Predicting Acute Kidney Injury in Acute Rhabdomyolysis

Abstract

Rhabdomyolysis is a clinical syndrome of significant skeletal muscle damage leading to electrolyte disturbance and kidney toxicity, which may result in acute kidney injury. The short-term impact of acute kidney injury includes a severity-dependent increased mortality and need for renal replacement therapy, while long-term effects include development and progression of chronic kidney disease, and increased cardiovascular risk. The ability to predict acute kidney injury early in the presentation is valuable for providing tailored preventative strategies, planning the intensity of monitoring, and appropriate resource allocation. Several clinical variables and biomarkers are reported to be associated with rhabdomyolysis-associated acute kidney injury, and a number of prediction models have been developed for this purpose. However, heterogeneity in study populations and methodology poses challenges to the utility and clinical integration of these variables and prediction models. This article explores and summarizes some of the relevant variables and models used to predict acute kidney injury in rhabdomyolysis, and discusses the uncertainties around the traditional biomarkers like creatine kinase and myoglobin, along with insights from recent observational studies.