Palano Francesca, Adduci Carmen, Cosentino Pietro, Silvetti Giacomo, Boldini Francesca, Francia Pietro
Division of Cardiology, Department of Clinical and Molecular Medicine, Sapienza University, Rome, Via di Grottarossa 1035, 00189, Rome, Italy.
High Blood Press Cardiovasc Prev. 2020 Oct;27(5):341-347. doi: 10.1007/s40292-020-00390-1. Epub 2020 May 25.
Atrial fibrillation (AF) is the most common cardiac arrhythmia. Pharmacologic and non-pharmacologic rhythm control strategies impact on AF-related symptoms, while leaving largely unaffected the risk of stroke. Moreover, up to 20% of AF patients are asymptomatic during paroxysmal relapses of arrhythmia, thus underlying the need for early markers to identify at-risk patients and prevent cerebrovascular accidents. Indeed, non-invasive assessment of pre-clinical substrate changes that predispose to AF could provide early identification of at-risk patients and allow for tailored care paths. ECG-derived P wave analysis is a simple-to-use and inexpensive tool that has been successfully employed to detect AF-associated structural and functional atrial changes. Beyond standard electrocardiographic techniques, high resolution signal averaged electrocardiography (SAECG), by recording microvolt amplitude atrial signals, allows more accurate analysis of the P wave and possibly AF risk stratification. This review focuses on the evidence that support P wave analysis to assess AF substrates, predict arrhythmia relapses and guide rhythm-control interventions.
心房颤动(AF)是最常见的心律失常。药物和非药物节律控制策略会影响与AF相关的症状,而对中风风险的影响则微乎其微。此外,高达20%的AF患者在心律失常阵发性复发期间无症状,因此需要早期标志物来识别高危患者并预防脑血管意外。事实上,对易引发AF的临床前基质变化进行非侵入性评估,可以早期识别高危患者并制定个性化的治疗方案。基于心电图的P波分析是一种简单易用且成本低廉的工具,已成功用于检测与AF相关的心房结构和功能变化。除了标准心电图技术外,高分辨率信号平均心电图(SAECG)通过记录微伏级振幅的心房信号,能够更准确地分析P波,并可能对AF进行风险分层。本综述重点关注支持P波分析以评估AF基质、预测心律失常复发和指导节律控制干预的证据。