Zhang Hao, Qiao Huanyu, Yang Bo, Lu Yifan, Bai Tao, Xue Jinrong, Liu Yongmin
Department of Cardiac Surgery, Beijing Anzhen Hospital, Capital Medical University, Beijing, China.
Beijing Institute of Heart Lung and Blood Vessel Diseases, Beijing, China.
J Thorac Dis. 2023 Jul 31;15(7):3708-3725. doi: 10.21037/jtd-22-1706. Epub 2023 Jul 11.
This cohort study collected the clinical data of patients who underwent off-pump coronary artery bypass grafting (OPCABG) during hospitalization to observe the occurrence of postoperative atrial fibrillation (POAF), construct a POAF prediction model for CABG patients based on the left atrial diameter (LAD), and assist clinicians in making better medical decisions.
In this study, all patients who had no prior history of arrhythmia and who had received isolated OPCABG between May 1, 2021, and February 1, 2022, at Beijing Anzhen Hospital Affiliated to Capital Medical University (n=749) were reviewed. Depending on an optimal cutoff obtained from receiver operating characteristic (ROC) curve analysis, patients were separated into two groups: a group with POAF (n=188) and a group without POAF (n=561). The incidence of POAF was then compared. Prediction models were built, and nomograms were plotted was plotted. Model evaluation, including calibration curve and decision curve analysis, was performed.
In all, 188 out of 749 (25.1%) patients who underwent cardiac surgery experienced POAF. Multifactorial logistic regression analysis showed that age ≥66 years, LAD ≥39 mm, and post-OPCABG atrial fibrillation (AF) were independently associated. The prognostic nomogram model showed good concordance index (C-index) scores. Decision curve analysis suggested the clinical benefit of the prediction models.
In this study, a prediction model for patients with POAF after OPCABG was assessed, which was shown to make more accurate predictions compared with the original risk prediction system. It may assist doctors to optimize management of patients with POAF.
本队列研究收集了住院期间接受非体外循环冠状动脉旁路移植术(OPCABG)患者的临床数据,以观察术后房颤(POAF)的发生情况,基于左心房直径(LAD)构建CABG患者的POAF预测模型,并协助临床医生做出更好的医疗决策。
本研究回顾了2021年5月1日至2022年2月1日期间在首都医科大学附属北京安贞医院接受单纯OPCABG且无心律失常病史的所有患者(n = 749)。根据受试者工作特征(ROC)曲线分析获得的最佳截断值,将患者分为两组:POAF组(n = 188)和无POAF组(n = 561)。然后比较POAF的发生率。构建预测模型并绘制列线图。进行模型评估,包括校准曲线和决策曲线分析。
在749例接受心脏手术的患者中,共有188例(25.1%)发生POAF。多因素逻辑回归分析显示,年龄≥66岁、LAD≥39 mm和OPCABG术后房颤(AF)是独立相关因素。预后列线图模型显示出良好的一致性指数(C指数)评分。决策曲线分析表明了预测模型的临床益处。
在本研究中,对OPCABG术后POAF患者的预测模型进行了评估,结果显示与原始风险预测系统相比,该模型能做出更准确的预测。它可能有助于医生优化POAF患者的管理。