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.
Study Type
OBSERVATIONAL
Enrollment
1,200
OLVG hospital
Amsterdam, Netherlands
"Estimated mobility 3 months, after obtaining a hip fracture" "Estimated ADL independence 3 months after obtaining a hip fracture"
For the outcome mobility participants get to know if they will be mobility independent (score 1-3 will get a 0) or mobility depenedent (score 4-5 will get a 0). for the outcome ADL independence patients get a score indicating whether ADL is maintained/better (1) and else if ADL is deteriorated (0).
Time frame: ADL independence and mobility 3 months after a hip fracture
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