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.
Studieoversikt
Status
Forhold
Intervensjon / Behandling
Detaljert beskrivelse
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)
Studietype
Registrering (Antatt)
Fase
- Ikke aktuelt
Kontakter og plasseringer
Studiekontakt
- Navn: Isabelle DUFOUR
- Telefonnummer: +33 (0) 185781011
- E-post: isabelle.dufour@gerondif.org
Studer Kontakt Backup
- Navn: Prisca LUCAS, PhD MPH
- Telefonnummer: +33 (0)185737323
- E-post: prisca.lucas@gerondif.org
Studiesteder
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Paris, Frankrike, 75013
- Rekruttering
- Broca Hospital
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Ta kontakt med:
- Olivier HANON, MD PHD
- Telefonnummer: 01 44 08 33 81
- E-post: olivier.hanon@aphp.fr
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Deltakelseskriterier
Kvalifikasjonskriterier
Alder som er kvalifisert for studier
- Eldre voksen
Tar imot friske frivillige
Beskrivelse
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.
Studieplan
Hvordan er studiet utformet?
Designdetaljer
- Primært formål: Diagnostisk
- Tildeling: Ikke-randomisert
- Intervensjonsmodell: Crossover-oppdrag
- Masking: Enkelt
Våpen og intervensjoner
Deltakergruppe / Arm |
Intervensjon / Behandling |
|---|---|
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Annen: 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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Eksperimentell: 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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Hva måler studien?
Primære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
|---|---|---|
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Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography.
Tidsramme: At baseline
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Agreement will be assessed using:
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At baseline
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Sekundære resultatmål
Resultatmål |
Tiltaksbeskrivelse |
Tidsramme |
|---|---|---|
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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.
Tidsramme: 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
Tidsramme: 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
Tidsramme: At baseline
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At baseline
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Samarbeidspartnere og etterforskere
Sponsor
Etterforskere
- Hovedetterforsker: Olivier HANON, MD PhD, Geriatric Department, Broca hospital
Studierekorddatoer
Studer hoveddatoer
Studiestart (Faktiske)
Primær fullføring (Antatt)
Studiet fullført (Antatt)
Datoer for studieregistrering
Først innsendt
Først innsendt som oppfylte QC-kriteriene
Først lagt ut (Faktiske)
Oppdateringer av studieposter
Sist oppdatering lagt ut (Faktiske)
Siste oppdatering sendt inn som oppfylte QC-kriteriene
Sist bekreftet
Mer informasjon
Begreper knyttet til denne studien
Nøkkelord
Ytterligere relevante MeSH-vilkår
Andre studie-ID-numre
- 2025-A02039-40
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