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.
연구 개요
상태
정황
상세 설명
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)
연구 유형
등록 (추정된)
단계
- 해당 없음
연락처 및 위치
연구 연락처
- 이름: Isabelle DUFOUR
- 전화번호: +33 (0) 185781011
- 이메일: isabelle.dufour@gerondif.org
연구 연락처 백업
- 이름: Prisca LUCAS, PhD MPH
- 전화번호: +33 (0)185737323
- 이메일: prisca.lucas@gerondif.org
연구 장소
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Paris, 프랑스, 75013
- 모병
- Broca Hospital
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연락하다:
- Olivier HANON, MD PHD
- 전화번호: 01 44 08 33 81
- 이메일: olivier.hanon@aphp.fr
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참여기준
자격 기준
공부할 수 있는 나이
- 고령자
건강한 자원 봉사자를 받아들입니다
설명
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.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 주 목적: 특수 증상
- 할당: 무작위화되지 않음
- 중재 모델: 크로스오버 할당
- 마스킹: 하나의
무기와 개입
참가자 그룹 / 팔 |
개입 / 치료 |
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다른: 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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실험적: 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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연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography.
기간: At baseline
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Agreement will be assessed using:
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At baseline
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2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
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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.
기간: 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
기간: 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
기간: At baseline
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At baseline
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공동 작업자 및 조사자
스폰서
수사관
- 수석 연구원: Olivier HANON, MD PhD, Geriatric Department, Broca hospital
연구 기록 날짜
연구 주요 날짜
연구 시작 (실제)
기본 완료 (추정된)
연구 완료 (추정된)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
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