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Precision of AI-Based Cardiac Ultrasound for LVEF in the Elderly

NCT06478901 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 129

Last updated 2024-06-27

No results posted yet for this study

Summary

Heart failure (HF) is common in older adults, especially those over 65. It is a leading cause of hospitalization and has high mortality rates. Diagnosing HF in elderly patients can be challenging due to atypical symptoms and multiple other health issues. Echocardiography, an ultrasound of the heart, is crucial for accurate diagnosis and treatment planning.

One problem in geriatric care is the difficulty of accessing echocardiography due to high demand and limited specialized doctors. Recent advancements show that AI-assisted portable ultrasound devices can reliably measure heart function, producing results comparable to traditional methods.

This study aims to evaluate the accuracy and relevance of AI-assisted echocardiography (AutoEF-AI) in elderly patients. It also assesses whether geriatricians, even without specialized training, can capture quality images for AI analysis.

In simple terms, this study investigates if portable ultrasound devices with AI can provide precise heart function diagnostics, making it easier for older adults with heart failure to get the care they need, even without specialists.

Conditions

  • Heart Failure
  • Heart Failure Systolic
  • Elderly
  • Artificial Intelligence

Interventions

DEVICE

Echocardiography

Echocardiography assited by Artificial intelligence

Sponsors & Collaborators

  • Hôpital Broca APHP

    lead OTHER

Eligibility

Min Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-01-14
Primary Completion
2024-02-02
Completion
2024-02-20

Countries

  • France

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06478901 on ClinicalTrials.gov