Internal Validation of a Risk Score for Prediction of Postoperative Atrial Fibrillation after Cardiac Surgery

Abstract Background: Postoperative atrial fibrillation (POAF) after cardiac surgery has great clinical and economic implications. Many attempts have been made to identify risk factors aiming at a better evaluation of prophylactic treatment strategies. Objective: To perform an internal validation of a risk score for POAF. Methods: A prospective cohort of 1,054 patients who underwent myocardial revascularization and/or valve surgery was included. The risk score model was developed in 448 patients, and its performance was tested in the remaining 606 patients. Variables with a significance level of 5% in the cohort were included and subjected to a multiple logistic regression model with backward selection. Performance statistics was performed using the c-statistic, the chi-square and the Hosmer-Lemeshow (HL) goodness-of-fit, Pearson's correlation coefficient. Results: Four variables were considered predictors of outcome: age (≥ 70 years), mitral valve disease, the non-use or discontinuation of beta-blockers and a positive water balance (> 1,500 mL). The ROC curve was 0.76 (95% confidence interval [CI]: 0.72-0.79). The risk model showed a good ability according to the performance statistics - HL test x(2) = 0.93; p = 0.983 and r = 0.99 (Pearson's coefficient). There was an increase in the frequency of POAF with the increase of the score: very low risk = 0.0%; low risk = 3.9%; intermediate risk = 10.9%; and high risk = 60.0%; p < 0.0001. Conclusion: The predictive variables of POAF allowed us to construct a simplified risk score. This scoring system showed good accuracy and can be used in routine clinical practice.

摘要 背景：心脏手术后的心房颤动（Postoperative Atrial Fibrillation, POAF）具有显著的临床与经济负担。学界已开展多项研究以识别该病症的危险因素，以期更科学地评估预防性治疗策略。
研究目的：针对POAF风险评分开展内部验证。
研究方法：本研究纳入1054名接受心肌血运重建术和/或瓣膜手术的前瞻性队列患者。该风险评分模型以448名患者作为建模集，剩余606名患者作为验证集以检验其性能。以队列中显著性水平为5%的变量纳入分析，采用向后选择法构建多因素logistic回归模型。模型性能评估采用c统计量、卡方检验、霍斯默-莱梅肖（Hosmer-Lemeshow, HL）拟合优度检验以及Pearson相关系数。
研究结果：最终确定4个预后预测变量：年龄≥70岁、二尖瓣疾病、未使用或停用β受体阻滞剂（beta-blockers），以及液体正平衡（＞1500mL）。受试者工作特征（Receiver Operating Characteristic, ROC）曲线下面积为0.76（95%置信区间（confidence interval, CI）：0.72~0.79）。性能统计结果显示该风险模型具备良好的预测能力：霍斯默-莱梅肖检验χ²=0.93，p=0.983；Pearson相关系数r=0.99。随着风险评分升高，POAF的发生频率亦逐步升高：极低危组为0.0%、低危组为3.9%、中危组为10.9%、高危组为60.0%，组间差异具有显著统计学意义（p＜0.0001）。
研究结论：本研究筛选出的POAF预测变量可用于构建简化版风险评分系统。该评分体系展现出良好的预测准确性，可应用于临床日常实践。