Jaakkola Samuli, Lip Gregory Y H, Biancari Fausto, Nuotio Ilpo, Hartikainen Juha E K, Ylitalo Antti, Airaksinen K E Juhani
Heart Center, Turku University Hospital and University of Turku, Turku, Finland.
University of Birmingham Institute of Cardiovascular Sciences, City Hospital, Birmingham, United Kingdom; Aalborg Thrombosis Research Unit, Department of Clinical Medicine, Aalborg University, Aalborg, Denmark.
Am J Cardiol. 2017 Mar 1;119(5):749-752. doi: 10.1016/j.amjcard.2016.11.026. Epub 2016 Dec 2.
Electrical cardioversion (ECV) is the standard treatment for acute atrial fibrillation (AF), but identification of patients with increased risk of ECV failure or early AF recurrence is of importance for rational clinical decision-making. The objective of this study was to derive and validate a clinical risk stratification tool for identifying patients at high risk for unsuccessful outcome after ECV for acute AF. Data on 2,868 patients undergoing 5,713 ECVs of acute AF in 3 Finnish hospitals from 2003 through 2010 (the FinCV study data) were included in the analysis. Patients from western (n = 3,716 cardioversions) and eastern (n = 1,997 cardioversions) hospital regions were used as derivation and validation datasets. The composite of cardioversion failure and recurrence of AF within 30 days after ECV was recorded. A clinical scoring system was created using logistic regression analyses with a repeated-measures model in the derivation data set. A multivariate analysis for prediction of the composite end point resulted in identification of 5 clinical variables for increased risk: Age (odds ratio [OR] 1.31, confidence interval [CI] 1.13 to 1.52), not the First AF (OR 1.55, CI 1.19 to 2.02), Cardiac failure (OR 1.52, CI 1.08 to 2.13), Vascular disease (OR 1.38, CI 1.11 to 1.71), and Short interval from previous AF episode (within 1 month before ECV, OR 2.31, CI 1.83 to 2.91) [hence, the acronym, AF-CVS]. The c-index for the AF-CVS score was 0.67 (95% CI 0.65 to 0.69) with Hosmer-Lemeshow p value 0.84. With high (>5) scores (i.e., 12% to 16% of the patients), the rate of composite end point was ∼40% in both cohorts, and among low-risk patients (score <3), the composite end point rate was ∼10%. In conclusion, the risk of ECV failure and early recurrence of AF can be predicted with simple patient and disease characteristics.
电复律(ECV)是急性心房颤动(AF)的标准治疗方法,但识别电复律失败或房颤早期复发风险增加的患者对于合理的临床决策至关重要。本研究的目的是推导并验证一种临床风险分层工具,用于识别急性房颤电复律后预后不良的高危患者。分析纳入了2003年至2010年芬兰3家医院2868例接受5713次急性房颤电复律患者的数据(FinCV研究数据)。来自西部(n = 3716次复律)和东部(n = 1997次复律)医院区域的患者分别用作推导和验证数据集。记录电复律失败和电复律后30天内房颤复发的综合情况。在推导数据集中使用逻辑回归分析和重复测量模型创建了一个临床评分系统。对复合终点预测的多变量分析确定了5个风险增加的临床变量:年龄(比值比[OR] 1.31,置信区间[CI] 1.13至1.52)、非首次房颤(OR 1.55,CI 1.19至2.02)、心力衰竭(OR 1.52,CI 1.08至2.13)、血管疾病(OR 1.38,CI 1.11至1.71)以及距上次房颤发作的间隔时间短(电复律前1个月内,OR 2.31,CI 1.83至2.91)[因此,简称为AF - CVS]。AF - CVS评分的c指数为0.67(95% CI 0.65至0.69),Hosmer - Lemeshow p值为0.84。在两个队列中,高评分(>5)(即患者的12%至16%)患者的复合终点发生率约为40%,而低风险患者(评分<3)的复合终点发生率约为10%。总之,通过简单的患者和疾病特征可以预测电复律失败和房颤早期复发的风险。