Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter May 5, 2022

Estimating urine albumin to creatinine ratio from protein to creatinine ratio using same day measurement: validation of equations

Guillaume Résimont, Laura Vranken, Hans Pottel, François Jouret, Jean-Marie Krzesinski, Etienne Cavalier ORCID logo and Pierre Delanaye

Abstract

Objectives

Severity of chronic kidney disease is defined by glomerular filtration rate (GFR) and albuminuria (ACR) by the KDIGO and are related to cardiovascular outcomes and end-stage-kidney-failure. However, proteinuria (PCR) is more often available than ACR in records. Recently, equations were developed to estimate ACR from PCR. We investigated their performances in our population.

Methods

In the academic medical hospital of Liège, we retrospectively analysed same day measurement of ACR and PCR and staged them according to the KDIGO A1-A2-A3 categories. Analyser Roche Cobas (R) gathered 2,633 urinalysis (May 2018-May 2019) and analyser Abbott Alinity (A) 2,386 urinalysis (May 2019-March 2020). We compared the KDIGO staging of mACR and eACR obtained from Weaver’s and Sumida’s equations.

Results

Median age was 63 [52;71]/64 [53;72] years old, 43/42% were female; 78/74% had diabetes; proportion of mACR-A1 was 65.6%/64.2%, A2 was 25.5%/25.5% and A3 was 8.8%/10.3% (Method R/A, respectively). Both equations gave similar distribution of KDIGO staging of eACR. Overall agreements were higher than 88% regardless of the analyser or of the equation. Performances in between equations were equivalent according to the multi-level AUC (multinomial logistic regression model).

Conclusions

Good concordance was observed between mACR and eACR regardless of the equation or of the analyser. No patient with an A3-measured ACR was estimated within the KDIGO A1 category. Though ACR should be measured when clinically needed, it may be reasonably estimated from the PCR through these equations, for epidemiologic retrospective studies or research purposes.


Corresponding author: Guillaume Résimont, Nephrology-Dialysis-Transplantation, University of Liège, CHU Sart Tilman (CHU ULiège), Liège, Belgium, Phone: +32 43667111, Fax: +32 43667205, E-mail:

  1. Research funding: None declared.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Remnant samples only were used in this study. No specific approval was requested to the CHU de Liège Institutional Review Board as a leaflet including the following statement is given to all admitted patients: “According to the law of the December 19, 2008, any left-over of biological material collected from patients for their standard medical management and normally destroyed when all diagnostic analysis have been performed, can be used for validation of methods. The law authorizes such use except if the patient expressed an opposition when still alive (presumed consent). Written informed consent for participation was not required for this study in accordance with the Belgian national legislation and the Institutional requirements.

  5. Ethical approval: The local Institutional Review Board deemed the study exempt from review.

References

1. Kidney Disease: Improving Global Outcomes (KDIGO) CKD Work Group. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Suppl 2013;3:1–150.Search in Google Scholar

2. Matsushita, K, Coresh, J, Sang, Y, Chalmers, J, Fox, CS, Guallar, E, et al.. Estimated glomerular filtration rate and albuminuria for prediction of cardiovascular outcomes: a collaborative meta-analysis of individual participant data. Lancet Diabetes Endocrinol 2015;3:514–25. https://doi.org/10.1016/s2213-8587(15)00040-6.Search in Google Scholar

3. Tangri, N, Stevens, LA, Griffith, J, Tighiouart, H, Djurdjev, O, Naimark, D, et al.. A predictive model for progression of chronic kidney disease to kidney failure. JAMA 2011;305:1553–9. https://doi.org/10.1001/jama.2011.451.Search in Google Scholar PubMed

4. Résimont, G, Cavalier, E, Radermecker, RP, Delanaye, P. Albuminuria in diabetic patients: how to measure it?-a narrative review. J Lab Precis Med 2022;7:1–10.10.21037/jlpm-21-58Search in Google Scholar

