ArticlePloS one2024
Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 6 citations in OpenAlex.
- Reinforcement Learning for Intraoperative Hypotension Management with Consideration to Postoperative Acute Kidney Injury.Kidney360 · 2026Article
- Predicting Acute Kidney Injury with Nephrotoxic Burden in Noncritical Patients: An Internal and External Validation Study.Kidney360 · 2026Article
- SHREC: A framework for advancing next-generation computational phenotyping with large language models.PLOS digital health · 2026Article
- Multi-hospital electronic decision support for drug-associated acute kidney injury (MEnD-AKI): Study protocol for a randomized clinical trial.Contemporary clinical trials · 2025Article
- Diagnostic value of the urea-to-creatinine ratio for gastrointestinal bleeding source: influence of renal function.BMC nephrology · 2025Article
- SHREC: A Framework for Advancing Next-Generation Computational Phenotyping with Large Language Models.ArXiv · 2025Article
- Epidemiology, trajectories and outcomes of acute kidney injury among hospitalized patients: a large retrospective multicenter cohort study.Journal of nephrology · 2025Article
- Learning optimal treatment strategies for intraoperative hypotension using deep reinforcement learning.ArXiv · 2025Article
- Identifying a cohort of hospitalized chronic kidney disease patients using electronic health records: lessons learnt and implications for future research and clinical practice guidelines.Clinical kidney journal · 2025Article
- Clinical courses of acute kidney injury in hospitalized patients: a multistate analysis.Scientific reports · 2023Article
- Bilateral renal artery stenosis impacts postoperative complications after major vascular surgery.Surgery open science · 2023Article
- Clinical Considerations for Patients Experiencing Acute Kidney Injury Following Percutaneous Nephrolithotomy.Biomedicines · 2023Article
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Authors and funding
16 authors at 2 institutions in 1 country.
Funding
Abstract
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 phenotypes 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 2. Of 12,451 AKI encounters based on race-agnostic algorithm 1, race adjustment reclassified 591 to No AKI and 305 to a less severe AKI stage. Of 12,251 AKI encounters based on race-agnostic algorithm 2, race adjustment reclassified 382 to No AKI and 196 (1.6%) to a less severe AKI stage. The phenotyping algorithm based on refit without race formula performed well in identifying patients with CKD and AKI with a sensitivity of 100% (95% confidence interval [CI] 97%-100%) and 99% (95% CI 97%-100%) and a specificity of 88% (95% CI 82%-93%) and 98% (95% CI 93%-100%), respectively. Race-agnostic algorithms identified substantial proportions of additional patients with CKD and AKI compared to race-adjusted algorithm in African American patients. The phenotyping algorithm is promising in identifying patients with kidney disease and improving clinical decision-making.
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