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AI-based Prediction of Cardiac Function Using Echocardiography and Body Composition Data (ECHO-FIT Study)

NCT06811519 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2025-03-04

No results posted yet for this study

Summary

This prospective observational study (ECHO-FIT Study) aims to develop and validate a predictive model for cardiac function, particularly left ventricular ejection fraction (LVEF), by integrating echocardiographic measurements with body composition data obtained from the QCCUNIQ BC 720 device.

The study plans to enroll 2,000 adult participants, comprising 1,000 individuals with normal LVEF (≥50%) and 1,000 with heart failure (LVEF \<50%), all of whom will undergo standard-of-care echocardiography and body composition analysis.

By analyzing the relationships between key echocardiographic parameters (such as LVEF and diastolic function) and body composition measures (including fat mass, skeletal muscle mass, and total body water), we will develop a non-invasive prediction model capable of identifying individuals at higher risk of cardiac dysfunction.

This innovative approach has the potential to enhance early detection and personalized management of heart failure, reduce dependence on resource-intensive diagnostic procedures, and ultimately improve patient outcomes.

Conditions

  • Heart Failure
  • Left Ventricular (LV) Systolic Dysfunction
  • Body Composition Measurement
  • Artificial Intelligence (AI)

Interventions

DIAGNOSTIC_TEST

Body Composition Analyzer (ACCUNIQ BC720)

Body Composition Analyzer (ACCUNIQ BC720)

Sponsors & Collaborators

  • Yonsei University

    lead OTHER

Principal Investigators

  • In Hyun Jung, MD., PhD. · Severance Hospital

Eligibility

Min Age
20 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2025-02-24
Primary Completion
2027-12-31
Completion
2028-12-31

Countries

  • South Korea

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06811519 on ClinicalTrials.gov