Jie Jian, Lingqin Zhang, Yang Zhang, Chang Jian, Tingting Wang, Mingxuan Xie, Wenjuan Wu, Bo Liang, Xingliang Xiong
{"title":"预测冠心病合并心房颤动患者院内主要不良心脑血管事件的动态提名图：一项多中心回顾性研究。","authors":"Jie Jian, Lingqin Zhang, Yang Zhang, Chang Jian, Tingting Wang, Mingxuan Xie, Wenjuan Wu, Bo Liang, Xingliang Xiong","doi":"10.1097/MCA.0000000000001399","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objective: </strong>Patients with both coronary artery disease (CAD) and atrial fibrillation (AF) are at a high risk of major adverse cardiovascular and cerebrovascular events (MACCE) during hospitalization. Accurate prediction of MACCE can help identify high-risk patients and guide treatment decisions. This study was to elaborate and validate a dynamic nomogram for predicting the occurrence of MACCE during hospitalization in Patients with CAD combined with AF.</p><p><strong>Methods: </strong>A total of 3550 patients with AF and CAD were collected. They were randomly assigned to a training group and a validation group in a ratio of 7 : 3. Univariate and multivariate analyses were utilized to identify risk factors ( P < 0.05). To avoid multicollinearity and overfit of the model, the least absolute shrinkage and selection operator was conducted to further screen the risk factors. Calibration curves, receiver operating characteristic curves, and decision curve analyses are employed to assess the nomogram. For external validation, a cohort consisting of 249 patients was utilized from the Medical Information Mart for Intensive Care IV Clinical Database, version 2.2.</p><p><strong>Results: </strong>Eight indicators with statistical differences were screened by univariate analysis, multivariate analysis, and the least absolute shrinkage and selection operator method ( P < 0.05). The prediction model based on eight risk factors demonstrated good prediction performance in the training group, with an area under the curve (AUC) of 0.838. This performance was also maintained in the internal validation group (AUC = 0.835) and the external validation group (AUC = 0.806). Meanwhile, the calibration curve indicates that the nomogram was well-calibrated, and decision curve analysis revealed that the nomogram exhibited good clinical utility.</p><p><strong>Conclusion: </strong>The nomogram we constructed may aid in stratifying the risk and predicting the prognosis for patients with CAD and AF.</p>","PeriodicalId":10702,"journal":{"name":"Coronary artery disease","volume":" ","pages":"659-667"},"PeriodicalIF":1.5000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A dynamic nomogram for predicting in-hospital major adverse cardiovascular and cerebrovascular events in patients with both coronary artery disease and atrial fibrillation: a multicenter retrospective study.\",\"authors\":\"Jie Jian, Lingqin Zhang, Yang Zhang, Chang Jian, Tingting Wang, Mingxuan Xie, Wenjuan Wu, Bo Liang, Xingliang Xiong\",\"doi\":\"10.1097/MCA.0000000000001399\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background and objective: </strong>Patients with both coronary artery disease (CAD) and atrial fibrillation (AF) are at a high risk of major adverse cardiovascular and cerebrovascular events (MACCE) during hospitalization. Accurate prediction of MACCE can help identify high-risk patients and guide treatment decisions. This study was to elaborate and validate a dynamic nomogram for predicting the occurrence of MACCE during hospitalization in Patients with CAD combined with AF.</p><p><strong>Methods: </strong>A total of 3550 patients with AF and CAD were collected. They were randomly assigned to a training group and a validation group in a ratio of 7 : 3. Univariate and multivariate analyses were utilized to identify risk factors ( P < 0.05). To avoid multicollinearity and overfit of the model, the least absolute shrinkage and selection operator was conducted to further screen the risk factors. Calibration curves, receiver operating characteristic curves, and decision curve analyses are employed to assess the nomogram. For external validation, a cohort consisting of 249 patients was utilized from the Medical Information Mart for Intensive Care IV Clinical Database, version 2.2.</p><p><strong>Results: </strong>Eight indicators with statistical differences were screened by univariate analysis, multivariate analysis, and the least absolute shrinkage and selection operator method ( P < 0.05). The prediction model based on eight risk factors demonstrated good prediction performance in the training group, with an area under the curve (AUC) of 0.838. This performance was also maintained in the internal validation group (AUC = 0.835) and the external validation group (AUC = 0.806). Meanwhile, the calibration curve indicates that the nomogram was well-calibrated, and decision curve analysis revealed that the nomogram exhibited good clinical utility.</p><p><strong>Conclusion: </strong>The nomogram we constructed may aid in stratifying the risk and predicting the prognosis for patients with CAD and AF.</p>\",\"PeriodicalId\":10702,\"journal\":{\"name\":\"Coronary artery disease\",\"volume\":\" \",\"pages\":\"659-667\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Coronary artery disease\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/MCA.0000000000001399\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/6 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Coronary artery disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/MCA.0000000000001399","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/6 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
A dynamic nomogram for predicting in-hospital major adverse cardiovascular and cerebrovascular events in patients with both coronary artery disease and atrial fibrillation: a multicenter retrospective study.
Background and objective: Patients with both coronary artery disease (CAD) and atrial fibrillation (AF) are at a high risk of major adverse cardiovascular and cerebrovascular events (MACCE) during hospitalization. Accurate prediction of MACCE can help identify high-risk patients and guide treatment decisions. This study was to elaborate and validate a dynamic nomogram for predicting the occurrence of MACCE during hospitalization in Patients with CAD combined with AF.
Methods: A total of 3550 patients with AF and CAD were collected. They were randomly assigned to a training group and a validation group in a ratio of 7 : 3. Univariate and multivariate analyses were utilized to identify risk factors ( P < 0.05). To avoid multicollinearity and overfit of the model, the least absolute shrinkage and selection operator was conducted to further screen the risk factors. Calibration curves, receiver operating characteristic curves, and decision curve analyses are employed to assess the nomogram. For external validation, a cohort consisting of 249 patients was utilized from the Medical Information Mart for Intensive Care IV Clinical Database, version 2.2.
Results: Eight indicators with statistical differences were screened by univariate analysis, multivariate analysis, and the least absolute shrinkage and selection operator method ( P < 0.05). The prediction model based on eight risk factors demonstrated good prediction performance in the training group, with an area under the curve (AUC) of 0.838. This performance was also maintained in the internal validation group (AUC = 0.835) and the external validation group (AUC = 0.806). Meanwhile, the calibration curve indicates that the nomogram was well-calibrated, and decision curve analysis revealed that the nomogram exhibited good clinical utility.
Conclusion: The nomogram we constructed may aid in stratifying the risk and predicting the prognosis for patients with CAD and AF.
期刊介绍：
Coronary Artery Disease welcomes reports of original research with a clinical emphasis, including observational studies, clinical trials, translational research, novel imaging, pharmacology and interventional approaches as well as advances in laboratory research that contribute to the understanding of coronary artery disease. Each issue of Coronary Artery Disease is divided into four areas of focus: Original Research articles, Review in Depth articles by leading experts in the field, Editorials and Images in Coronary Artery Disease. The Editorials will comment on selected original research published in each issue of Coronary Artery Disease, as well as highlight controversies in coronary artery disease understanding and management.
Submitted artcles undergo a preliminary review by the editor. Some articles may be returned to authors without further consideration. Those being considered for publication will undergo further assessment and peer-review by the editors and those invited to do so from a reviewer pool.
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