■本研究的目的是探讨Sun手术(使用四urcate移植物和支架大象躯干植入的全足弓置换)后新发术后房颤(POAF)的危险因素。急性A型主动脉夹层(AAAD),并建立预测模型,以评估接受Sun手术的AAAD患者新发POAF的可能性。
■我们回顾了2017年12月1日至2022年12月31日在齐鲁医院接受Sun\'s手术的诊断为AAAD的患者的临床参数。数据通过单变量和多变量逻辑回归分析进行分析。使用方差膨胀因子来研究变量共线性。开发了用于预测新发POAF的列线图,并通过Bootstrap重采样进行了验证。此外,我们模型的校准通过校准曲线和Hosmer-Lemeshow检验进行评估.此外,我们使用净获益曲线评估了我们模型的临床效用.
■这项研究集中于242名AAAD患者的队列,其中42人经历了新发POAF,表明发病率为17.36%。年龄,左心房直径(LA),右心房直径(RA),术前红细胞(RBC),和以前的急性冠脉综合征(preACS)出现了对Sun手术后新发POAF的独立影响,通过单变量和多变量逻辑回归分析确定。共线性分析,证明变量之间没有共线性。制定了Sun手术后新发POAF的用户友好预测列线图。该模型显示出良好的诊断准确性,曲线下面积(AUC)为0.7852。通过自举验证模型(1,000次重复)产生0.8080的AUC(95%CI:0.8056-0.8104)。确认其稳健性。此外,该模型表现出良好的拟合度,校准,和决策曲线分析中的正净收益。
■根据这些发现,我们建立了新发POAF发生的预测模型。这些结果提示了该预测模型对于识别有发展POAF风险的患者的潜在功效。该模型的可视化使医疗保健专业人员能够方便,迅速地评估患者的房颤风险。从而便于及时干预实施。
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.