AI spots hidden heart valve risks in routine scans

NCT ID NCT07573852

Knowledge-focused Sponsor: Shanghai Zhongshan Hospital Source: ClinicalTrials.gov ↗

First seen Jun 26, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This completed study used artificial intelligence to analyze electrocardiograms (ECGs) and chest X-rays from over 116,000 adults. The goal was to see if combining these routine tests could predict which patients would develop moderate or severe heart valve regurgitation. The researchers hope this approach could help doctors decide who needs closer monitoring or earlier treatment.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to: If successful, this AI model could help doctors identify patients at risk of worsening heart valve disease earlier, using routine tests like ECG and chest X-rays.
What could go wrong: This is a retrospective study, meaning it looks back at existing data. It does not test a new treatment, and the AI model may not work as well in real-world settings or different patient groups.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

116,380 people

The number who actually took part.

Started

Jul 2017

Finished

Dec 2025

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

This study population was a retrospective multicenter, echo-phenotyped longitudinal cohort derived from routine clinical care. The development cohort was obtained from Zhongshan Hospital, Shanghai, China, and included consecutive adult patients receiving care between July 14, 2017 and December 31, 2023. An external validation cohort was obtained from a second center using the same eligibility framework. The cohort was anchored to routinely acquired ECG and CXR, with baseline echocardiography used to define prevalent valvular status and follow-up echocardiography used to determine progression to clinically significant regurgitant valvular heart disease.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Accepted

You do not need to have the condition being studied to take part.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: Adult patients aged ≥18 years. Underwent routine electrocardiography (ECG), chest radiography (CXR), and echocardiography within 60 days. Had subsequent follow-up echocardiographic data available for outcome ascertainment. Patients were identified from routine clinical practice in inpatient admission or outpatient evaluation settings. Exclusion Criteria: Age below the adult threshold. Missing any of the required baseline examinations (ECG, CXR, or echocardiography within 60 days). No follow-up echocardiographic data available. For future-risk evaluation in the test cohort, samples with moderate or severe regurgitation at baseline were excluded.

Get updates

Get notified about this study

Sign up to get updates when this study changes or when new studies for Regurgitation, aortic valve are added.

Vår säkerhetsrekommendation!

Genom att skicka in godkänner du våra Användarvillkor

Conditions

The condition(s) this trial relates to.

aortic valve insufficiency gastroesophageal reflux disease heart valve disorder mitral valve insufficiency

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Regurgitation, aortic valve Regurgitation, mitral Valvular heart disease stenosis and regurgitation Valvular heart diseases

AI spots hidden heart valve risks in routine scans

What the study statuses mean