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

Completed
Conditions
Electrocardiogram, Valvular Heart Disease
Interventions
Other: No intervention
Registration Number
NCT06475157
Lead Sponsor
Shanghai Zhongshan Hospital
Brief Summary

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

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
500000
Inclusion Criteria
  • Subjects that received ECG and echocardiography tests during a date frame.
Exclusion Criteria
  • Subjects who is younger than 18 years of age.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
Patient group without progression of valvular heart diseasesNo intervention-
Patient group with progression of valvular heart diseasesNo intervention-
Primary Outcome Measures
NameTimeMethod
Progression of valvular heart diseases15 years

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.

Secondary Outcome Measures
NameTimeMethod

Trial Locations

Locations (2)

Hammersmiths Hospital

🇬🇧

London, United Kingdom

180 Fenglin Road

🇨🇳

Shanghai, China

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