Abstract
BACKGROUND: Although measuring albuminuria is the preferred method for defining and staging chronic kidney disease (CKD), total urine protein or dipstick protein is often measured instead.
OBJECTIVE: To develop equations for converting urine protein-creatinine ratio (PCR) and dipstick protein to urine albumin-creatinine ratio (ACR) and to test their diagnostic accuracy in CKD screening and staging.
DESIGN: Individual participant-based meta-analysis.
SETTING: 12 research and 21 clinical cohorts.
PARTICIPANTS: 919 383 adults with same-day measures of ACR and PCR or dipstick protein.
MEASUREMENTS: Equations to convert urine PCR and dipstick protein to ACR were developed and tested for purposes of CKD screening (ACR ≥30 mg/g) and staging (stage A2: ACR of 30 to 299 mg/g; stage A3: ACR ≥300 mg/g).
RESULTS: Median ACR was 14 mg/g (25th to 75th percentile of cohorts, 5 to 25 mg/g). The association between PCR and ACR was inconsistent for PCR values less than 50 mg/g. For higher PCR values, the PCR conversion equations demonstrated moderate sensitivity (91%, 75%, and 87%) and specificity (87%, 89%, and 98%) for screening (ACR >30 mg/g) and classification into stages A2 and A3, respectively. Urine dipstick categories of trace or greater, trace to +, and ++ for screening for ACR values greater than 30 mg/g and classification into stages A2 and A3, respectively, had moderate sensitivity (62%, 36%, and 78%) and high specificity (88%, 88%, and 98%). For individual risk prediction, the estimated 2-year 4-variable kidney failure risk equation using predicted ACR from PCR had discrimination similar to that of using observed ACR.
LIMITATION: Diverse methods of ACR and PCR quantification were used; measurements were not always performed in the same urine sample.
CONCLUSION: Urine ACR is the preferred measure of albuminuria; however, if ACR is not available, predicted ACR from PCR or urine dipstick protein may help in CKD screening, staging, and prognosis.
PRIMARY FUNDING SOURCE: National Institute of Diabetes and Digestive and Kidney Diseases and National Kidney Foundation.
Original language | English |
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Pages (from-to) | 426-435 |
Number of pages | 13 |
Journal | Annals of Internal Medicine |
Volume | 173 |
Issue number | 6 |
Early online date | 14 Jul 2020 |
DOIs | |
Publication status | Published - 15 Sep 2020 |
Keywords
- GLOMERULAR-FILTRATION-RATE
- COLLABORATIVE METAANALYSIS
- DIAGNOSTIC-ACCURACY
- GENERAL-POPULATION
- RENAL-DISEASE
- ALL-CAUSE
- RISK
- MORTALITY
- ASSOCIATION
- PREDICTION
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Profiles
-
Simon Sawhney
- School of Medicine, Medical Sciences & Nutrition, Applied Health Sciences - Senior Clinical Lecturer
- School of Medicine, Medical Sciences & Nutrition, Centre for Health Data Science
- Clinical Medicine
- School of Medicine, Medical Sciences & Nutrition, Farr Aberdeen
- School of Medicine, Medical Sciences & Nutrition, Data Safe Haven
Person: Academic, Clinical Academic