Acute kidney injury (AKI) is characterized by a sudden decline in kidney function. The Kidney Disease: Improving Global Outcomes (KDIGO) clinical practice guidelines define AKI based on an increase in serum creatinine (SCr) levels as well as a decrease in urine volume. For clinical researchers of AKI, the ability to handle longitudinal SCr data and flag AKI status and stage in individual patients is a fundamental skill. This article provides a practical guide for identifying AKI episodes from longitudinal SCr data using R programming. The methods described in this article are based on a hands-on seminar presented at the 68th Annual Meeting of the Japanese Society of Nephrology in 2025.
Miyamoto et al. (2026) studied this question.