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Model predicts patient characteristics likely to result in CKD following acute kidney injury

A multivariable model that used routine laboratory data accurately predicted the likelihood of advanced chronic kidney disease following hospitalization with acute kidney injury, according to findings published in JAMA.

“Because not all patients who survive acute kidney injury progress to chronic kidney disease, follow-up of all patients hospitalized with acute kidney injury could lead to unnecessary use of clinical resources,” Matthew T. James, MD PhD, from the departments of medicine and community health sciences at the University of Calgary Cumming School of Medicine, Alberta, Canada, and colleagues wrote. “Identifying and screening patients at high risk of developing advanced chronic kidney disease could improve outcomes for patients following acute kidney injury.”

Many patients with acute kidney injury do not receive a follow-up assessment or appropriate care when their kidney function doesn’t recover, possibly because no risk-prediction tools exist to detect high-risk patients requiring follow-up, according to the researchers.

James and colleagues used data from two population-based cohorts of 9,973 Canadian patients who survived hospitalization with acute kidney injury to derive and validate risk prediction models for progression of acute kidney injury to advanced chronic kidney disease (CKD). They externally validated the risk models using data from a cohort of 2,761 patients hospitalized in another Canadian hospital. Using demographic, laboratory and comorbidity variables taken before discharge, they measured advanced CKD for at least 3 months during the year postdischarge. Participants were followed for up to 1 year.

More than 20% of all participants had stage 2 or 3 acute kidney injury. In total, 408 (2.7%) patients in the derivation cohort and 62 (2.2%) patients in the external validations cohort developed advanced CKD.

Six variables — including older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury and higher serum creatinine value at discharge — were independently associated with advanced CKD in the derivation cohort. Using a multivariable model that included these six variables in the external validation cohort showed a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex and discharge serum creatinine value alone or included age, sex and acute kidney injury stage alone.

“The predictor variables used in this model and risk index may be readily ascertained at the time of hospital discharge making it feasible for implementation within discharge planning processes to identify patients at high risk of developing advanced chronic kidney disease following hospitalization with acute kidney injury,” James and colleagues wrote. “Such risk stratification could help guide prognostic assessment and follow-up during transition to outpatient medical care, and inform resource allocation since advanced chronic kidney disease carries a high risk of complications, is accompanied by recommendations for assessment by nephrology specialists, and leads to high resource requirements to provide care.” – by Savannah Demko

Disclosures: James reports receiving support from a New Investigator and CIHR Foundation award from the Canadian Institutes of Health Research and grant support from Amgen Canada. Please see the study for all other authors’ relevant financial disclosures.