Artificial Intelligence-enhanced Electrocardiogram Diagnoses and Predicts Future Regurgitant Valvular Heart Diseases

Shanghai Zhongshan Hospital500,000 enrolled

Overview

This is a retrospective study to establish models for the prediction of future valvular heart diseases with artificial intelligence-enhanced electrocardiogram (ECG).

Study Type

OBSERVATIONAL

Enrollment

500,000

Conditions

Electrocardiogram, Valvular Heart Disease

Interventions

No interventionOTHER

No intervention is applied.

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria: * Subjects that received ECG and echocardiography tests during a date frame. Exclusion Criteria: * Subjects who is younger than 18 years of age.

Locations (2)

180 Fenglin Road

Shanghai, China

Hammersmiths Hospital

London, United Kingdom

Outcomes

Primary Outcomes

Progression of valvular heart diseases

There would be echo records of subjectes of the study during follow-up. So for subjects with baseline none or mild valvular heart diseases, including mitral regurgitation, aortic regurgitation, and tricuspid regurgitation, there might be some with progression to moderate or severe valvular heart diseases, and some other without this progression. The primary outcome of the study would be the progression of valvular heart diseases from none or mild to moderateor severe, as assessed by echocardiography.

Time frame: 15 years

Data from ClinicalTrials.gov

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