5. Al-Wahsh, H, Lam, NN, Quinn, RR, Ronksley, PE, Sood, MM, Hemmelgarn, B, et al.. Calculated versus measured albumin-creatinine ratio to predict kidney failure and death in people with chronic kidney disease. Kidney Int 2022;Apr 7. https://doi.org/10.1016/j.kint.2022.02.034. [Epub ahead of print].Search in Google Scholar PubMed

6. Weaver, RG, James, MT, Ravani, P, Weaver, CGW, Lamb, EJ, Tonelli, M, et al.. Estimating urine albumin-to-creatinine ratio from protein-to-creatinine ratio: development of Equations using Same-Day Measurements. J Am Soc Nephrol 2020;31:591–601. https://doi.org/10.1681/asn.2019060605.Search in Google Scholar PubMed PubMed Central

7. Sumida, K, Nadkarni, GN, Grams, ME, Sang, Y, Ballew, SH, Coresh, J, et al.. Conversion of urine protein-creatinine ratio or urine dipstick protein to urine albumin-creatinine ratio for use in chronic kidney disease screening and prognosis: an individual participant-based meta-analysis. Ann Intern Med 2020;173:426–35. https://doi.org/10.7326/m20-0529.Search in Google Scholar

8. Bachmann, LM, Nilsson, G, Bruns, DE, McQueen, MJ, Lieske, JC, Zakowski, JJ, et al.. State of the art for measurement of urine albumin: comparison of routine measurement procedures to isotope dilution tandem mass spectrometry. Clin Chem 2014;60:471–80. https://doi.org/10.1373/clinchem.2013.210302.Search in Google Scholar PubMed

9. Jacobson, BE, Seccombe, DW, Katayev, A, Levin, A. A study examining the bias of albumin and albumin/creatinine ratio measurements in urine. Clin Chem Lab Med 2015;53:1737–43. https://doi.org/10.1515/cclm-2014-1105.Search in Google Scholar PubMed

10. Flachaire, E, Damour, O, Bienvenu, J, Aouiti, T, Later, R. Assessment of the benzethonium chloride method for routine determination of protein in cerebrospinal fluid and urine. Clin Chem 1983;29:343–5. https://doi.org/10.1093/clinchem/29.2.343.Search in Google Scholar

11. McElderry, LA, Tarbit, IF, Cassells-Smith, AJ. Six methods for urinary protein compared. Clin Chem 1982;28:356–60. https://doi.org/10.1093/clinchem/28.2.356.Search in Google Scholar

12. Dube, J, Girouard, J, Leclerc, P, Douville, P. Problems with the estimation of urine protein by automated assays. Clin Biochem 2005;38:479–85. https://doi.org/10.1016/j.clinbiochem.2004.12.010.Search in Google Scholar

13. Maisnar, V, Tichy, M, Stulik, J, Vavrova, J, Friedecky, B, Palicka, V, et al.. The problems of proteinuria measurement in urine with presence of Bence Jones protein. Clin Biochem 2011;44:403–5. https://doi.org/10.1016/j.clinbiochem.2011.01.008.Search in Google Scholar

14. Martin, H. Laboratory measurement of urine albumin and urine total protein in screening for proteinuria in chronic kidney disease. Clin Biochem Rev 2011;32:97–102.Search in Google Scholar

15. Shapiro, SS, Wilk, MB. An analysis of variance test for normality (complete samples). Biometrika 1965;52:591–611. https://doi.org/10.1093/biomet/52.3-4.591.Search in Google Scholar

16. Hanley, JA, McNeil, BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology 1982;143:29–36. https://doi.org/10.1148/radiology.143.1.7063747.Search in Google Scholar

17. Van Der Velde, M, Matsushita, K, Coresh, J, Astor, BC, Woodward, M, Levey, A, et al.. Lower estimated glomerular filtration rate and higher albuminuria are associated with all-cause and cardiovascular mortality. A collaborative meta-analysis of high-risk population cohorts. Kidney Int 2011;79:1341–52. https://doi.org/10.1038/ki.2010.536.Search in Google Scholar

