Yang Zhihao, Liu Chunxiao, Fu Chao, Zhao Xin
Department of Cardiovascular Surgery, Qilu Hospital of Shandong University, Jinan, China.
Institute of Thoracoscopy in Cardiac Surgery, Shandong University, Jinan, China.
Front Cardiovasc Med. 2024 Aug 21;11:1429680. doi: 10.3389/fcvm.2024.1429680. eCollection 2024.
The objective of this study is to explore the risk factors associated with new-onset postoperative atrial fibrillation (POAF) following Sun's surgery(total arch replacement using a tetrafurcate graft with stented elephant trunk implantation) for acute type A aortic dissection(AAAD) and to develop a predictive model for assessing the likelihood of new-onset POAF in patients undergoing Sun's surgery for AAAD.
We reviewed the clinical parameters of patients diagnosed with AAAD who underwent Sun's surgery at Qilu Hospital between December 1, 2017 and December 31, 2022. The data was analyzed through univariable and multivariable logistic regression analysis. Variance inflation factor was used to investigate for variable collinearity. A nomogram for predicting new-onset POAF was developed and verified by bootstrap resampling. In addition, the calibration of our model was evaluated by the calibration curve and Hosmer-Lemeshow test. Furthermore, the clinical utility of our model was evaluated using the net benefit curve.
This study focused on a cohort of 242 patients with AAAD, among whom 42 experienced new-onset POAF, indicating an incidence rate of 17.36%. Age, left atrial diameter (LA), right atrial diameter (RA), preoperative red blood cells (RBC), and previous acute coronary syndrome (preACS) emerged as independent influences on new-onset POAF following Sun's surgery, as identified by univariable and multivariable logistic regression analysis. Collinearity analysis with demonstrated no collinearity among the variables. A user-friendly prediction nomogram for new onset POAF following Sun's surgery was formulated. The model demonstrated commendable diagnostic accuracy with an area under the curve (AUC) of 0.7852. Validation of the model through bootstrapping (1,000 repetitions) yielded an AUC of 0.8080 (95% CI: 0.8056-0.8104). affirming its robustness. Additionally, the model exhibited favorable fit, calibration, and positive net benefits in decision curve analysis.
Drawing upon these findings, we have developed a predictive model for the occurrence of new-onset POAF. These results suggest the potential efficacy of this prediction model for identifying patients at risk of developing POAF. The visualization of this model empowers healthcare professionals to conveniently and promptly assess the risk of AF in patients, thereby facilitating the timely intervention implementation.
本研究旨在探讨孙氏手术（使用带支架象鼻的四分支移植物进行全弓置换）治疗急性A型主动脉夹层（AAAD）后新发术后房颤（POAF）的相关危险因素，并建立一个预测模型，以评估接受孙氏手术治疗AAAD患者发生新发POAF的可能性。
我们回顾了2017年12月1日至2022年12月31日期间在齐鲁医院接受孙氏手术的AAAD患者的临床参数。通过单变量和多变量逻辑回归分析对数据进行分析。使用方差膨胀因子来研究变量共线性。制定了一个预测新发POAF的列线图，并通过自助重采样进行验证。此外，通过校准曲线和Hosmer-Lemeshow检验评估我们模型的校准情况。此外，使用净效益曲线评估我们模型的临床实用性。
本研究聚焦于242例AAAD患者队列，其中42例发生新发POAF，发病率为17.36%。单变量和多变量逻辑回归分析确定，年龄、左心房直径（LA）、右心房直径（RA）、术前红细胞（RBC）和既往急性冠状动脉综合征（preACS）是孙氏手术后新发POAF的独立影响因素。共线性分析表明变量之间不存在共线性。制定了一个便于使用的孙氏手术后新发POAF预测列线图。该模型显示出良好的诊断准确性，曲线下面积（AUC）为0.7852。通过自助法（1000次重复）对模型进行验证，得到的AUC为0.8080（95%CI：0.8056 - 0.8104），证实了其稳健性。此外，该模型在决策曲线分析中表现出良好的拟合度、校准度和正净效益。
基于这些发现，我们开发了一个新发POAF发生的预测模型。这些结果表明该预测模型在识别有发生POAF风险患者方面的潜在有效性。该模型的可视化使医疗保健专业人员能够方便快捷地评估患者发生房颤的风险，从而有助于及时实施干预措施。
