ArticleJournal of arrhythmia2025
AI-ECG for early detection of atrial fibrillation: First-year results from a stroke prevention study in Shimizu, Japan.
Article in Journal of arrhythmia, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Clinical and Echocardiographic Factors Associated With AI-Estimated Atrial Fibrillation Likelihood During Sinus Rhythm in Patients With Documented Paroxysmal Atrial Fibrillation.Journal of arrhythmia · 2026Article
- AI-ECG Risk Stratification for Atrial Fibrillation: Real-World Performance and Explainability.JACC. Advances · 2026Article
- Clinical artificial intelligence (AI) in Japan: Regulatory pathways, domain-specific evidence, and its data infrastructure from an international perspective.Global health & medicine · 2026Review
- Quantitative Measurement of Extracellular Vesicle-Sized Particles in Blood Plasma by Laser Diffraction Without an Extraction Process: A Proof-of-Concept Study in Atrial Fibrillation.Journal of arrhythmia · 2026Article
- Artificial intelligence-enabled electrocardiography from scientific research to clinical application.EMBO molecular medicine · 2026Review
- AI-ECG for early detection of atrial fibrillation: First-year results from a stroke prevention study in Shimizu, Japan.Journal of arrhythmia · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: An artificial intelligence algorithm-guided electrocardiogram (AI-ECG) has been developed to detect atrial fibrillation (AF) in patients with sinus rhythm (SR). However, its utility for population-based screening remains unclear in Japan. Method and Results: In this prospective cohort study, "SPAFS" (Stroke Prevention by Early Detection of AF in Shimizu), participants who underwent health examinations at the Shimizu Medical Association Examination Center from January 2022 to July 2023 were enrolled, with known AF excluded. ECGs were categorized by AI as low-, moderate-, or high risk: non-SR were labeled as non-applicable (NA). All participants underwent 7-day single-lead ECG monitoring. Among 362 participants (61.1 ± 10.5 years, 38% male, CHADS2 score 0.49 ± 0.70), AF was newly detected in 3.0% ( Conclusions: AI-ECG risk determination correlated with AF detection in a Japanese healthy cohort, especially in the aged population, supporting its utility as a population-based screening tool.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.