Commonly used surrogates for baseline renal function affect the classification and prognosis of acute kidney injury

Abstract

Studies of acute kidney injury usually lack data on pre-admission kidney function and often substitute an inpatient or imputed serum creatinine as an estimate for baseline renal function. In this study, we compared the potential error introduced by using surrogates such as (1) an estimated glomerular filtration rate of 75 ml/min per 1.73 m(2) (suggested by the Acute Dialysis Quality Initiative), (2) a minimum inpatient serum creatinine value, and (3) the first admission serum creatinine value, with values computed using pre-admission renal function. The study covered a 12-month period and included a cohort of 4863 adults admitted to the Vanderbilt University Hospital. Use of both imputed and minimum baseline serum creatinine values significantly inflated the incidence of acute kidney injury by about half, producing low specificities of 77-80%. In contrast, use of the admission serum creatinine value as baseline significantly underestimated the incidence by about a third, yielding a low sensitivity of 39%. Application of any surrogate marker led to frequent misclassification of patient deaths after acute kidney injury and differences in both in-hospital and 60-day mortality rates. Our study found that commonly used surrogates for baseline serum creatinine result in bi-directional misclassification of the incidence and prognosis of acute kidney injury in a hospital setting.

Figure 1. a: In-Hospital Mortality Rates Grouped by Baseline Estimation Method

X-axis groups mortality rates by maximal AKIN stage achieved and are further stratified by baseline estimation method used. Y-axis plots the corresponding mortality rates with 95% confidence intervals shown. b: 60-Day Mortality Rates Grouped by Baseline Estimation Method. X-axis groups mortality rates by maximal AKIN stage achieved and are further stratified by baseline estimation method used. Y-axis plots the corresponding mortality rates with 95% confidence intervals shown.

Figure 1. a: In-Hospital Mortality Rates Grouped by Baseline Estimation Method

X-axis groups mortality rates by maximal AKIN stage achieved and are further stratified by baseline estimation method used. Y-axis plots the corresponding mortality rates with 95% confidence intervals shown. b: 60-Day Mortality Rates Grouped by Baseline Estimation Method. X-axis groups mortality rates by maximal AKIN stage achieved and are further stratified by baseline estimation method used. Y-axis plots the corresponding mortality rates with 95% confidence intervals shown.