An observational study in Hypertrophic Cardiomyopathy (HCM) and Left Ventricular Hypertrophy, sponsored by Second Affiliated Hospital, School of Medicine, Zhejiang University. Recruiting at 1 site in China. Open to participants aged 18 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2025-12-04.
Sponsored by Second Affiliated Hospital, School of Medicine, Zhejiang University · Observational
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.
To overcome the twin bottlenecks of late detection and poor inter-centre reproducibility, the project leverages a large, multicentre historical cohort and anchors its pipeline on the 12-lead ECG-an inexpensive, ubiquitously available signal that can be captured in any department. Using deep-learning architectures augmented with attention mechanisms, we will develop (1) a discriminative model that separates HCM from phenocopies and normal hearts, and (2) an algorithmic framework that remains stable across devices and populations. Model governance will be embedded through version-controlled releases, cloud-edge deployment, and an "offline replay" evaluation loop, producing an end-to-end evidence chain that mirrors real-world clinical workflows.
Exclusion Criteria:
Patients from whom analyzable ECG data cannot be obtained.
diagnosed with hypertrophic cardiomyopathy by echocardiography and cardiac magnetic resonance imaging
patients with left-ventricular hypertrophy attributable to non-hypertrophic cardiomyopathy conditions
healthy individuals without myocardial hypertrophy
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 2
model diagnostic performance
The accuracy rate of the model's phenotype-specific classification for patients with different patterns of myocardial hypertrophy
Time frame: year 2
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 2
Plan to share: No
No publications or documents are linked to this record.
Eligibility is decided by the study team. Share this record with your doctor or contact the team directly.
Contact study teamGet an email when the registry record changes — status, dates, results — or when someone posts here.
Sign in to followQuestions and observations about this study, from anyone following it. Not medical advice, and not a channel to the study team — their contact details are on the registry record.
Sign in to join the discussion. Reading takes no account; posting does. You choose a display name, and a pseudonym is the default.
Nothing here yet. If you are running this trial, taking part in it, or weighing whether to, this is the place to say so.
Second Affiliated Hospital, School of Medicine, Zhejiang University