Hip fractures in especially older adults cause severe clinical and functional impacts. Despite improved surgical care, one year mortality remains 14-30%, and fewer than half of the survivors regain their pre-fracture functional status. After a hip fracture, patients are primarily concerned with what they will be able to do in daily life. Wihout accurate predictions of mobility and Activities of Daily Life (ADL) independence, it is difficult to set realistic expectations and make appropriate decisions regarding treatment and rehabilitation. While there have been advancements in developing predictive models for mortality following hip fractures, there is a notable gap in models focused on predicting functional recovery. This study aims to develop and validate a machine learning-based model that can predict mobility and ADL independence three months after obtaining a hip fracture.
| Facility | City | Region | Status |
|---|---|---|---|
| OLVG hospital | Amsterdam | Netherlands | Recruiting |
This page summarises publicly available registry data for informational purposes — not medical advice. Eligibility is determined by each study team; patients should discuss participation with their clinician.
View NCT07556263 on ClinicalTrials.gov ↗ ← All trials in the Netherlands