Radiologist Diagnostic Performance Versus Artificial Intelligence (AI)

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

1000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2020-03-01

Study Completion Date

2021-10-30

Brief Summary

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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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Detailed Description

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Conditions

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Painful Hip Fonctional Impotence After Minor Trauma (Fall)

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Study Groups

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Suspicion of hip fracture

hip standard radiography/ CT scan/ MRI

Intervention Type PROCEDURE

hip standard radiography/ CT scan/ MRI

Interventions

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hip standard radiography/ CT scan/ MRI

Intervention Type PROCEDURE

Eligibility Criteria

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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