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

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.

Protocol for a multicentre and prospective follow-up cohort study of early detection of atrial fibrillation, silent stroke and cognitive impairment in high-risk primary care patients: the PREFA-TE study

“…However, persistent barriers exist that go beyond individualised person-centred interventions and health promotion efforts. [41][42][43][44][45][46][47][48] The experts at the consensus conference recommend systematic screening for all individuals aged ≥75 years and suggest that systematic screening may also be considered for people aged 65-74 years who have additional risk factors, elevated biomarkers or a positive alert from digital devices. 43 44 49 Furthermore, the first practical guide on the use of digital devices for monitoring heart rhythm and frequency provides clarification on which technologies to employ and under what circumstances.…”

Echocardiography and Electrocardiography in Detecting Atrial Cardiomyopathy: A Promising Path to Predicting Cardioembolic Strokes and Atrial Fibrillation

“…Among them, 36% exhibited an LA-Sr value of <26%, but this specific condition did not show associations with age, sex, or traditional cardiovascular risk factors, including diabetes, hypertension, or chronic kidney disease, nor did it correlate with a history of heart failure or ischemic cardiopathy (Table 1). Not even the CHA2DS2-VASc score revealed differences among patients with an LA-Sr < 26%, emphasizing the potential limitations in discerning thrombogenic risk based on the evidence in the literature regarding the predictive power of ECG and TTE data [10][11][12][13][14][15][16][17][18]29,30,[45][46][47][48].…”

“…Several P-wave abnormalities were points of interest in the present study. A-IAB had a stronger predictive value for supraventricular arrhythmias in many clinical scenarios (mainly atrial flluter and AF, wich is denominated Bayés' Syndrome), for cardioembolic stroke, and for dementia [14][15][16][17][18]25]. A consensus document classified IAB as partial or advanced [16].…”

“…Concerning the ECG, numerous parameters are linked to both LA enlargement and dysfunction [10][11][12][13][14][15][16][17][18][19][20][21]. The most extensively studied P-wave indices encompass the interatrial blocks (IAB), the P-wave terminal force in V1 (PTFV1), and P-wave axis and voltages (Table S1) [21][22][23][24][25].…”