AI-based Prediction of Cardiac Function Using Echocardiography and Body Composition Data (ECHO-FIT Study)
ECHO-FIT
1 other identifier
observational
2,000
1 country
1
Brief 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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Feb 2025
Longer than P75 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
January 31, 2025
CompletedFirst Posted
Study publicly available on registry
February 6, 2025
CompletedStudy Start
First participant enrolled
February 24, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2027
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 31, 2028
March 4, 2025
March 1, 2025
2.8 years
January 31, 2025
March 1, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Left Ventricular Ejection Fraction < 50%
Prediction of Left Ventricular Ejection Fraction \< 50%
within 1 week
Study Arms (1)
Diagnostic Test: Scanning body composition analyzer and performing AI algorithms
Diagnostic Test: Scanning body composition analyzer and performing AI algorithms
Interventions
Body Composition Analyzer (ACCUNIQ BC720)
Eligibility Criteria
This study is conducted in patients who have undergone transthoracic echocardiography.
You may qualify if:
- Aged 20 years or older.
- Undergoing a standard echocardiographic examination.
- Providing consent to undergo body composition analysis.
- Signing the informed consent form to voluntarily participate in the study.
You may not qualify if:
- Having a physical or mental condition that makes it impossible to conduct an echocardiogram or perform body composition analysis.
- Deemed inappropriate for study participation by the researcher (e.g., unable to cooperate).
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Yongin Severance Hospital
Yongin, Gyeonggi-do, 16995, South Korea
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
In Hyun Jung, MD., PhD.
Severance Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE CROSSOVER
- Time Perspective
- PROSPECTIVE
- Target Duration
- 1 Year
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Professor
Study Record Dates
First Submitted
January 31, 2025
First Posted
February 6, 2025
Study Start
February 24, 2025
Primary Completion (Estimated)
December 31, 2027
Study Completion (Estimated)
December 31, 2028
Last Updated
March 4, 2025
Record last verified: 2025-03