Diagnosis of HCM With AI-ECG

March 4, 2024 updated by: Yixiu Liang, Shanghai Zhongshan Hospital

Diagnosis of Hypertrophic Cardiomyopathy With Artificial Intelligence-enhanced Electrocardiogram

The study aims to establish a diagnostic model of hypertrophic cardiomyopathy with artificial intelligence-enhanced electrocardiogram.

Study Overview

Status

Recruiting

Conditions

Study Type

Observational

Enrollment (Estimated)

10000

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

Yes

Sampling Method

Non-Probability Sample

Study Population

The study includes patients with HCM, and subjects without HCM as control.

Description

Inclusion Criteria:

  • Diagnosed with HCM

Exclusion Criteria:

  • Patients with ventricular pacing

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
HCM group
Patients diagnosed with HCM
Control group
Subjects without HCM

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Diagnosis of HCM with AI-ECG
Time Frame: 1 year within the time frame of ECG data collection

First a diagnosis of HCM is made as the standard outcome according to 1) an International Classification of Diseases (ICD) code for HCM (ICD-9425.1, 425.11, 425.18, and ICD10 I42.1, I42.2); 2) reports from the echocardiographers.

An AI-ECG algorithm will be used to make a diagnosis of HCM and compared with the standard outcome.

The performance of the AI-ECG algorithm will be evaluated with metrics including AU-ROC, specificity, sensitivity and F1 value.
1 year within the time frame of ECG data collection

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Shanghai Zhongshan Hospital

Investigators

  • Principal Investigator: Yixiu Liang, MD, Fudan University

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2024

Primary Completion (Estimated)

December 31, 2024

Study Completion (Estimated)

December 31, 2024

Study Registration Dates

First Submitted

April 8, 2023

First Submitted That Met QC Criteria

February 29, 2024

First Posted (Actual)

March 1, 2024

Study Record Updates

Last Update Posted (Estimated)

March 6, 2024

Last Update Submitted That Met QC Criteria

March 4, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • AI-ECG-HCM

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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