coronary intervention in patients with ST-segment elevation myocardial infarction.
Article in European journal of medical research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
aimThis study developed a nomogram to predict the risk of ischemic mitral regurgitation (IMR) after percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI) patients and evaluate their long-term prognosis.
methodsData from 342 STEMI patients were collected. Logistic regression identified independent risk factors for IMR during hospitalization, while Cox regression assessed risk factors during follow-up. The nomogram was developed based on these factors. ROC evaluated its predictive value, and decision curve analysis/clinical impact curves assessed clinical utility. Kaplan-Meier analysis evaluated the model's prognostic value.
resultsThe independent risk factors for hospitalized IMR after PCI in STEMI patients included Gensini score (OR 1.009; P = 0.047), left ventricular ejection fraction (LVEF) (OR 0.941; P = 0.007), albumin (OR 0.941; P = 0.046), and systemic immune-inflammatory index (SII) (OR 1.096; P < 0.001). During follow-up, diabetes mellitus (HR: 1.154; P = 0.019), hemoglobin (HR: 0.991; P = 0.028), Gensini score (HR: 1.007; P = 0.022), LVEF (HR: 0.972; P = 0.015), and SII/100 (HR: 1.034; P < 0.001) were identified as independent predictors of IMR. The nomogram showed strong clinical benefit, good calibration, and predictive value. Patients with lower scores had better long-term outcomes.
conclusionThis nomogram effectively predicts the occurrence of IMR after PCI in STEMI patients, providing valuable prognostic insights.
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