AI-Enabled Diagnosis and Prognosis of Hypertrophic Cardiomyopathy
Precision Diagnosis and Prognostic Prediction of Hypertrophic Cardiomyopathy Using Artificial Intelligence: A Multicenter Study
Second Affiliated Hospital, School of Medicine, Zhejiang University
15,000 participants
Jan 1, 2025
OBSERVATIONAL
Conditions
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
Inclusion Criteria4
- 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.
Exclusion Criteria1
- Patients from whom analyzable ECG data cannot be obtained.
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Locations(1)
View Full Details on ClinicalTrials.gov
For the most up-to-date information, visit the official listing.
NCT07263204