Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients

by Tezcan Ozrazgat-Baslanti, Yuanfang Ren, Esra Adiyeke, Rubab Islam, Haleh Hashemighouchani, Matthew Ruppert, Shunshun Miao, Tyler Loftus, Crystal Johnson-Mann, R. W. M. A. Madushani, Elizabeth A. Shenkman, William Hogan, Mark S. Segal, Gloria Lipori, Azra Bihorac, Charles Hobson Standard race adjustments for estimating glomerular filtration rate (GFR) and reference creatinine can yield a lower acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence among African American patients than non–race adjusted estimates. We developed two race-agnostic computable p henotypes that assess kidney health among 139,152 subjects admitted to the University of Florida Health between 1/2012–8/2019 by removing the race modifier from the estimated GFR and estimated creatinine formula used by the race-adjusted algorithm (race-agnostic algorithm 1) and by utilizing 2021 CKD-EPI refit without race formula (race-agnostic algorithm 2) for calculations of the estimated GFR and estimated creatinine. We compared results using these algorithms to the race-adjusted algorithm in African American patients. Using clinical adjudication, we validated race-agnostic computable phenotypes developed for preadmission CKD and AKI presence on 300 cases. Race adjustment reclassified 2,113 (8%) to no CKD and 7,901 (29%) to a less severe CKD stage compared to race-agnostic algorithm 1 and reclassified 1,208 (5%) to no CKD and 4,606 (18%) to a less severe CKD stage compared to race-agnostic algorithm...
Source: PLoS One - Category: Biomedical Science Authors: Source Type: research