ace[Atrial fibrillation screening-reading the P-wave]
Background Atrial fibrillation (AF) is frequently intermittent and may therefore remain undetected on a short resting electrocardiogram (ECG). At the same time, a sinus-rhythm ECG contains information on the underlying atrial substrate. Objective To review conventional and artificial intelligence (AI)-based ECG markers of an atrial risk phenotype and their potential role in targeted AF screening. Materials and methods Narrative appraisal of current consensus and guideline documents and of clinical, electrophysio…
AI models analyzing sinus-rhythm ECGs can identify atrial risk phenotypes and help select patients for prolonged rhythm monitoring to improve AF detection yield.
An AI-based P-wave risk score derived from sinus-rhythm ECG does not establish an AF diagnosis and alone does not constitute an indication for treatment, risking overinterpretation in screening.
Narrative appraisal rather than systematic trial, and AI-based risk scores do not by themselves establish AF diagnosis or justify treatment, limiting direct clinical actionability.
Evidence
- Peer-reviewedDie Innere Medizin2026-10-02
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Truvace Impact Record TRV-2026-1286, v1: “[Atrial fibrillation screening-reading the P-wave].” Truvace, 2026-10-05. /record/TRV-2026-1286 (accessed at citation time). sha256 cea28ff47b16be9b…
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