ArticleFrontiers in cardiovascular medicine2026
Construction and validation of a prediction model for in-stent restenosis following coronary stent implantation during dual antiplatelet therapy.
Article in Frontiers in cardiovascular 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
Objectives: In-stent restenosis (ISR) is a serious complication that occurs after a percutaneous coronary intervention (PCI). This study aims to integrate thromboelastography (TEG) parameters, coagulation function, and clinical indicators to develop and validate a prediction model for ISR during antiplatelet therapy after PCI. Method: A total of 401 consecutive patients with coronary artery disease who underwent a PCI with drug-eluting stent implantation between January 2018 and January 2024 were enrolled in this study. Clinical baseline characteristics were collected. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used to screen 6 key predictors from 34 candidate clinical features. Multivariate logistic regression identified independent risk factors for ISR. Model performance was evaluated using the receiver operating characteristic curve for discrimination, bootstrap internal validation for stability, the Hosmer-Lemeshow test for goodness of fit, and decision curve analysis for clinical utility. Results: Among the 401 enrolled patients, 137 (34.2%) developed ISR. LASSO regression selected 6 key predictors from 34 candidate variables. Multivariable logistic regression ultimately identified a low adenosine diphosphate (ADP) inhibition rate, a low arachidonic acid (AA) inhibition rate, reaction time ( Conclusions: The prediction model, constructed based on TEG parameters (ADP inhibition rate, AA inhibition rate,
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