Prediction tool for chronic kidney disease following acute kidney injury

Reference

James MT, Pannu N, Hemmelgarn BR, et al. Derivation and external validation of prediction models for advanced chronic kidney disease following acute kidney injury. JAMA 2017;318(18):1787-1797.

Synopsis

Identifying patients at an increased risk of chronic renal disease after an acute kidney injury may help ameliorate disease progression. These investigators obtained data from a population-based, kidney disease network registry in Canada that includes serum creatinine measurements from acute care and outpatient settings. A derivation cohort (n = 9973) was assembled by randomly selecting two thirds of the cohort, with the remaining third serving as an internal validation cohort (n = 4985). An external validation cohort (n = 2761) was assembled by using data from a similar kidney disease network in a different province. Eligible patients included adult residents 18 years or older who required hospitalization for an acute kidney injury, defined as an increase in serum creatinine greater than 0.3 mg/dL or greater than 50% of their prehospitalization baseline. Other inclusion criteria included a baseline estimated glomerular filtration rate (eGFR) higher than 45 mL/min/1.73 m2 obtained between 7 days and 365 days prior to hospitalization, and at least 2 outpatient serum creatinine measurements separated by a minimum of 3 months with the first obtained between 30 days and 1 year after the hospital discharge date. Chronic renal disease was defined as a sustained eGFR of less than 30 mL/min/1.73 m2 within 30 days to 1 year after hospital discharge or initiation of chronic dialysis. Six variables were associated with an increased risk of progression to advanced chronic kidney disease: older age, female sex, higher baseline serum creatinine, albuminuria, greater acute kidney injury severity, and higher discharge serum creatinine level. The 6-variable model performed extremely well in predicting the risk of chronic kidney disease in the external validation cohort. The authors created a prediction tool based on point values for each variable, resulting in a total risk score predictive of advanced chronic kidney disease. See Essential Evidence Plus to access the scoring tool for point-of-care clinical use.