ArticleInternational journal of general medicine2026
Integration of 2D Speckle Tracking Strain and Clinical Indicators for Early Prediction of Post-PCI Heart Failure in Patients with STEMI and Type 2 Diabetes.
Article in International journal of general medicine, 2026. 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
Background: Patients with ST-segment elevation myocardial infarction (STEMI) and type 2 diabetes mellitus (T2DM) are at increased risk of heart failure after percutaneous coronary intervention (PCI). Early identification of high-risk individuals remains challenging. This study aimed to develop a prediction model integrating two-dimensional speckle tracking imaging (2D-STI) and clinical variables to improve risk stratification. Methods: A total of 328 T2DM patients with STEMI who underwent PCI were retrospectively analyzed. Clinical, laboratory, and 2D-STI parameters were collected within one week after PCI. Heart failure within one year was the study endpoint. LASSO regression followed by Boruta analysis was used to identify key predictors. A multivariable logistic model was established, visualized by a nomogram, and evaluated using ROC curves, reclassification indices, calibration, and decision curve analysis. Results: Heart failure occurred in 62 patients (18.9%). Six variables-GLS, HbA1c, BMI, eGFR, hs-CRP, and diabetes duration-were identified as core predictors. GLS showed the highest individual discriminative ability (AUC = 0.798). The combined model achieved an AUC of 0.861, significantly outperforming the base model (AUC = 0.803, Conclusion: Integrating GLS with clinical, metabolic, inflammatory, and renal indicators significantly improves early prediction of post-PCI heart failure in T2DM patients with STEMI, offering a practical tool for individualized risk assessment.
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