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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.
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:
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Standard Echocardiography (Reference method) | Other | The standard echocardiography will be performed by a cardiologist as part of routine clinical care. |
|
| AutoEF-AI Assessment | Experimental | AI-assisted automated LVEF assessment |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AutoEF-AI Assessment | Diagnostic Test | Performed by a geriatrician who has completed a one-day practical training session and combines:
|
| Measure | Description | Time Frame |
|---|---|---|
| Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography. | Agreement will be assessed using:
| At baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Diagnostic performance of AutoEF-AI for the detection of LVEF <50%, including sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy. | 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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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Isabelle DUFOUR | Contact | +33 (0) 185781011 | isabelle.dufour@gerondif.org | |
| Prisca LUCAS, PhD MPH | Contact | +33 (0)185737323 | prisca.lucas@gerondif.org |
| Name | Affiliation | Role |
|---|---|---|
| Olivier HANON, MD PhD | Geriatric Department, Broca hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Broca Hospital | Paris | 75013 | France |
|
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Agreement between LVEF measured using AutoEF-AI and LVEF measured using standard echocardiography
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|
| Standard Echocardiography (Reference method) | Diagnostic Test | The standard echocardiography will be performed by an expert cardiologist as part of routine clinical care and will serve as the gold standard |
|
| At baseline |
| Analysis of factors associated with agreement between the two methods | 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. | At baseline |
| Feasibility of AutoEF-AI use by a geriatrician after a short training program |
| At baseline |
| ID | Term |
|---|---|
| D006333 | Heart Failure |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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