Felipe S Naranjo1,2, Yingying Sang3,4,5, Shoshana H Ballew3,4, Nikita Stempniewicz6, Stephan C Dunning7, Andrew S Levey8, Josef Coresh3,4, Morgan E Grams2,3. 1. Division of Nephrology, Department of Medicine, University of Nebraska Medical Center, Omaha, Nebraska. 2. Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland. 3. Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland. 4. Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland. 5. OptumLabs Visiting Fellow, Cambridge, Massachusetts. 6. American Medical Group Association, Alexandria, Virginia. 7. OptumLabs, Cambridge, Massachusetts. 8. Division of Nephrology, Tufts Medical Center, Boston, Massachusetts.
Abstract
Background: The four-variable kidney failure risk equation (KFRE) is a well-validated tool for patients with GFR <60 ml/min per 1.73 m2 and incorporates age, sex, GFR, and urine albumin-creatinine ratio (ACR) to forecast individual risk of kidney failure. Implementing the KFRE in electronic medical records is challenging, however, due to low ACR testing in clinical practice. The aim of this study was to determine, when ACR is missing, whether to impute ACR from protein-to-creatinine ratio (PCR) or dipstick protein for use in the four-variable KFRE, or to use the three-variable KFRE, which does not require ACR. Methods: Using electronic health records from OptumLabs Data Warehouse, patients with eGFR <60 ml/min per 1.73 m2 were categorized on the basis of the availability of ACR testing within the previous 3 years. For patients missing ACR, we extracted urine PCR and dipstick protein results, comparing the discrimination of the three-variable KFRE (age, sex, GFR) with the four-variable KFRE estimated using imputed ACR from PCR and dipstick protein levels. Results: There were 976,299 patients in 39 health care organizations; 59% were women, the mean age was 72 years, and mean eGFR was 47 ml/min per 1.73 m2. The proportion with ACR testing was 19% within the previous 3 years. An additional 2% had an available PCR and 36% had a dipstick protein; the remaining 43% had no form of albuminuria testing. The four-variable KFRE had significantly better discrimination than the three-variable KFRE among patients with ACR testing, PCR testing, and urine dipstick protein levels, even with imputed ACR for the latter two groups. Calibration of the four-variable KFRE was acceptable in each group, but the three-variable equation showed systematic bias in the groups that lacked ACR or PCR testing. Conclusions: Implementation of the KFRE in electronic medical records should incorporate ACR, even if only imputed from PCR or urine dipstick protein levels.
Background: The four-variable kidney failure risk equation (KFRE) is a well-validated tool for patients with GFR <60 ml/min per 1.73 m2 and incorporates age, sex, GFR, and urine albumin-creatinine ratio (ACR) to forecast individual risk of kidney failure. Implementing the KFRE in electronic medical records is challenging, however, due to low ACR testing in clinical practice. The aim of this study was to determine, when ACR is missing, whether to impute ACR from protein-to-creatinine ratio (PCR) or dipstick protein for use in the four-variable KFRE, or to use the three-variable KFRE, which does not require ACR. Methods: Using electronic health records from OptumLabs Data Warehouse, patients with eGFR <60 ml/min per 1.73 m2 were categorized on the basis of the availability of ACR testing within the previous 3 years. For patients missing ACR, we extracted urine PCR and dipstick protein results, comparing the discrimination of the three-variable KFRE (age, sex, GFR) with the four-variable KFRE estimated using imputed ACR from PCR and dipstick protein levels. Results: There were 976,299 patients in 39 health care organizations; 59% were women, the mean age was 72 years, and mean eGFR was 47 ml/min per 1.73 m2. The proportion with ACR testing was 19% within the previous 3 years. An additional 2% had an available PCR and 36% had a dipstick protein; the remaining 43% had no form of albuminuria testing. The four-variable KFRE had significantly better discrimination than the three-variable KFRE among patients with ACR testing, PCR testing, and urine dipstick protein levels, even with imputed ACR for the latter two groups. Calibration of the four-variable KFRE was acceptable in each group, but the three-variable equation showed systematic bias in the groups that lacked ACR or PCR testing. Conclusions: Implementation of the KFRE in electronic medical records should incorporate ACR, even if only imputed from PCR or urine dipstick protein levels.
Authors: Navdeep Tangri; Morgan E Grams; Andrew S Levey; Josef Coresh; Lawrence J Appel; Brad C Astor; Gabriel Chodick; Allan J Collins; Ognjenka Djurdjev; C Raina Elley; Marie Evans; Amit X Garg; Stein I Hallan; Lesley A Inker; Sadayoshi Ito; Sun Ha Jee; Csaba P Kovesdy; Florian Kronenberg; Hiddo J Lambers Heerspink; Angharad Marks; Girish N Nadkarni; Sankar D Navaneethan; Robert G Nelson; Stephanie Titze; Mark J Sarnak; Benedicte Stengel; Mark Woodward; Kunitoshi Iseki Journal: JAMA Date: 2016-01-12 Impact factor: 56.272
Authors: Juan Jesús Carrero; Morgan E Grams; Yingying Sang; Johan Ärnlöv; Alessandro Gasparini; Kunihiro Matsushita; Abdul R Qureshi; Marie Evans; Peter Barany; Bengt Lindholm; Shoshana H Ballew; Andrew S Levey; Ron T Gansevoort; Carl G Elinder; Josef Coresh Journal: Kidney Int Date: 2016-12-04 Impact factor: 10.612
Authors: Casey M Rebholz; Josef Coresh; Shoshana H Ballew; Blaithin McMahon; Seamus P Whelton; Elizabeth Selvin; Morgan E Grams Journal: Am J Kidney Dis Date: 2015-03-12 Impact factor: 8.860
Authors: Kunihiro Matsushita; Josef Coresh; Yingying Sang; John Chalmers; Caroline Fox; Eliseo Guallar; Tazeen Jafar; Simerjot K Jassal; Gijs W D Landman; Paul Muntner; Paul Roderick; Toshimi Sairenchi; Ben Schöttker; Anoop Shankar; Michael Shlipak; Marcello Tonelli; Jonathan Townend; Arjan van Zuilen; Kazumasa Yamagishi; Kentaro Yamashita; Ron Gansevoort; Mark Sarnak; David G Warnock; Mark Woodward; Johan Ärnlöv Journal: Lancet Diabetes Endocrinol Date: 2015-05-28 Impact factor: 32.069