Loading
Life sciences · Review
Annals of Noninvasive Electrocardiology · October 28, 2026
No summary has been generated for this record yet. What follows is drawn from its source metadata only.
Review.
No findings were extractable from the material analysed.
Safety was not reported in the material analysed. Check the source before drawing any conclusion about harm.
The source did not state who this applies to in practice.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
This record has not been graded across any dimension yet. Treat the label above as provisional and read the source.
What is missing. This record has no bottom line, key findings, reported figures, evidence dimensions. That is a gap in the analysis, not a judgement about the study.
ABSTRACT Background Left ventricular systolic dysfunction (LVSD) is common and treatable but often undiagnosed, especially in early stages with non‐specific symptoms. AI applied to standard ECGs offers low‐cost screening for low ejection fraction (EF), yet its real‐world impact on diagnosis remains unclear. Methods A systematic review and meta‐analysis of RCTs assessed AI‐ECG screening for low EF in clinical practice. The protocol was registered with PROSPERO (CRD420261287652). Databases (PubMed, Scopus, Cochrane Central, Google Scholar) were searched from inception to January 18, 2026, for RCTs comparing AI‐ECG screening to usual care in adults without known heart failure undergoing routine ECGs. The primary outcome was new low EF (≤ 50%) confirmed by echocardiography. Secondary outcomes included echocardiography referral rates, positive predictive value, and cardiology referral rates. Pooled risk ratios (RR) with 95% CIs were calculated using a random‐effects model. Results Three RCTs were included (two individual and one cluster) with 37,467 participants. After adjusting for clustering, AI‐ECG screening significantly improved detection of new low EF diagnoses compared to usual care (RR 1.36, 95% CI 1.12 to 1.64; p = 0.002; I 2 = 0%), with a number needed to screen of 204. No significant difference was found in echocardiography referral rates (RR 1.02, 95% CI 0.96 to 1.09; p = 0.55; I 2 = 36%). The PPV of the AI tool ranged from approximately 20% to 34% across studies. Conclusion AI‐ECG screening added to routine care improves low EF detection without substantially increasing echocardiography referrals. These findings support AI‐ECG for earlier LVSD detection in at‐risk populations, though further validation across diverse AI platforms is warranted.