Kwong Calvin, Ling Albee Y, Crawford Michael H, Zhao Susan X, Shah Nigam H
Department of Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA.
Cardiology. 2017;138(3):133-140. doi: 10.1159/000476030. Epub 2017 Jun 28.
Detection of atrial fibrillation (AF) in post-cryptogenic stroke (CS) or transient ischemic attack (TIA) patients carries important therapeutic implications.
To risk stratify CS/TIA patients for later development of AF, we conducted a retrospective cohort study using data from 1995 to 2015 in the Stanford Translational Research Integrated Database Environment (STRIDE).
Of the 9,589 adult patients (age ≥40 years) with CS/TIA included, 482 (5%) patients developed AF post CS/TIA. Of those patients, 28.4, 26.3, and 45.3% were diagnosed with AF 1-12 months, 1-3 years, and >3 years after the index CS/TIA, respectively. Age (≥75 years), obesity, congestive heart failure, hypertension, coronary artery disease, peripheral vascular disease, and valve disease are significant risk factors, with the following respective odds ratios (95% CI): 1.73 (1.39-2.16), 1.53 (1.05-2.18), 3.34 (2.61-4.28), 2.01 (1.53-2.68), 1.72 (1.35-2.19), 1.37 (1.02-1.84), and 2.05 (1.55-2.69). A risk-scoring system, i.e., the HAVOC score, was constructed using these 7 clinical variables that successfully stratify patients into 3 risk groups, with good model discrimination (area under the curve = 0.77).
Findings from this study support the strategy of looking longer and harder for AF in post-CS/TIA patients. The HAVOC score identifies different levels of AF risk and may be used to select patients for extended rhythm monitoring.
在隐源性卒中(CS)或短暂性脑缺血发作(TIA)后患者中检测心房颤动(AF)具有重要的治疗意义。
为对CS/TIA患者发生AF的风险进行分层,我们利用斯坦福转化研究综合数据库环境(STRIDE)中1995年至2015年的数据进行了一项回顾性队列研究。
纳入的9589例成年CS/TIA患者(年龄≥40岁)中,482例(5%)在CS/TIA后发生AF。在这些患者中,分别有28.4%、26.3%和45.3%在首次CS/TIA后1 - 12个月、1 - 3年和超过3年被诊断为AF。年龄(≥75岁)、肥胖、充血性心力衰竭、高血压、冠状动脉疾病、外周血管疾病和瓣膜疾病是显著的危险因素,其各自的比值比(95%置信区间)如下:1.73(1.39 - 2.16)、1.53(1.05 - 2.18)、3.34(2.61 - 4.28)、2.01(1.53 - 2.68)、1.72(1.35 - 2.19)、1.37(1.02 - 1.84)和2.05(1.55 - 2.69)。利用这7个临床变量构建了一个风险评分系统,即HAVOC评分,该系统成功地将患者分为3个风险组,具有良好的模型区分度(曲线下面积 = 0.77)。
本研究结果支持在CS/TIA后患者中更长期、更仔细地筛查AF的策略。HAVOC评分可识别不同程度的AF风险,可用于选择患者进行延长的心律监测。