Department of Heart Failure, Pulmonary Hypertension and Transplant, Instituto Cardiovascular de Buenos Aires, Buenos Aires, Argentina.
Clinical Cardiology, Instituto Cardiovascular de Buenos Aires, Buenos Aires, Argentina.
Ann Card Anaesth. 2021 Oct-Dec;24(4):458-463. doi: 10.4103/aca.ACA_34_20.
Atrial fibrillation frequently occurs in the postoperative period of cardiac surgery, associated with an increase in morbidity and mortality. The scores POAF, CHA2DS2-VASc and HATCH demonstrated a validated ability to predict atrial fibrillation after cardiac surgery (AFCS). The objective is to develop and validate a risk score to predict AFCS from the combination of the variables with highest predictive value of POAF, CHA2DS2-VASc and HATCH models.
We conducted a single-center cohort study, performing a retrospective analysis of prospectively collected data. The study included consecutive patients undergoing cardiac surgery in 2010-2016. The primary outcome was the development of new-onset AFCS. The variables of the POAF, CHA2DS2-VASc and HATCH scores were evaluated in a multivariate regression model to determine the predictive impact. Those variables that were independently associated with AFCS were included in the final model.
A total of 3113 patients underwent cardiac surgery, of which 21% presented AFCS. The variables included in the new score COM-AF were: age (≥75: 2 points, 65-74: 1 point), heart failure (2 points), female sex (1 point), hypertension (1 point), diabetes (1 point), previous stroke (2 points). For the prediction of AFCS, COM-AF presented an AUC of 0.78 (95% CI 0.76-0.80), the rest of the scores presented lower discrimination ability (P < 0.001): CHA2DS2-VASc AUC 0.76 (95% CI 0.74-0.78), POAF 0.71 (95% CI 0.69-0.73) and HATCH 0.70 (95% CI: 0, 67-0.72). Multivariable analysis demonstrated that COM-AF score was an independent predictor of AFCS: OR 1,91 (IC 95% 1,63-2,23).
From the combination of variables with higher predictive value included in the POAF, CHA2DS2-VASc, and HATCH scores, a new risk model system called COM-AF was created to predict AFCS, presenting a greater predictive ability than the original ones. Being necessary future prospective validations.
心房颤动常发生在心脏手术后的围手术期,与发病率和死亡率的增加有关。POAF、CHA2DS2-VASc 和 HATCH 评分均证明具有预测心脏手术后心房颤动(AFCS)的验证能力。目的是从 POAF、CHA2DS2-VASc 和 HATCH 模型中具有最高预测价值的变量组合中开发和验证一种预测 AFCS 的风险评分。
我们进行了一项单中心队列研究,对前瞻性收集的数据进行回顾性分析。该研究纳入了 2010 年至 2016 年期间接受心脏手术的连续患者。主要结局是新发 AFCS。在多变量回归模型中评估 POAF、CHA2DS2-VASc 和 HATCH 评分的变量,以确定预测影响。与 AFCS 独立相关的变量被纳入最终模型。
共有 3113 名患者接受了心脏手术,其中 21%出现了 AFCS。新的 COM-AF 评分纳入的变量包括:年龄(≥75 岁:2 分,65-74 岁:1 分)、心力衰竭(2 分)、女性(1 分)、高血压(1 分)、糖尿病(1 分)、既往卒中(2 分)。对于 AFCS 的预测,COM-AF 的 AUC 为 0.78(95%CI 0.76-0.80),其余评分的区分能力较低(P<0.001):CHA2DS2-VASc AUC 为 0.76(95%CI 0.74-0.78),POAF 为 0.71(95%CI 0.69-0.73),HATCH 为 0.70(95%CI:0,67-0.72)。多变量分析表明,COM-AF 评分是 AFCS 的独立预测因素:OR 1.91(95%CI 1.63-2.23)。
从 POAF、CHA2DS2-VASc 和 HATCH 评分中纳入预测价值较高的变量组合,创建了一种新的风险模型系统 COM-AF 来预测 AFCS,其预测能力优于原始模型。需要进一步进行前瞻性验证。