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.

IF 1.5 4区 医学 Q3 CARDIAC & CARDIOVASCULAR SYSTEMS
Coronary artery disease Pub Date : 2024-12-01 Epub Date: 2024-06-06 DOI:10.1097/MCA.0000000000001399
Jie Jian, Lingqin Zhang, Yang Zhang, Chang Jian, Tingting Wang, Mingxuan Xie, Wenjuan Wu, Bo Liang, Xingliang Xiong
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引用次数: 0

Abstract

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.

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。
背景和目的:同时患有冠状动脉疾病(CAD)和心房颤动(AF)的患者在住院期间发生重大不良心脑血管事件(MACCE)的风险很高。准确预测主要心脑血管不良事件有助于识别高危患者并指导治疗决策。本研究旨在制定并验证一个动态提名图,用于预测 CAD 合并房颤患者住院期间 MACCE 的发生率:方法:共收集了 3550 名房颤合并 CAD 患者。方法:共收集了 3550 名房颤合并 CAD 患者,按照 7 :3.利用单变量和多变量分析确定风险因素(P 结果:通过单变量分析、多变量分析以及最小绝对缩减法和选择算子法,筛选出了具有统计学差异的 8 个指标(P 结论:我们构建的危险因素提名图可能有助于识别心血管疾病的危险因素:我们构建的提名图有助于对 CAD 合并房颤患者进行风险分层和预后预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Coronary artery disease
Coronary artery disease 医学-外周血管病
CiteScore
2.50
自引率
0.00%
发文量
190
审稿时长
6-12 weeks
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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