Relevance of Artificial Intelligence-Assisted Echocardiography for Left Ventricular Ejection Fraction Assessment in Geriatric Patients (REFERENCE-AI)
Heart failure (HF) is the leading cause of hospitalization among adults aged 80 years and older and represents a major diagnostic challenge in geriatric medicine due to frequently atypical clinical presentations and the presence of multiple comorbidities. Although transthoracic echocardiography (TTE) with measurement of left ventricular ejection fraction (LVEF) remains the gold standard for cardiac functional assessment, access to echocardiography is often limited in geriatric wards.
Recent advances in artificial intelligence (AI) have enabled the development of portable ultrasound devices and automated image analysis software capable of providing reliable and reproducible LVEF measurements. AI-assisted automated LVEF assessment (AutoEF-AI) may therefore represent a valuable alternative to conventional echocardiography for the cardiac evaluation of older patients with heart failure.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Prospective, single-center interventional study comparing two methods of left ventricular ejection fraction measurement in patients aged 75 years and older hospitalized for acute heart failure.Each hemodynamically stable participant will undergo two echocardiographic examinations performed within 24 hours:
- Standard Echocardiography (Reference Method)
- AI-assisted automated LVEF assessment (AutoEF-AI)
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Isabelle DUFOUR
- Phone Number: +33 (0) 185781011
- Email: isabelle.dufour@gerondif.org
Study Contact Backup
- Name: Prisca LUCAS, PhD MPH
- Phone Number: +33 (0)185737323
- Email: prisca.lucas@gerondif.org
Study Locations
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Paris, France, 75013
- Recruiting
- Broca Hospital
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Contact:
- Olivier HANON, MD PHD
- Phone Number: 01 44 08 33 81
- Email: olivier.hanon@aphp.fr
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Age ≥75 years.
- Hospitalization in a geriatric unit for acute heart failure according to the 2021 ESC diagnostic criteria.
- Hemodynamic stability at the time of echocardiographic examination.
- Ability to understand study information, provide written informed consent, and willingness to participate.
- Affiliation with, or beneficiary of, a health insurance/social security scheme.
Exclusion Criteria:
- Hemodynamic instability preventing echocardiographic assessment.
- Contraindication to transthoracic echocardiography.
- Patients under legal protection (guardianship, curatorship, or judicial protection measures) or unable to provide informed consent.
- Refusal to participate in the study.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Non-Randomized
- Interventional Model: Crossover Assignment
- Masking: Single
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
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Other: Standard Echocardiography (Reference method)
The standard echocardiography will be performed by a cardiologist as part of routine clinical care.
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The standard echocardiography will be performed by an expert cardiologist as part of routine clinical care and will serve as the gold standard
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Experimental: AutoEF-AI Assessment
AI-assisted automated LVEF assessment
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Performed by a geriatrician who has completed a one-day practical training session and combines:
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What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography.
Time Frame: At baseline
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Agreement will be assessed using:
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At baseline
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Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Diagnostic performance of AutoEF-AI for the detection of LVEF <50%, including sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy.
Time Frame: At baseline
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Calculation of the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and overall accuracy of AutoEF-AI for identifying left ventricular ejection fraction (LVEF) below 50%, compared with the standard reference method.
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At baseline
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Analysis of factors associated with agreement between the two methods
Time Frame: At baseline
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Multiple linear regression model will be used to identify clinical and technical variables (age, sex, cardiovascular history, presence of a pacemaker, cardiac arrhythmias, image quality, comorbidities, etc.) associated with a significant discrepancy between LVEF measurements obtained using AutoEF-AI and standard echocardiography.
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At baseline
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Feasibility of AutoEF-AI use by a geriatrician after a short training program
Time Frame: At baseline
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At baseline
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Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Olivier HANON, MD PhD, Geriatric Department, Broca hospital
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
- 2025-A02039-40
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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