Why the study?
Can a clinical prediction model using machine learning algorithms accurately estimate the risk of postoperative delirium in geriatric hip fracture patients?
Can a clinical prediction model using machine learning algorithms accurately estimate the risk of postoperative delirium in geriatric hip fracture patients?
A machine learning-based clinical prediction model may help estimate the risk of postoperative delirium in geriatric hip fracture patients to guide preventative measures.
May guide delirium risk stratification in hip fracture patients; leaves open external validation before clinical use.
We developed a clinical prediction model that shows promise in estimating the risk of postoperative delirium in geriatric hip fracture patients. The clinical prediction model can play a beneficial role in decision-making for preventative measures for patients at risk of developing a delirium. If found to be externally valid, clinicians might use the available web-based application to help incorporate the model into clinical practice to aid decision-making and optimize preoperative prevention efforts.
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Oosterhoff et al. (2021) studied this question.
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