Relevance of Artificial Intelligence-Assisted Echocardiography for Left Ventricular Ejection Fraction Assessment in Geriatric Patients

Overview

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.

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)

Interventions

• Diagnostic test AutoEF-AI Assessment
  Performed by a geriatrician who has completed a one-day practical training session and combines: * A handheld ultrasound device providing real-time image acquisition guidance for obtaining apical views. * Us2.ai software for automated LVEF analysis. The geriatrician is blinded to results of the gold standard echocardiography performed by the cardiologist.
• Diagnostic test Standard Echocardiography (Reference method)
  The standard echocardiography will be performed by an expert cardiologist as part of routine clinical care and will serve as the gold standard

Primary outcome measures

• Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography. [Time frame: At baseline]

Secondary outcome measures (3)

• 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]
• Analysis of factors associated with agreement between the two methods [Time frame: At baseline]
• Feasibility of AutoEF-AI use by a geriatrician after a short training program [Time frame: At baseline]

Eligibility criteria

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.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Allocation

Non-randomized

Model

Crossover

Masking

Single blind

Primary purpose

Diagnostic

Study locations

France · 1 center

• Broca Hospital — Paris

Identifiers

NCT: NCT07701369 · 2025-A02039-40

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