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Clinical Trials/NCT04304742
NCT04304742
Completed
Not Applicable

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

University Hospital, Montpellier1 site in 1 country1,000 target enrollmentMarch 1, 2020

Overview

Phase
Not Applicable
Intervention
Not specified
Conditions
Painful Hip
Sponsor
University Hospital, Montpellier
Enrollment
1000
Locations
1
Primary Endpoint
Detection rate of femoral neck fracture
Status
Completed
Last Updated
4 years ago

Overview

Brief Summary

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.

Registry
clinicaltrials.gov
Start Date
March 1, 2020
End Date
October 30, 2021
Last Updated
4 years ago
Study Type
Observational
Sex
All

Investigators

Responsible Party
Sponsor

Eligibility Criteria

Inclusion Criteria

  • Not provided

Exclusion Criteria

  • Not provided

Outcomes

Primary Outcomes

Detection rate of femoral neck fracture

Time Frame: 1 day

Detection rate of femoral neck fracture

Secondary Outcomes

  • Detection rate of other hip fracture(1 day)

Study Sites (1)

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