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

Artificial Intelligence-enhanced Electrocardiogram Diagnoses and Predicts Future

Status

Completed

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06475157

Enrollment

500000

Registered

2024-06-26

Start date

2024-03-01

Completion date

2024-05-30

Last updated

2024-07-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Electrocardiogram, Valvular Heart Disease

Brief summary

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

Interventions

OTHERNo intervention

No intervention is applied.

Study design

Observational model

CASE_CONTROL

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

ALL

Age

18 Years to No maximum

Healthy volunteers

Yes

Inclusion criteria

* Subjects that received ECG and echocardiography tests during a date frame.

Exclusion criteria

* Subjects who is younger than 18 years of age.

Design outcomes

Primary

Measure	Time frame	Description
Progression of valvular heart diseases	15 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.

Countries

China, United Kingdom

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026