Artificial Intelligence, Bone Fracture
Conditions
Brief summary
As part of the management of a patient with suspected bone fractures, emergency physicians are required to make treatment decisions before obtaining the imaging reading report from the radiologist, who is generally not available only a few hours after the patient's admission, or even the following day. This situation of the emergency doctor, alone interpreting the radiological image, in a context of limited time due to the large flow of patients to be treated, leads to a significant risk of interpretation error. Unrecognized fractures represent one of the main causes of diagnostic errors in emergency departments. This comparative study consists of two cohorts of patients referred to the emergency department for suspected bone fracture. The first will be of interest to patients whose radiological images will be interpreted by the reading of the emergency doctor systematically doubled by the reading of the artificial intelligence. The other will interest a group of patients cared for by the simple reading of the emergency doctor. All of the images from both groups of patients will be re-read by the establishment's group of radiologists no later than 24 hours following the patient's treatment. A centralized review will be provided by two expert radiologists. Also, patients in both groups will be systematically recalled in the event of detection of an unknown fracture for hospitalization.
Interventions
DEVICEArtificial intelligence
Artificial intelligence software : Boneview. It analyzes the x-rays, gives an assessment of the presence of fractures at the examination level and locates the fractures on each image by presenting them to the practitioner directly on their screen, without any other logistical constraints for the doctor.
PROCEDUREEmergency physician
the emergency physician analyzes the x-rays
Sponsors
Clinique Esquirol Saint Hilaire
Elsan
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Major Subject * Patient admitted to the emergency department for suspected peripheral fractures in the extremities of the upper limb and/or lower limb (wrist/hand and ankle/foot). * Patient affiliated to or entitled to a social security system * Patient having received written and informed information about the study and having signed a free and informed consent to participate in the study.
Exclusion criteria
* Patient previously admitted to the emergency room for suspicion of fractures and not included in the study * Patient admitted to the emergency room with suspicion of multiple fractures * Refusal to participate in the study * Protected patient: adult under guardianship, curatorship or other legal protection, deprived of liberty by judicial or administrative decision and under judicial protection * Pregnant, breastfeeding or parturient patient
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Patient readmission rate for failure to diagnose fracture during initial treatment. | 1 day | This rate will be determined in each group (reading by the emergency doctor systematically doubled by the reading of the AI vs. simple reading by the emergency doctor) compared to centralized rereading. |
Countries
France
Contacts
Primary ContactMartial MATINGOU, Dr
Outcome results
None listed