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TRUVACE RECORD VERSION
record: TRV-2026-2462
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-11T01:46:25.402255Z
status: published
lens: g_space
sector: health
headline: Leveraging AI-ECG Technology for Early Notification and Tracking of AF Development (LATENT): A Randomized Controlled Trial
dek: Background Electrocardiographic analysis aided by artificial intelligence (AI) may identify atrial electrical vulnerability during sinus rhythm. The objective of this study was to determine whether AI-enabled ECG (AI-ECG) is effective for detecting atrial fibrillation (AF), atrial flutter (AFl), or prespecified pre-AF atrial findings in a randomized trial. Methods In this single-center, open-label trial, 14 665 adults 40 to 85 years of age without previous AF/AFl were randomized to an AI-ECG-guided strategy or u…
gain_title: In a randomized trial of 14,665 adults, AI-ECG-guided monitoring detected new atrial fibrillation, flutter or pre-AF findings in 0.74% of intervention participants versus 0.48% of controls.
problem_title: (none)
trace_subject: (none)
gain_reading: In a randomized trial of 14,665 adults, AI-ECG-guided monitoring detected new atrial fibrillation, flutter or pre-AF findings in 0.74% of intervention participants versus 0.48% of controls.
gain_evidence: The primary outcome occurred in 54 intervention participants (0.74%) versus 35 control participants (0.48% | AI-ECG-guided monitoring resulted in a modest increase in the detection of new AF, AFl, or pre-AF atrial findings.
problem_reading: (none)
problem_evidence: (none)
quick_read: A single-center, open-label randomized trial assigned 14,665 adults aged 40 to 85 with no prior atrial fibrillation (AF) or atrial flutter to an AI-ECG-guided strategy or usual care. The primary outcome, new AF, flutter or pre-AF atrial findings within 90 days, occurred in 54 intervention participants (0.74%) versus 35 controls (0.48%).

Only 84 of 7,337 intervention participants (1.1%) were flagged as high risk by the AI, and 48 of them (57.1%) underwent Holter monitoring of up to 7 days. Each was paired with an age- and sex-matched control who received identical monitoring, which was meant to reduce ascertainment bias.

The authors describe the increase in detection as modest and statistically fragile: the odds ratio was 1.54 (95% CI, 1.01-2.37; P=0.046), and reclassifying one intervention event as a nonevent moved the P value to 0.057. The trial measured detection, not patient outcomes, and the authors call for larger trials.
limitation: The authors say the findings were statistically fragile: reclassifying a single intervention event changed the P value from 0.046 to 0.057, and larger trials are needed to assess patient outcomes.
tag: Evidence-backed gain
key_points: The trial randomized 7,337 adults to AI-ECG-guided care and 7,328 to usual care. | Participants were 40 to 85 years old and had no previous AF or atrial flutter. | The AI flagged 84 intervention participants (1.1%) and 78 control participants (1.1%) as high risk. | Of the 84 high-risk intervention participants, 48 (57.1%) completed Holter monitoring of up to 7 days. | The primary outcome occurred in 0.74% of the intervention group versus 0.48% of controls (odds ratio 1.54; 95% CI, 1.01-2.37). | Reclassifying one intervention event as a nonevent changed the P value from 0.046 to 0.057. | Reporting cardiologists were blinded to AI results and randomized assignment.
rundown: The LATENT trial tested whether AI analysis of ordinary sinus-rhythm ECGs could identify people with atrial electrical vulnerability who would benefit from targeted rhythm monitoring. Adults without previous AF or flutter were randomized to an AI-ECG-guided strategy or usual care in a single-center, open-label design.

Intervention participants whose ECG from the preceding year was judged high risk by the AI were offered Holter monitoring for up to 7 days. Each monitored participant was paired with an age- and sex-matched control, chosen before control ECGs underwent AI analysis, who received identical monitoring.

The composite outcome covered newly detected AF, flutter or pre-AF findings such as frequent premature atrial complexes, short runs of them, or nonsustained AF or flutter. The intervention effect differed by baseline AI-ECG risk.

The authors conclude the result shows a clinical application of AI-ECG risk stratification for targeted surveillance and offers a foundation for larger trials of patient outcomes. The trial is registered as NCT06847932.
sources:
- peer_reviewed | Circulation | https://doi.org/10.1161/circulationaha.126.083540 | 2026-11-07
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