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...
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IMR Press
2025-01-01
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| Series: | Reviews in Cardiovascular Medicine |
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| Online Access: | https://www.imrpress.com/journal/RCM/26/1/10.31083/RCM25352 |
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| author | Junyan Zhang Zhongxiu Chen Ran Liu Yuxiao Li Hongsen Zhao Yanning Li Minggang Zhou Hua Wang Chen Li Li Rao Yong He |
| author_facet | Junyan Zhang Zhongxiu Chen Ran Liu Yuxiao Li Hongsen Zhao Yanning Li Minggang Zhou Hua Wang Chen Li Li Rao Yong He |
| author_sort | Junyan Zhang |
| collection | DOAJ |
| description | 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). |
| format | Article |
| id | doaj-art-5ad12655a7be4ee38b58c91c12b86396 |
| institution | Kabale University |
| issn | 1530-6550 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IMR Press |
| record_format | Article |
| series | Reviews in Cardiovascular Medicine |
| spelling | doaj-art-5ad12655a7be4ee38b58c91c12b863962025-01-25T10:41:20ZengIMR PressReviews in Cardiovascular Medicine1530-65502025-01-012612535210.31083/RCM25352S1530-6550(24)01635-1Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary InterventionJunyan Zhang0Zhongxiu Chen1Ran Liu2Yuxiao Li3Hongsen Zhao4Yanning Li5Minggang Zhou6Hua Wang7Chen Li8Li Rao9Yong He10Department of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaInformation Center of West China Hospital, Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaInformation Center of West China Hospital, Sichuan University, 610041 Chengdu, Sichuan, ChinaInformation Center of West China Hospital, Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaDepartment of Cardiology, West China Hospital of Sichuan University, 610041 Chengdu, Sichuan, ChinaBackground: 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).https://www.imrpress.com/journal/RCM/26/1/10.31083/RCM25352percutaneous coronary interventionhigh bleeding risknomogramprognosisprediction modelinternal validation |
| spellingShingle | Junyan Zhang Zhongxiu Chen Ran Liu Yuxiao Li Hongsen Zhao Yanning Li Minggang Zhou Hua Wang Chen Li Li Rao Yong He Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention Reviews in Cardiovascular Medicine percutaneous coronary intervention high bleeding risk nomogram prognosis prediction model internal validation |
| title | Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention |
| title_full | Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention |
| title_fullStr | Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention |
| title_full_unstemmed | Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention |
| title_short | Development and Validation of a Nomogram for Predicting Long-Term Net Adverse Clinical Events in High Bleeding Risk Patients Undergoing Percutaneous Coronary Intervention |
| title_sort | development and validation of a nomogram for predicting long term net adverse clinical events in high bleeding risk patients undergoing percutaneous coronary intervention |
| topic | percutaneous coronary intervention high bleeding risk nomogram prognosis prediction model internal validation |
| url | https://www.imrpress.com/journal/RCM/26/1/10.31083/RCM25352 |
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