Precision Diagnosis and Prognostic Prediction of Hypertrophic Cardiomyopathy Using Artificial Intelligence: A Multicenter Study

Status: Recruiting
Location: See location...
Study Type: Observational
SUMMARY

By harnessing artificial intelligence to decode the 12-lead electrocardiogram, the project will enable precise ECG-based phenotyping of hypertrophic cardiomyopathy-accurately classifying septal, apical, and other morphologic subtypes-while simultaneously differentiating HCM from hypertensive heart disease, aortic stenosis, and other phenocopy disorders.

Eligibility
Participation Requirements
Sex: All
Minimum Age: 18
Healthy Volunteers: t
View:

• Adults aged ≥ 18 years.

• HCM cohort: Adults diagnosed with hypertrophic cardiomyopathy in accordance with the \*2023 Chinese Guidelines for the Diagnosis and Treatment of Hypertrophic Cardiomyopathy in Adults\*.

• HCM phenocopy cohort: Adults with an LV wall thickness ≥ 13 mm at any site on echocardiography.

• Healthy-control cohort: Adults with no history of cardiac disease and no evidence of myocardial hypertrophy on echocardiography.

Locations
Other Locations
China
Second Affiliated Hospital, Zhejiang University School of Medicine
RECRUITING
Hangzhou
Contact Information
Primary
Xiaojie Xie, MD, PhD
xiexj@zju.edu.cn
(+86)0571-87784700
Time Frame
Start Date: 2025-01-01
Estimated Completion Date: 2026-12-31
Participants
Target number of participants: 15000
Treatments
HCM
diagnosed with hypertrophic cardiomyopathy by echocardiography and cardiac magnetic resonance imaging
phenocopy
patients with left-ventricular hypertrophy attributable to non-hypertrophic cardiomyopathy conditions
normal control
healthy individuals without myocardial hypertrophy
Sponsors
Leads: Second Affiliated Hospital, School of Medicine, Zhejiang University

This content was sourced from clinicaltrials.gov