Medical Imaging Department II, Shaanxi Kangfu Hospital, Xi'an, Shaanxi Province, China.
Medicine (Baltimore). 2024 Apr 12;103(15):e37582. doi: 10.1097/MD.0000000000037582.
Atrial fibrillation (AF) is one of the most common clinical arrhythmias. This study aims to predict the risk of post-stroke AF through electrocardiographic changes in sinus rhythm.
We searched the MEDLINE (PubMed) and EMBASE databases to identify relevant research articles published until August 2023. Prioritized items from systematic reviews and meta-analyses were screened, and data related to AF detection rate were extracted. A meta-analysis using a random-effects model was conducted for data synthesis and analysis.
A total of 32 studies involving electrocardiograms (ECG) were included, with a total analysis population of 330,284 individuals. Among them, 16,662 individuals (ECG abnormal group) developed AF, while 313,622 individuals (ECG normal group) did not. ECG patterns included terminal P-wave terminal force V1, interatrial block (IAB), advanced interatrial block, abnormal P-wave axis, pulse rate prolongation, and atrial premature complexes. Overall, 15,762 patients experienced AF during the study period (4.77%). In the ECG abnormal group, the proportion was 14.21% (2367/16,662), while in the control group (ECG normal group), the proportion was 4.27% (13,395/313,622). The pooled risk ratio for developing AF was 2.45 (95% confidence interval [CI]: 2.02-2.98, P < .001), with heterogeneity (I2) of 95%. The risk ratio values of alAB, P-wave terminal force V1, interatrial block, abnormal P-wave axis, pulse rate prolongation and atrial premature complexes were 4.12 (95% CI, 2.99-5.66), 1.47 (95% CI, 1.19-1.82), 2.54 (95% CI, 1.83-3.52), 1.70 (95% CI, 0.98-2.97), 2.65 (95% CI, 1.88-3.72), 3.79 (95% CI, 2.12-6.76), respectively.
There is a significant correlation between ECG patterns and the occurrence of AF. The alAB exhibited the highest level of predictability for the occurrence of AF. These indicators support their use as screening tools to identify high-risk individuals who may benefit from further examinations or empirical anticoagulation therapy following stroke.
心房颤动（AF）是最常见的临床心律失常之一。本研究旨在通过窦性心律的心电图变化预测中风后 AF 的风险。
我们检索了 MEDLINE（PubMed）和 EMBASE 数据库，以确定截至 2023 年 8 月发表的相关研究文章。筛选了系统评价和荟萃分析的优先项目，并提取了与 AF 检出率相关的数据。使用随机效应模型对数据进行综合分析。
共纳入 32 项心电图（ECG）研究，总分析人群为 330284 人。其中，16662 人（ECG 异常组）发生 AF，313622 人（ECG 正常组）未发生。ECG 模式包括终末 P 波终末力 V1、房间隔阻滞（IAB）、高级房间隔阻滞、异常 P 波轴、脉搏率延长和房性早搏。总体而言，研究期间共有 15762 例患者发生 AF（4.77%）。在 ECG 异常组中，比例为 14.21%（2367/16662），而在对照组（ECG 正常组）中，比例为 4.27%（13395/313622）。发生 AF 的风险比为 2.45（95%置信区间[CI]：2.02-2.98，P<0.001），异质性（I2）为 95%。alAB、P 波终末力 V1、房间隔阻滞、异常 P 波轴、脉搏率延长和房性早搏的风险比分别为 4.12（95%CI，2.99-5.66）、1.47（95%CI，1.19-1.82）、2.54（95%CI，1.83-3.52）、1.70（95%CI，0.98-2.97）、2.65（95%CI，1.88-3.72）、3.79（95%CI，2.12-6.76）。
心电图模式与 AF 的发生之间存在显著相关性。alAB 对 AF 的发生具有最高的预测能力。这些指标支持将其用作筛查工具，以识别中风后可能受益于进一步检查或经验性抗凝治疗的高危个体。
