AI spots heart failure, valve disease from ECG in 2 seconds — SkimNews
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- Imperial College London researchers developed an AI tool that identifies signs of heart failure and heart valve disease from ECG results in less than two seconds, detecting up to 81% of heart failure cases and up to 90% of heart valve disease cases in a 67,000-patient US trial.
- British Heart Foundation funded the trial, with results presented at the European Society of Cardiology annual congress in Munich — the world's largest heart conference.
- Prof Fu Siong Ng said the technology could prioritize high-risk patients for echocardiograms, which patients currently wait several months to receive after referral.
- Dr Ahmed El-Medany, the BHF clinical research fellow who led the analysis, described the tool as a 'superhuman AI' and said the next challenge is designing handheld AI-led ECG readers for healthcare professionals.
- Ng said the AI model could also be run opportunistically on all ECGs done in a hospital to flag undiagnosed heart failure or valve disease in patients being tested for unrelated reasons.
- Dr Sonya Babu-Narayan, BHF clinical director, cautioned the technology cannot definitively diagnose or rule out either condition on its own, but delivers a 'very strong indication' someone may have them.
- Roughly 1 billion ECGs are performed worldwide each year, making the test one of medicine's most common — and a potentially massive deployment surface for the new tool.
Why it matters: ECGs are performed roughly a billion times a year worldwide, and patients currently wait months for the echocardiogram follow-up needed to confirm heart failure or valve disease. If deployed on routine ECG reads, the tool could both jump high-risk patients to the front of that queue and catch previously undiagnosed cases in people being tested for unrelated reasons — shifting ECG from a rhythm test into a screening tool for structural heart disease.
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