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OpenTrials
Completed

NCT Number: NCT04304742

Radiologist Diagnostic Performance Versus Artificial Intelligence (AI)

In France, femoral neck fracture is mainly detected with interpretation of pelvis/hip X-ray imaging (French Health Authority recommandation).

However, up to 10% of fractures are not identified or misdiagnosed, especially in patients admitted to the emergency department.

Indeed, radiologists may be subject to excessive work, wich cause the risk of inaccurate on X-rays diagnosis.

The Artificial intelligence (AI) begins study the detection of fratures on medical imaging.

In this retropective study, this technology developed by GLEAMER company is tested to evaluate the detection rate of hip fracture and specifically femoral neck fracture, compared to the radiologist diagnostic, in eldery patients admitted in emergency department.

AI could optimize the diagnostic performance of radiologists (increase of confidence level) and improve the efficiency of suspected fractures sorting from emergency department.

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Key information

Conditions

Painful Hip Femoral Fractures Femoral Neck Fractures Fonctional Impotence After Minor Trauma (Fall) Fractures, Bone Hip Fractures Hip Injuries Leg Injuries Wounds and Injuries

Age range

60 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Uhmontpellier

Montpellier, 34295, France

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Patients aged 60 and older
  • Minor trauma
  • Admitted in emergency department for painful hip/fonctional impotence after minor trauma
  • Takes at least a hip radiography

Exclusion criteria

  • Painful before the minor trauma
  • Important trauma

Treatment and study plan

hip standard radiography/ CT scan/ MRI

Procedure

hip standard radiography/ CT scan/ MRI

Primary outcomes

  1. Detection rate of femoral neck fracture

    Time frame: 1 day

    Detection rate of femoral neck fracture

Secondary outcomes

  1. Detection rate of other hip fracture

    Time frame: 1 day

    Detection rate of other hip fracture

Sponsors and collaborators

Lead sponsor

University Hospital, Montpellier

Other

Registry information

Official study title

Retrospective Study Comparing Radiologist Diagnostic Performance Versus Artificial Intelligence (AI) for Hip Fracture Suspicion in Elderly Patients

Acronym: RAVIA

Important dates

Study start
2020
Primary completion
2021
Study completion
2021
First posted
Mar 11, 2020
Registry last updated
Apr 14, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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