ARTIFICIAL INTELLIGENCE-BASED PREDICTION OF CLINICAL OUTCOMES IN PATIENTS SUSTAINING PROXIMAL HUMERAL FRACTURES
| Registry | NCT06467006, acronym Orthopredict |
|---|---|
| Status | Not yet recruiting |
| Study type | Observational |
| Enrollment | 500 (Estimated) |
| Sponsor | Consorci Sanitari de l'Anoia (Other); collaborators: Parc de Salut Mar, Parc Taulí Hospital Universitari |
| Conditions | Proximal Humeral Fracture |
| Interventions | Use of IA for proximal humeral fracture prognosis (Other) |
| Dates | start 2024-09-01 (estimated), primary completion 2026-12-01 (estimated), completion 2027-09-01 (estimated), first posted 2024-06-20, last updated 2024-06-20 |
Related Papers Related Patents Related Grants Related Experts
AI Assistant Save
All trials for Proximal Humeral Fracture All trials of Use of IA for proximal humeral fracture prognosis
Our smartphones can recognize the pictures of our family, loved ones and friends. Face recognition software leverages artificial intelligence (AI), image recognition and other advanced technology to map, analyze and confirm the identity of a face.
We humans do a poor job when classifying the injury related to a patient sustaining a proximal humeral fracture. In consequence, there is great heterogeneity in the treatment of proximal humerus fractures. Moreover, offering relevant information to patients regarding the risk of complications or fracture sequelae is challenging, given that the current series are based on obsolete classifications, and the published series bring together just over hundreds of patients analyzed. With these limitations, patients have few opportunities to participate in decision-making about their injury.
The present project aim is to integrate new technologies for the prediction of relevant clinical results for the patients presenting a proximal humeral fracture. In brief, AI can help identify similar fracture patterns without human inference, while humans can feed the algorithm with variables of interest such as the functional outcomes and complications related to this particular type of fracture.
Sex: All, ages: 18 Years to 90 Years
Inclusion Criteria: Patients sustaining a proximal humerus fracture treated nonoperatively under the criteria of the treating surgeon and patients' preference. Subjects evaluated within the first 3 weeks after the injury. Patients between 18 and 90 years of age. Patients who have been studied with simple shoulder radiographs in anteroposterior and scapular outlet projections. Participants who accept 1-year time follow-up. Exclusion Criteria: Patients with dementia or difficulty completing the evaluation after one year of follow-up. Patients who have previously received surgical treatment on the affected limb. Patients who have suffered a previous fracture in the affected limb. Surgically treated patients.