Risk prediction to inform surveillance of chronic kidney disease in the US Healthcare Safety Net: a cohort study

BMC Nephrology

Research Article

Glenn M. Chertow¹  Delphine S. Tuot²  Jonathan Himmelfarb³  Marlena Maziarz⁴  Yuxiang Xie⁴  Yoshio N. Hall⁵ 

[1] Division of Nephrology, School of Medicine, Stanford University, Palo Alto, CA, USA;Division of Nephrology, University of California San Francisco and San Francisco General Hospital, San Francisco, CA, USA;Kidney Research Institute, Department of Medicine, University of Washington, Seattle, WA, USA;Kidney Research Institute, Department of Medicine, University of Washington, Seattle, WA, USA;Department of Biostatistics, University of Washington, Seattle, WA, USA;Kidney Research Institute, Department of Medicine, University of Washington, Seattle, WA, USA;Kidney Research Institute, University of Washington, Box 359606, 325 9th Ave, 98104, Seattle, WA, USA;

关键词: Chronic Kidney Disease;    Electronic Health Record;    Severe Chronic Kidney Disease;    United States Renal Data System;    Risk Predictive Model;   

DOI  :  10.1186/s12882-016-0272-0

 received in 2015-08-19, accepted in 2016-06-01,  发布年份 2016

来源: Springer

【 摘 要 】

BackgroundThe capacity of electronic health record (EHR) data to guide targeted surveillance in chronic kidney disease (CKD) is unclear. We sought to leverage EHR data for predicting risk of progressing from CKD to end-stage renal disease (ESRD) to help inform surveillance of CKD among vulnerable patients from the healthcare safety-net.MethodsWe conducted a retrospective cohort study of adults (n = 28,779) with CKD who received care within 2 regional safety-net health systems during 1996–2009 in the Western United States. The primary outcomes were progression to ESRD and death as ascertained by linkage with United States Renal Data System and Social Security Administration Death Master files, respectively, through September 29, 2011. We evaluated the performance of 3 models which included demographic, comorbidity and laboratory data to predict progression of CKD to ESRD in conditions commonly targeted for disease management (hypertension, diabetes, chronic viral diseases and severe CKD) using traditional discriminatory criteria (AUC) and recent criteria intended to guide population health management strategies.ResultsOverall, 1730 persons progressed to end-stage renal disease and 7628 died during median follow-up of 6.6 years. Performance of risk models incorporating common EHR variables was highest in hypertension, intermediate in diabetes and chronic viral diseases, and lowest in severe CKD. Surveillance of persons who were in the highest quintile of ESRD risk yielded 83–94 %, 74–95 %, and 75–82 % of cases who progressed to ESRD among patients with hypertension, diabetes and chronic viral diseases, respectively. Similar surveillance yielded 42–71 % of ESRD cases among those with severe CKD. Discrimination in all conditions was universally high (AUC ≥0.80) when evaluated using traditional criteria.ConclusionsRecently proposed discriminatory criteria account for varying risk distribution and when applied to common clinical conditions may help to inform surveillance of CKD in diverse populations.

【 授权许可】

CC BY   
© The Author(s). 2016