Nguyen Kaylin T, Vittinghoff Eric, Dewland Thomas A, Mandyam Mala C, Stein Phyllis K, Soliman Elsayed Z, Heckbert Susan R, Marcus Gregory M
Section of Cardiac Electrophysiology, Division of Cardiology, Department of Medicine, University of California, San Francisco, San Francisco, California.
Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California.
Am J Cardiol. 2016 Sep 1;118(5):714-9. doi: 10.1016/j.amjcard.2016.06.008. Epub 2016 Jun 14.
Atrial fibrillation (AF) is likely secondary to multiple different pathophysiological mechanisms that are increasingly but incompletely understood. Motivated by the hypothesis that 3 previously described electrocardiographic predictors of AF identify distinct AF mechanisms, we sought to determine if these electrocardiographic findings independently predict incident disease. Among Cardiovascular Health Study participants without prevalent AF, we determined whether left anterior fascicular block (LAFB), a prolonged QTC, and atrial premature complexes (APCs) each predicted AF after adjusting for each other. We then calculated the attributable risk in the exposed for each electrocardiographic marker. LAFB and QTC intervals were assessed on baseline 12-lead electrocardiogram (n = 4,696). APC count was determined using 24-hour Holter recordings obtained in a random subsample (n = 1,234). After adjusting for potential confounders and each electrocardiographic marker, LAFB (hazard ratio [HR] 2.1, 95% confidence interval [CI] 1.1 to 3.9, p = 0.023), a prolonged QTC (HR 2.5, 95% CI 1.4 to 4.3, p = 0.002), and every doubling of APC count (HR 1.2, 95% CI 1.1 to 1.3, p <0.001) each remained independently predictive of incident AF. The attributable risk of AF in the exposed was 35% (95% CI 13% to 52%) for LAFB, 25% (95% CI 0.6% to 44%) for a prolonged QTC, and 34% (95% CI 26% to 42%) for APCs. In conclusion, in a community-based cohort, 3 previously established electrocardiogram-derived AF predictors were each independently associated with incident AF, suggesting that they may represent distinct mechanisms underlying the disease.
心房颤动(AF)可能继发于多种不同的病理生理机制,人们对这些机制的了解日益增多,但仍不完整。基于之前描述的3种AF心电图预测指标可识别不同AF机制的假设,我们试图确定这些心电图表现是否能独立预测新发疾病。在心血管健康研究中无AF病史的参与者中,我们确定了左前分支阻滞(LAFB)、QTc延长和房性早搏(APC)在相互校正后是否各自能预测AF。然后,我们计算了每个心电图指标在暴露人群中的归因风险。通过基线12导联心电图评估LAFB和QTc间期(n = 4696)。使用在随机子样本中获得的24小时动态心电图记录确定APC计数(n = 1234)。在对潜在混杂因素和每个心电图指标进行校正后,LAFB(风险比[HR] 2.1,95%置信区间[CI] 1.1至3.9,p = 0.023)、QTc延长(HR 2.5,95%CI 1.4至4.3,p = 0.002)以及APC计数每增加一倍(HR 1.2,95%CI 1.1至1.3,p <0.001)均仍能独立预测新发AF。LAFB在暴露人群中AF的归因风险为35%(95%CI 13%至52%),QTc延长为25%(95%CI 0.6%至44%),APC为34%(95%CI 26%至42%)。总之,在一个基于社区的队列中,之前确立的3种源自心电图的AF预测指标均与新发AF独立相关,提示它们可能代表该疾病的不同潜在机制。