Risk prediction of kalaemia disturbance and acute kidney injury after total knee arthroplasty: use of a machine learning algorithm.
Journal:
Orthopaedics & traumatology, surgery & research : OTSR
PMID:
39047862
Abstract
INTRODUCTION: Total knee arthroplasty (TKA) is a procedure associated with risks of electrolyte and kidney function disorders, which are rare but can lead to serious complications if not correctly identified. A routine check-up is very often carried out to assess the seric ionogram and kidney function after TKA, that rarely requires clinical intervention in the event of a disturbance. The aim of this study was to identify perioperative variables that would lead to the creation of a machine learning model predicting the risk of kalaemia disorders and/or acute kidney injury after total knee arthroplasty.