18. Astor, BC, Matsushita, K, Gansevoort, RT, Van Der Velde, M, Woodward, M, Levey, AS, et al.. Lower estimated glomerular filtration rate and higher albuminuria are associated with mortality and end-stage renal disease. A collaborative meta-analysis of kidney disease population cohorts. Kidney Int 2011;79:1331–40. https://doi.org/10.1038/ki.2010.550.Search in Google Scholar

19. Matsushita, K, van der Velde, M, Astor, BC, Woodward, M, Levey, AS, de Jong, PE, et al.. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet 2010;375:2073–81. https://doi.org/10.1016/S0140-6736(10)60674-5.Search in Google Scholar

20. Gansevoort, RT, Matsushita, K, Van Der Velde, M, Astor, BC, Woodward, M, Levey, AS, et al.. Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts. Kidney Int 2011;80:93–104. https://doi.org/10.1038/ki.2010.531.Search in Google Scholar PubMed PubMed Central

21. Jonsson, AJ, Lund, SH, Eriksen, BO, Palsson, R, Indridason, OS. The prevalence of chronic kidney disease in Iceland according to KDIGO criteria and age-adapted estimated glomerular filtration rate thresholds. Kidney Int 2020;98:1286–95. https://doi.org/10.1016/j.kint.2020.06.017.Search in Google Scholar PubMed

22. Inker, LA, Astor, BC, Fox, CH, Isakova, T, Lash, JP, Peralta, CA, et al.. KDOQI US commentary on the 2012 KDIGO clinical practice guideline for the evaluation and management of CKD. Am J Kidney Dis 2014;63:713–35. https://doi.org/10.1053/j.ajkd.2014.01.416.Search in Google Scholar PubMed

23. National Clinical Guideline Centre (UK). Chronic Kidney Disease (Partial Update): Early Identification and Management of Chronic Kidney Disease in Adults in Primary and Secondary Care. London, UK: National Institute for Health and Care Excellence; 2014.Search in Google Scholar

24. Haute Autorité de Santé. Evaluation du rapport Albuminurie/Créatininurie dans le diagnostic de la maladie rénale chronique chez l’adulte; 2011. Available from https://www.has-sante.fr/jcms/c_1169049/fr/evaluation-du-rapport-albuminurie/creatininurie-dans-le-diagnostic-de-la-maladie-renale-chronique-chez-l-adulte-rapport-d-evaluation.10.1007/s11834-011-0066-4Search in Google Scholar

25. Résimont, G, Gadisseur, R, Lutteri, L, Krzesinski, J, Cavalier, E, Delanaye, P. Comment j’explore une protéinurie. Rev Med Liege 2018;73:519–25.Search in Google Scholar

26. Seegmiller, JC, Miller, WG, Bachmann, LM. Moving toward standardization of urine albumin measurements. EJIFCC 2017;28:258–67.Search in Google Scholar

27. Stempniewicz, N, Vassalotti, JA, Cuddeback, JK, Ciemins, E, Storfer-Isser, A, Sang, Y, et al.. Chronic kidney disease testing among primary care patients with type 2 diabetes across 24 U.S. health care organizations. Diabetes Care 2021;44:2000–9. https://doi.org/10.2337/dc20-2715.Search in Google Scholar PubMed PubMed Central

28. Jehn, U, Görlich, D, Reuter, S. The estimation formula for the urinary albumin-creatinine ratio based on the protein-creatinine ratio are not valid for a kidney transplant and a living donor cohort. J Am Soc Nephrol 2020;31:1915–6. https://doi.org/10.1681/asn.2020050545.Search in Google Scholar

29. Weaver, RG, Tonelli, M, Lamb, EJ, Hemmelgarn, BR. Authors’ reply. J Am Soc Nephrol 2020;31:1916–7. https://doi.org/10.1681/asn.2020050707.Search in Google Scholar PubMed PubMed Central


Supplementary Material

The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2022-0049).


Received: 2022-01-19
Accepted: 2022-04-20
Published Online: 2022-05-05
Published in Print: 2022-06-27

© 2022 Walter de Gruyter GmbH, Berlin/Boston

Scroll Up Arrow