aceExternal validation of artificial intelligence-guided electrocardiogram (AI-ECG) in detecting asymptomatic left ventricular dysfunction: A systematic review and meta-analysis
Aim: Asymptomatic left ventricular dysfunction (LVD) represents a key and frequently under-recognized stage in the heart failure (HF) continuum. Early identification enables targeted prevention and timely initiation of evidence-based therapies. Artificial intelligence-enabled electrocardiography (AI-ECG) may provide a scalable alternative to imaging for LVD detection. This systematic review synthesized evidence from exclusively externally validated AI-ECG studies evaluating the detection of asymptomatic LVD, wit…
Across externally validated studies, AI-ECG discriminated asymptomatic left ventricular systolic dysfunction well, with performance broadly comparable to symptomatic populations, suggesting a scalable alternative to imaging.
The authors report high risk of bias driven by long intervals between ECG and echocardiogram, plus heterogeneity and small-study effects, so the results need cautious interpretation and further prospective validation.
Evidence
- Peer-reviewedAmerican Journal of Preventive Cardiology2026-05-30
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Truvace Impact Record TRV-2026-1837, v1: “External validation of artificial intelligence-guided electrocardiogram (AI-ECG) in detecting asymptomatic left ventricular dysfunction: A systematic review and meta-analysis.” Truvace, 2026-10-18. /record/TRV-2026-1837 (accessed at citation time). sha256 f8373d5ea7636316…
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