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AI PREDICTION FOR PROXIMAL HUMERAL FRACTURES

ARTIFICIAL INTELLIGENCE-BASED PREDICTION OF CLINICAL OUTCOMES IN PATIENTS SUSTAINING PROXIMAL HUMERAL FRACTURES

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06467006
Acronym
Orthopredict
Enrollment
500
Registered
2024-06-20
Start date
2024-09-30
Completion date
2027-09-30
Last updated
2024-06-20

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Proximal Humeral Fracture

Brief summary

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.

Interventions

OTHERUse of IA for proximal humeral fracture prognosis

None (prognosis study)

Sponsors

Parc de Salut Mar
CollaboratorOTHER
Parc Taulí Hospital Universitari
CollaboratorOTHER
Consorci Sanitari de l'Anoia
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
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.

Design outcomes

Primary

MeasureTime frameDescription
Constant-Murley Score1 yearFunctional outcome

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026