AI-Enabled Diagnosis and Prognosis of Hypertrophic Cardiomyopathy
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorSecond Affiliated Hospital, School of Medicine, Zhejiang University
About this trial
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 criteria
This trial accepts healthy volunteersQualifiers
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.
Disqualifiers
None
Trial population
1. HCM cohort: Adults diagnosed with hypertrophic cardiomyopathy in accordance with the \*2023 Chinese Guidelines for the Diagnosis and Treatment of Hypertrophic Cardiomyopathy in Adults\*. 2. HCM phenocopy cohort: Adults with an LV wall thickness ≥ 13 mm at any site on echocardiography. 3. Healthy-control cohort: Adults with no history of cardiac disease and no evidence of myocardial hypertrophy on echocardiography.
Trial design
Design model
Cohort
Time perspective
Retrospective
Treatments tested in this trial
Not listed
Trial groups
15,000 Participants
are grouped into 3 trial groupsGroup A: HCM
Group B: phenocopy
Group C: normal control
Trial outcomes
Primary outcomes
1
model diagnostic performance
Model performance was evaluated using calculated metrics including accuracy, sensitivity, specificity, and the area under the ROC curve (AUC).
Time frame
year 2Secondary outcomes
1
model diagnostic performance
The accuracy rate of the model's phenotype-specific classification for patients with different patterns of myocardial hypertrophy
Time frame
year 22
the model's generalizability
The model's diagnostic performance on the external, multicentre validation cohort, including overall accuracy, sensitivity, specificity, and area under the ROC curve (AUC).
Time frame
year 2Sponsors and contacts
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Source ClinicalTrials.gov