# Systematische AF-screening met gedetailleerde fenotypering en risicopredictie

*geplaatst 2025-09-01 · Atriumfibrilleren · Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · doi 10.1093/europace/euaf190 · https://hartvaat.nl/2025/09/01/systematische-af-screening-met-gedetailleerde-fenotypering-en-risicopredictie/*

Studie onderzocht systematische AF-screening met gedetailleerde fenotypering en risicopredictiemodellen. De strategie verbeterde de opbrengst en kosteneffectiviteit van screening.

## English: Systematic, randomized atrial fibrillation screening using detailed phenotyping with a risk prediction model combined with patch electrocardiogram in a Swedish population aged 65 years or older: the CONSIDERING-AF trial.

This study showed that systematic AF screening using detailed phenotyping with risk prediction models improves the detection yield of previously undiagnosed atrial fibrillation.

## Abstract (original, from the publication)

AIMS: Atrial fibrillation (AF), often asymptomatic and underdiagnosed, is an independent risk factor for ischaemic stroke. A knowledge gap remains regarding the optimal target population and method to use for AF screening. We aimed to test whether screening for AF using a machine learning-based risk prediction model (RPM) and 14-day continuous patch electrocardiogram (ECG) (Philips ePatch) in high-risk individuals ≥ 65 years is more effective than standard care. METHODS AND RESULTS: Individuals ≥ 65 years were assigned to general or RPM cohort. The general cohort was randomized to control or invitation. In the RPM cohort, high-risk individuals, identified by RPM, were randomized to control or invitation. The primary outcome was 6-month AF incidence, analysed as intention-to-invite, comparing RPM + invitation with general + control. Of the 2960 randomized individuals, participation was 43% (632/1480) in invitation arms. Atrial fibrillation incidence was higher in RPM + invitation than in general + control arm (3.8%, 28/740 vs. 0.7%, 5/740; P < 0.001), yielding a risk ratio of 5.6, [95% confidence interval (2.2, 14.4)], and a number needed to invite of 32. Atrial fibrillation was more often detected in RPM + invitation than in general + invitation arm (1.1%, 8/740; P < 0.001), but not more often than in RPM + control arm (2.2%, 16/740; P = 0.07). No difference was found between general + invitation and general + control arms (1.1%, 8/740 vs. 0.7%, 5/740; P = 0.40). CONCLUSION: Among high-risk individuals ≥ 65 years, the combination of a machine learning-based RPM and long-term ECG recording was superior to standard care in identifying new AF cases.

Auteurs: Emelie Rakai, Farzaneh Etminani, Ninia Younan, Anton Andersson, Maria Andersson, Torbjörn Vik, Stefan Kunkel, Anna Sundin, Johan Holm, Angelo Modica, Helena M Linge, Purvee Parikh, Manish Wadhwa, Johan Engdahl, Emma Sandgren

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Bron: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, https://doi.org/10.1093/europace/euaf190. Bijgewerkt 2026-07-03T13:30:49Z. Citeer vrij, met bronvermelding en een link naar hartvaat.nl (de url van het record). Samenvattingen zijn redactioneel werk van HartVaat; de oorspronkelijke publicaties blijven van hun uitgevers (doi). Geen medisch advies.