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利用窦性节律心电图异常预测缺血性脑卒中的 AF 风险:一项荟萃分析。

Predicting risk of AF in ischaemic stroke using sinus rhythm ECG abnormalities: A meta-analysis.

机构信息

Christchurch Hospital, Christchurch, New Zealand.

Royal Hobart Hospital, Hobart, TAS, Australia.

出版信息

Eur Stroke J. 2023 Sep;8(3):712-721. doi: 10.1177/23969873231172559. Epub 2023 May 2.

Abstract

OBJECTIVE

To identify ECG changes in sinus rhythm that may be used to predict subsequent development of new AF.

METHOD

We identified prospective and retrospective cohort or case control studies evaluating ECG patterns from a 12-lead ECG in sinus rhythm taken in hospital or community predicting subsequent development of new AF. For each identified ECG predictor, we then identify absolute event rates and pooled risk ratios (RR) using an aggregate level random effects meta-analysis.

RESULTS

We identified 609,496 patients from 22 studies. ECG patterns included P wave terminal force V1 (PTFV1), interatrial block (IAB) and advanced interatrial block (aIAB), abnormal P wave axis (aPWA), PR prolongation and atrial premature complexes (APCs). Pooled risk ratios reached significance for each of these; PTFV1 RR 1.48 (95% CI 1.04-2.10), IAB 2.54 (95% CI 1.64-3.93), aIAB 4.05 (95% CI 2.64-6.22), aPWA 1.89 (95% CI 1.25-2.85), PR prolongation 2.22 (95% CI 1.27-3.87) and APCs 3.71 (95% CI 2.23-6.16). Diabetes reduced the predictive value of PR prolongation.

CONCLUSION

APC and aIAB were most predictive of AF, while IAB, PR prolongation, PTFV1 and aPWA were also significantly associated with development of AF. These support their use in a screening tool to identify at risk cohorts who may benefit from further investigation, or following stroke, with empirical anticoagulation.

摘要

目的

确定窦性节律中的 ECG 变化,这些变化可用于预测新发生的 AF。

方法

我们确定了前瞻性和回顾性队列或病例对照研究,评估了在医院或社区中进行的 12 导联心电图中窦性节律的 ECG 模式,这些模式可预测新发生的 AF。对于每个确定的 ECG 预测因素,我们使用综合水平随机效应荟萃分析来确定绝对事件发生率和汇总风险比(RR)。

结果

我们从 22 项研究中确定了 609496 名患者。ECG 模式包括 P 波终末电势 V1(PTFV1)、房间隔阻滞(IAB)和高级房间隔阻滞(aIAB)、异常 P 波轴(aPWA)、PR 延长和房性期前收缩(APCs)。这些指标的汇总风险比均具有统计学意义;PTFV1 RR 为 1.48(95%CI 1.04-2.10),IAB 为 2.54(95%CI 1.64-3.93),aIAB 为 4.05(95%CI 2.64-6.22),aPWA 为 1.89(95%CI 1.25-2.85),PR 延长为 2.22(95%CI 1.27-3.87),APCs 为 3.71(95%CI 2.23-6.16)。糖尿病降低了 PR 延长的预测价值。

结论

APCs 和 aIAB 对 AF 的预测性最强,而 IAB、PR 延长、PTFV1 和 aPWA 也与 AF 的发生显著相关。这些结果支持将它们用于筛查工具,以识别可能受益于进一步调查或在中风后接受经验性抗凝治疗的高危患者群体。

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