Yang Heng, Yuan Chen, Yang Juesheng, Xiang Haiyan, Lan Wanqi, Tang Yanhua
Department of Cardiovascular Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
The Second Clinical Medical College of Nanchang University, Nanchang, China.
Front Cardiovasc Med. 2022 Sep 29;9:949259. doi: 10.3389/fcvm.2022.949259. eCollection 2022.
Postoperative atrial fibrillation (POAF) is a severe complication after cardiac surgery and is associated with an increased risk of ischemic stroke and mortality. The main aim of this study was to identify the independent predictors associated with POAF after isolated valve operation and to develop a risk prediction model.
This retrospective observational study involved patients without previous AF who underwent isolated valve surgery from November 2018 to October 2021. Patients were stratified into two groups according to the development of new-onset POAF. Baseline characteristics and perioperative data were collected from the two groups of patients. Univariate and multivariate logistic regression analyses were applied to identify independent risk factors for the occurrence of POAF, and the results of the multivariate analysis were used to create a predictive nomogram.
A total of 422 patients were included in the study, of which 163 (38.6%) developed POAF. The Multivariate logistic regression analysis indicated that cardiac function (odds ratio [OR] = 2.881, 95% confidence interval [CI] = 1.595-5.206; < 0.001), Left atrial diameter index (OR = 1.071, 95%CI = 1.028-1.117; = 0.001), Operative time (OR = 1.532, 95%CI = 1.095-2.141; = 0.013), Neutrophil count (OR = 1.042, 95%CI = 1.006-1.08; = 0.021) and the magnitude of fever (OR = 3.414, 95%CI = 2.454-4.751; < 0.001) were independent predictors of POAF. The above Variables were incorporated, and a nomogram was successfully constructed with a C-index of 0.810. The area under the receiver operating characteristic curve was 0.817.
Cardiac function, left atrial diameter index, operative time, neutrophil count, and fever were independent predictors of POAF in patients with isolated valve surgery. Establishing a nomogram model based on the above predictors helps predict the risk of POAF and may have potential clinical utility in preventive interventions.
术后心房颤动（POAF）是心脏手术后的一种严重并发症，与缺血性中风和死亡率增加相关。本研究的主要目的是确定单纯瓣膜手术后与POAF相关的独立预测因素，并建立一个风险预测模型。
这项回顾性观察性研究纳入了2018年11月至2021年10月期间接受单纯瓣膜手术且既往无房颤的患者。根据新发POAF的发生情况将患者分为两组。收集两组患者的基线特征和围手术期数据。采用单因素和多因素逻辑回归分析确定POAF发生的独立危险因素，并将多因素分析结果用于创建预测列线图。
本研究共纳入422例患者，其中163例（38.6%）发生POAF。多因素逻辑回归分析表明，心功能（比值比[OR]=2.881，95%置信区间[CI]=1.595-5.206；<0.001）、左房直径指数（OR=1.071，95%CI=1.028-1.117；=0.001）、手术时间（OR=1.532，95%CI=1.095-2.141；=0.013）、中性粒细胞计数（OR=1.042，95%CI=1.006-1.08；=0.021）和发热程度（OR=3.414，95%CI=2.454-4.751；<0.001）是POAF的独立预测因素。纳入上述变量后，成功构建了列线图，C指数为0.810。受试者工作特征曲线下面积为0.817。
心功能、左房直径指数、手术时间、中性粒细胞计数和发热是单纯瓣膜手术患者POAF的独立预测因素。基于上述预测因素建立列线图模型有助于预测POAF风险，可能在预防干预中具有潜在的临床应用价值。
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