Junyan Zhang, Zhongxiu Chen, Ran Liu, Yuxiao Li, Hongsen Zhao, Yanning Li, Minggang Zhou, Hua Wang, Chen Li, Li Rao, Yong He
{"title":"用于预测接受经皮冠状动脉介入治疗的高出血风险患者长期临床不良事件的提名图的开发与验证。","authors":"Junyan Zhang, Zhongxiu Chen, Ran Liu, Yuxiao Li, Hongsen Zhao, Yanning Li, Minggang Zhou, Hua Wang, Chen Li, Li Rao, Yong He","doi":"10.31083/RCM25352","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Patients with a high risk of bleeding undergoing percutaneous coronary intervention (PCI-HBR) were provided consensus-based criteria by the Academic Research Consortium for High Bleeding Risk (ARC-HBR). However, the prognostic predictors in this group of patients have yet to be fully explored. Thus, an effective prognostic prediction model for PCI-HBR patients is required.</p><p><strong>Methods: </strong>We prospectively enrolled PCI-HBR patients from May 2022 to April 2024 at West China Hospital of Sichuan University. The cohort was randomly divided into training and internal validation sets in a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was employed to select variables in the training set. Subsequently, a prediction model for 1-year net adverse clinical events (NACEs)-free survival was developed using a multivariable Cox regression model, and a nomogram was constructed. The outcome of the NACEs is defined as a composite endpoint that includes death, myocardial infarction, ischemic stroke, and Bleeding Academic Research Consortium (BARC) grade 3-5 major bleeding. Validation was conducted exclusively using the internal validation cohort, assessing the discrimination, calibration, and clinical utility of the nomogram.</p><p><strong>Results: </strong>This study included 1512 patients with PCI-HBR, including 1058 in the derivation cohort and 454 in the validation cohort. We revealed five risk factors after LASSO regression, Cox regression, and clinical significance screening. These were then utilized to construct a prognostic prediction nomogram, including chronic kidney disease, left main stem lesion, multivessel disease, triglycerides (TG), and creatine kinase-myocardial band (CK-MB). The nomogram exhibited strong predictive ability (the area under the curve (AUC) to predict 1-year NACE-free survival was 0.728), displaying favorable levels of accuracy, discrimination, and clinical usefulness in the internal validation cohort.</p><p><strong>Conclusions: </strong>This study presents a nomogram to predict 1-year NACE outcomes in PCI-HBR patients. Internal validation showed strong predictive capability and clinical utility. Future research should validate the nomogram in diverse populations and explore new predictors for improved accuracy.</p><p><strong>Clinical trial registration: </strong>The data for this study were obtained from the PPP-PCI registry, NCT05369442 (https://clinicaltrials.gov/study/NCT05369442).</p>","PeriodicalId":20989,"journal":{"name":"Reviews in cardiovascular medicine","volume":"26 1","pages":"25352"},"PeriodicalIF":1.9000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11760544/pdf/","citationCount":"0","resultStr":"{\"title\":\"Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention.\",\"authors\":\"Junyan Zhang, Zhongxiu Chen, Ran Liu, Yuxiao Li, Hongsen Zhao, Yanning Li, Minggang Zhou, Hua Wang, Chen Li, Li Rao, Yong He\",\"doi\":\"10.31083/RCM25352\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Patients with a high risk of bleeding undergoing percutaneous coronary intervention (PCI-HBR) were provided consensus-based criteria by the Academic Research Consortium for High Bleeding Risk (ARC-HBR). However, the prognostic predictors in this group of patients have yet to be fully explored. Thus, an effective prognostic prediction model for PCI-HBR patients is required.</p><p><strong>Methods: </strong>We prospectively enrolled PCI-HBR patients from May 2022 to April 2024 at West China Hospital of Sichuan University. The cohort was randomly divided into training and internal validation sets in a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was employed to select variables in the training set. Subsequently, a prediction model for 1-year net adverse clinical events (NACEs)-free survival was developed using a multivariable Cox regression model, and a nomogram was constructed. The outcome of the NACEs is defined as a composite endpoint that includes death, myocardial infarction, ischemic stroke, and Bleeding Academic Research Consortium (BARC) grade 3-5 major bleeding. Validation was conducted exclusively using the internal validation cohort, assessing the discrimination, calibration, and clinical utility of the nomogram.</p><p><strong>Results: </strong>This study included 1512 patients with PCI-HBR, including 1058 in the derivation cohort and 454 in the validation cohort. We revealed five risk factors after LASSO regression, Cox regression, and clinical significance screening. These were then utilized to construct a prognostic prediction nomogram, including chronic kidney disease, left main stem lesion, multivessel disease, triglycerides (TG), and creatine kinase-myocardial band (CK-MB). The nomogram exhibited strong predictive ability (the area under the curve (AUC) to predict 1-year NACE-free survival was 0.728), displaying favorable levels of accuracy, discrimination, and clinical usefulness in the internal validation cohort.</p><p><strong>Conclusions: </strong>This study presents a nomogram to predict 1-year NACE outcomes in PCI-HBR patients. 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Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention.
Background: Patients with a high risk of bleeding undergoing percutaneous coronary intervention (PCI-HBR) were provided consensus-based criteria by the Academic Research Consortium for High Bleeding Risk (ARC-HBR). However, the prognostic predictors in this group of patients have yet to be fully explored. Thus, an effective prognostic prediction model for PCI-HBR patients is required.
Methods: We prospectively enrolled PCI-HBR patients from May 2022 to April 2024 at West China Hospital of Sichuan University. The cohort was randomly divided into training and internal validation sets in a ratio of 7:3. The least absolute shrinkage and selection operator (LASSO) regression algorithm was employed to select variables in the training set. Subsequently, a prediction model for 1-year net adverse clinical events (NACEs)-free survival was developed using a multivariable Cox regression model, and a nomogram was constructed. The outcome of the NACEs is defined as a composite endpoint that includes death, myocardial infarction, ischemic stroke, and Bleeding Academic Research Consortium (BARC) grade 3-5 major bleeding. Validation was conducted exclusively using the internal validation cohort, assessing the discrimination, calibration, and clinical utility of the nomogram.
Results: This study included 1512 patients with PCI-HBR, including 1058 in the derivation cohort and 454 in the validation cohort. We revealed five risk factors after LASSO regression, Cox regression, and clinical significance screening. These were then utilized to construct a prognostic prediction nomogram, including chronic kidney disease, left main stem lesion, multivessel disease, triglycerides (TG), and creatine kinase-myocardial band (CK-MB). The nomogram exhibited strong predictive ability (the area under the curve (AUC) to predict 1-year NACE-free survival was 0.728), displaying favorable levels of accuracy, discrimination, and clinical usefulness in the internal validation cohort.
Conclusions: This study presents a nomogram to predict 1-year NACE outcomes in PCI-HBR patients. Internal validation showed strong predictive capability and clinical utility. Future research should validate the nomogram in diverse populations and explore new predictors for improved accuracy.
Clinical trial registration: The data for this study were obtained from the PPP-PCI registry, NCT05369442 (https://clinicaltrials.gov/study/NCT05369442).
期刊介绍:
RCM is an international, peer-reviewed, open access journal. RCM publishes research articles, review papers and short communications on cardiovascular medicine as well as research on cardiovascular disease. We aim to provide a forum for publishing papers which explore the pathogenesis and promote the progression of cardiac and vascular diseases. We also seek to establish an interdisciplinary platform, focusing on translational issues, to facilitate the advancement of research, clinical treatment and diagnostic procedures. Heart surgery, cardiovascular imaging, risk factors and various clinical cardiac & vascular research will be considered.