Background
AKI, Critical illness, critically ill, acute kidney injury
CRITICAL ILLNESS, CRITICALLY ILL
Critical illness often affects kidney function. Epidemiologic studies have shown that 40–60% of intensive care unit (ICU) patients have episodes of acute kidney injury (AKI) [Existing machine-learning predictions for kidney function have focused on predicting the onset of AKI [Despite the importance and need for continuous kidney function prediction, to the best of our knowledge, no prediction models for daily prediction of CrCl in critically ill patients exist. Hence, this study aims to develop and validate prediction models that apply machine learning algorithms to routinely collected patient data to predict CrCl one day ahead.