Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya, Turkey.
Department of Cardiovascular Surgery, Faculty of Medicine, Inonu University, Malatya, Turkey.
Thorac Cardiovasc Surg. 2023 Jun;71(4):282-290. doi: 10.1055/s-0041-1736245. Epub 2021 Dec 11.
Atrial fibrillation (AF), a condition that might occur after a heart bypass procedure, has caused differing estimates of its occurrence and risk. The current study analyses the possible risk factors of post-coronary artery bypass grafting (post-CABG) AF (postoperative AF [POAF]) and presents a software for preoperative POAF risk prediction.
This retrospective research was performed on 1,667 patients who underwent CABG surgery using the hospital database. The associations between the variables of the patients and AF risk factors after CABG were examined using multivariable logistic regression (LR) after preprocessing the relevant data. The tool was designed to predict POAF risk using Shiny, an R package, to develop a web-based software.
The overall proportion of post-CABG AF was 12.2%. According to the results of univariate tests, in terms of age ( < 0.001), blood urea nitrogen ( = 0.005), platelet ( < 0.001), triglyceride ( = 0.0026), presence of chronic obstructive pulmonary disease (COPD; = 0.01), and presence of preoperative carotid artery stenosis (PCAS; < 0.001), there were statistically significant differences between the POAF and non-POAF groups. Multivariable LR analysis disclosed the independent risk factors associated with POAF: PCAS (odds ratio [OR] = 2.360; = 0.028), COPD (OR = 2.243; = 0.015), body mass index (OR = 1.090; = 0.006), age (OR = 1.054, < 0.001), and platelet (OR = 0.994, < 0.001).
The experimental findings from the current research demonstrate that the suggested tool () can help clinicians predict POAF risk development in the preoperative period after validated on large sample(s) that can represent the related population(s). Simultaneously, since the updated versions of the proposed tool will be released periodically based on the increases in data dimensions with continuously added new samples and related factors, more robust predictions may be obtained in the subsequent stages of the current study in statistical and clinical terms.
心房颤动（房颤）是心脏旁路手术后可能发生的一种病症，其发生和风险的估计存在差异。本研究分析了冠状动脉旁路移植术后（CABG 术后）房颤（术后房颤[POAF]）的可能危险因素，并提出了一种用于术前 POAF 风险预测的软件。
本回顾性研究使用医院数据库对 1667 名接受 CABG 手术的患者进行了分析。使用多元逻辑回归（LR）对相关数据进行预处理后，检查了患者变量与 CABG 后房颤风险因素之间的关联。该工具使用 R 包 Shiny 设计用于预测 POAF 风险，以开发基于网络的软件。
CABG 后房颤的总体比例为 12.2%。根据单变量检验的结果，在年龄（ < 0.001）、血尿素氮（ = 0.005）、血小板（ < 0.001）、甘油三酯（ = 0.0026）、慢性阻塞性肺疾病（COPD； = 0.01）和术前颈动脉狭窄（PCAS； < 0.001）方面，POAF 组和非 POAF 组之间存在统计学显著差异。多元 LR 分析揭示了与 POAF 相关的独立危险因素：PCAS（优势比[OR] = 2.360； = 0.028）、COPD（OR = 2.243； = 0.015）、体重指数（OR = 1.090； = 0.006）、年龄（OR = 1.054， < 0.001）和血小板（OR = 0.994， < 0.001）。
本研究的实验结果表明，该工具（）可以帮助临床医生在术前期间预测 POAF 风险的发展，前提是在可以代表相关人群的大样本上进行验证。同时，由于根据不断添加的新样本和相关因素增加数据维度，该工具的更新版本将定期发布，因此在本研究的后续阶段，在统计学和临床方面可能会获得更稳健的预测结果。
