Evidence map›Paper›PMID 42310545›Full record

ArticleBMC cardiovascular disorders2026

Development and validation of a predictive model for side branch flow impairment following stent implantation in patients with non-left main coronary bifurcation lesions: a retrospective analysis.

Linlin Wang, Haoran Zhang, Aoxue Mei, Shuang Xie, Xintong Han, Lanqi Zeng, Jiamei Liu, Yang Jiao, Ying Zhang

Abstract readValidation Study
In one paragraph

Article in BMC cardiovascular disorders, 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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5 · Who and what money

Authors and funding

9 authors.

Linlin WangDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Haoran ZhangDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Aoxue MeiDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Shuang XieDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Xintong HanDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Lanqi ZengDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Jiamei LiuDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Yang JiaoDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China.
Ying ZhangDepartment of Cardiology, The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China. cyfyzy@126.com.

Funding

the Government Funded Clinical Medicine Talent Training Project ZF2023252
6 · The paper itself

Abstract

objectivesThe purpose of this study was to develop and validate a predictive model to assessing the risk of side branch flow impairment (SBFI) following stent implantation in patients with non-left main coronary bifurcation lesions (CBLs). This model aims to provide preprocedural risk stratification and inform the selection of interventional strategies.

backgroundCoronary artery bifurcation lesions constitute a particularly complex subtype of coronary artery disease that is frequently encountered in practice. Compared with non-bifurcation lesions, they are associated with greater procedural complexity and risk of procedure-related complications. PATIENTS AND

methodsData from 830 patients with CBL who underwent percutaneous coronary intervention (PCI) in the Affiliated Hospital of Chengde Medical University from January 2022 to December 2023 were retrospectively collected. The least absolute shrinkage and selection operator regression methods were used to screen variables, and multivariate logistic regression was used to establish a predictive model. A nomogram was built based on these factors and internally verified using the bootstrap resampling method. The C-statistic was used to verify and evaluate the discriminative ability of the model; the calibration curve was drawn, and the decision curve analysis (DCA) was performed to evaluate the calibration degree, clinical net benefit, and practicability of the model. The primary endpoint was SBFI, defined as a transient or persistent reduction in thrombolysis in myocardial infarction (TIMI) flow grade in a branch vessel following stent implantation in a major non-left main coronary artery.

resultsA nomogram was constructed using the selected predictors of SBFI, which included age, plaque location ipsilateral to the SB, TIMI flow grade before main vessel (MV) stenting, and N-terminal pro-brain natriuretic peptide (NT-proBNP). The discriminatory ability of the model, as assessed by the area under the curve (AUC), was 0.651. The robustness of the model was evaluated through internal validation with 1000 bootstrap replicates, resulting in a corrected AUC of 0.641. The calibration curve, evaluated by the Hosmer-Lemeshow test, showed good agreement between predictions and observations (χ

conclusionWe developed and validated a predictive model for SBFI after PCI in non-left main bifurcation lesions. The model exhibited modest discriminative ability, calibration, and a positive net benefit on DCA, suggesting that it may serve as a valuable risk stratification tool in clinical practice.

Indexed as

Coronary Artery DiseaseCoronary CirculationDecision Support TechniquesNomogramsPercutaneous Coronary InterventionStentsAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsCoronary artery diseaseCoronary bifurcation lesionsPercutaneous coronary interventionPredictive modelSide branch flow impairment

Identifiers

PMID42310545
PMCPMC13576310

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