Acute kidney injury (AKI) is a critical condition associated with poor patient outcomes. We aimed to review the current concepts and future strategies regarding AKI risk prediction models.
Recent studies have shown that AKI occurs frequently in patients with common risk factors and certain medical conditions. Prediction models for AKI risk have been reported in medical fields such as critical care medicine, surgery, nephrotoxic agent exposure, and others. However, practical, generalizable, externally validated, and robust AKI prediction models remain relatively rare. Further efforts to develop AKI prediction models based on comprehensive clinical data, artificial intelligence, improved delivery of care, and novel biomarkers may help improve patient outcomes through precise AKI risk prediction.
This brief review provides insights for current concepts for AKI prediction model development. In addition, by overviewing the recent AKI prediction models in various medical fields, future strategies to construct advanced AKI prediction models are suggested.
aDepartment of Biomedical Sciences, Seoul National University College of Medicine
bDepartment of Internal Medicine, Armed Forces Capital Hospital
cDepartment of Internal Medicine, Seoul National University Hospital
dKidney Research Institute, Seoul National University College of Medicine, Seoul, South Korea
Correspondence to Hajeong Lee, MD, Ph.D., Department of Internal Medicine, Seoul National University Hospital, 101 Daehak-ro, Seoul 03080, Jongno-gu, South Korea. Tel: +82 2 2072 4905; e-mail: firstname.lastname@example.org