Overview

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 after. 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 recovery after surgery. This study aims to develop and validate a machine learning model that can predict mobility and ADL independence three months after obtaining a hip fracture.

Eligibility

Inclusion Criteria:

• Patient has obtained a hip fracture, patient is older than 18 years

Exclusion Criteria:

• The patient does not grant permission for the use of their data