Standardization and improvement program for creatinine measurement in human serum
Current practices, quality control systems and proficiency testing schemes in clinical laboratories are likely unable to detect intrinsic bias in the in vitro diagnostic kits for creatinine as characterized or applied. A standardization program for clinical laboratories to determine the concentration of creatinine in human serum prior to estimate the glomerular filtration rate (eGFR) was conducted by the Mexican Association for Prevention of Chronic Diseases (AMPEC) and CENAM in 2016. In this study, 21 public and private clinical laboratories participated voluntarily and contributed with results of 27 measurement methods. These results were used to build a set of specific bias models, respectively, and then applied by each laboratory to correct their new measurements. A two-stage study was conducted; the first stage consisted of a blind experiment using certified reference material (CRM) DMR-574a of creatinine in human serum at three levels. The participating laboratories measured all three CRMs samples under a proficiency testing protocol using their routine methods. Linear regression with error in variables was applied to modeling the participants’ measurement method. In the second stage, each laboratory measured the concentration of creatinine in serum in approximately 100 samples from ambulatory patients, obtaining a total sample of 2416 measurements; subsequently, eGFR was calculated. In most of the participating laboratories (97 %), significant creatinine measurement bias was observed. Diagnosis based only on the concentration of creatinine in serum showed that: 72 % of the cases were correct, 23 % underestimated the eGFR and 5 % overestimated the eGFR. Bias is induced in the eGFR if no correction is made.
KeywordsCertified reference material Induced bias Calibration Standardization of creatinine Estimated glomerular filtration rate eGFR Uncertainty estimation
Thanks to the technical staff of the Division of Materials Metrology and to all the technical and management staff from the participating laboratories, whose experiments and professionalism made possible these data. Thanks to AMPEC members for their enthusiastic support and critical feedback. Suggestions for improving the article were given by two referees, we are thankful. Acknowledge to the PTB (Germany) for providing resources for presenting a related poster at the JCTLM meeting in 2017. We thank the anonymous reviewers for their careful reading of our manuscript and their many insightful comments and suggestions.
- 2.Ruiz-Arenas R et al (2017) A summary of worldwide national activities in Chronic Kidney Disease (CKD) testing. JIFCC 28(4):302–314Google Scholar
- 3.CENAM (2016) Expediente del Material de Referencia Certificado DMR574a Creatinina en Suero HumanoGoogle Scholar
- 6.BIPM-JCGM-100 (2008) Evaluation of measurement data—guide to the expression of uncertainty in measurementGoogle Scholar
- 8.CLSI Document C53-A (2010) Characterization and qualification of commutable reference materials for laboratory medicine; approved guideline. Clinical and Laboratory Standards Institute, WayneGoogle Scholar
- 9.KDIGO (2012) Clinical practice guideline for the evaluation and management of chronic kidney disease. www.kidney-international.org
- 10.R Core Team (2014) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org
- 11.Eaton JW et al (2014) GNU Octave version 3.8.1 manual: a high-level interactive language for numerical computations. CreateSpace Independent Publishing Platform. ISBN 1441413006. http://www.gnu.org/software/octave/doc/interpreter/
- 12.Bureau International des Poids et Mesures (2006) The International System of Units (SI), 8th edn. https://www.bipm.org/en/publications/si-brochure/