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ArticleRisk management and healthcare policy2025

Retrospective Cohort Study: Nomogram for 1-Year in-Stent Restenosis After PCI in Coronary Heart Disease.

Xin-Fu Cao, Dao-Hai Chen, Ya-Li Qiu, Chao Tang, Xiao-Long Li, Zhen-Hua Gu

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Article in Risk management and healthcare policy, 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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5 · Who and what money

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6 authors.

Xin-Fu CaoDepartment of Cardiology, Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine, Changzhou, Jiangsu, People's Republic of China.
Dao-Hai ChenDepartment of Cardiology, Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine, Changzhou, Jiangsu, People's Republic of China.
Ya-Li QiuDepartment of Respiratory and Critical Care Medicine, Changzhou Third People's Hospital, Changzhou, Jiangsu, People's Republic of China.
Chao TangDepartment of Cardiology, The Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, People's Republic of China.
Xiao-Long LiDepartment of Cardiology, Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine, Changzhou, Jiangsu, People's Republic of China.
Zhen-Hua GuDepartment of Cardiology, Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine, Changzhou, Jiangsu, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To construct a nomogram for risk prediction of in-stent restenosis (ISR) within one year after percutaneous coronary intervention (PCI) for coronary heart disease (CHD). Methods: This study included 842 patients with severe CHD who underwent PCI at Changzhou Affiliated Hospital of Nanjing University of Chinese Medicine between March 2016 to March 2024. Based on the occurrence of ISR within one year post-PCI, patients were stratified into two groups: the ISR group (n=112) and the non-ISR group (n=730). Potential risk factors were initially identified using LASSO regression, followed by multivariate logistic regression to determine independent predictors. A nomogram prediction model was developed using R software (version 4.2.6) and internally validated via the bootstrap resampling method (1000 iterations). Model performance was assessed through receiver operating characteristic (ROC) curve analysis, calibration curve analysis, and decision curve analysis (DCA). Results: This analysis revealed seven risk factors for ISR: diabetes (OR=1.380, 95% CI: 1.090-1.747), neutrophil/lymphocyte ratio (NLR, OR=2.312, 95% CI: 1.830-2.922), low-density lipoprotein (LDL) > 1.8 mmol/L (OR=2.159, 95% CI: 1.080-4.315), calcified lesions (OR=3.780, 95% CI: 2.051-6.968), stent diameter <3 mm (OR=2.595, 95% CI: 1.404-4.796), smoking (OR=2.796, 95% CI: 1.511-5.174) and no intravascular ultrasound (IVUS) assisted (OR=2.176, 95% CI: 1.342~3.257). These seven factors were incorporated into the nomogram model. The model demonstrated excellent discriminative ability, with an area under the curve (AUC) of 0.892 (95% CI: 0.859-0.924) and a consistency index (C-index) of 0.923. Calibration analysis showed close agreement between predicted and observed outcomes, while DCA indicated strong clinical utility across a wide probability threshold range (5.0%-86.2%). The relative importance of the risk factors, ranked in descending order, was as follows: calcified lesions, stent diameter <3 mm, no IVUS assisted, LDL>1.8 mmol/L, smoking, NLR and diabetes. Conclusion: The study identifies several risk factors for ISR in CHD patients within one year after PCI. The constructed nomogram model has good predictive efficiency and clinical applicability.

Indexed as

coronary heart diseasein-stent restenosisnomogram modelpercutaneous coronary interventionrisk factors

Identifiers

PMID40823265
PMCPMC12356208

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