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NCT06051682: FracturIA
Optimization of the Diagnosis of Bone Fractures in Patients Treated in the Emergency Department by Using Artificial Intelligence for Reading Radiological Images in Comparison With Traditional Reading by the Emergency Doctor.
NA trial testing Artificial intelligence in Artificial Intelligence in 1,500 participants. Status unknown.
11 September 2024
Quick facts
| Lead sponsor | Elsan |
|---|---|
| Phase | NA |
| Status | Status unknown |
| Study type | INTERVENTIONAL |
| Allocation | randomized |
| Design | parallel |
| Masking | none |
| Primary purpose | supportive care |
| Enrollment | 1,500 |
| Start date | 11 September 2023 |
| Primary completion | 11 September 2024 |
| Estimated completion | 11 October 2025 |
| Sites | 1 location across France |
Drugs / interventions tested
- Artificial intelligence
- Emergency physician
Conditions studied
- Artificial Intelligence — all drugs for Artificial Intelligence →
- Bone Fracture — all drugs for Bone Fracture →
Sponsor
Elsan — full company profile →
Who can join
18 and older, any sex, with Artificial Intelligence or Bone Fracture. Patients with the condition only — healthy volunteers not accepted.
Sponsor's own description
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.
Publications & conference data
No peer-reviewed publications indexed yet for this trial.
Verify or expand the search:
- PubMed search for NCT06051682
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Verify against primary sources
- ClinicalTrials.gov — authoritative US registry record
- WHO ICTRP — international registry index
- EU Clinical Trials Register
- Sponsor press releases (Google)
- Trial protocol + status: ClinicalTrials.gov NCT06051682 (US National Library of Medicine, public domain)
- Drug + disease cross-links: matched in real time against Drug Landscape's normalised drug + company + condition tables
- Sponsor: as reported to ClinicalTrials.gov by Elsan
- Last refreshed: 25 September 2023
Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT06051682.
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