Literature DB >> 28720681

The EuBIVAS Project: Within- and Between-Subject Biological Variation Data for Serum Creatinine Using Enzymatic and Alkaline Picrate Methods and Implications for Monitoring.

Anna Carobene1,2, Irene Marino3, Abdurrahman Coşkun4,2, Mustafa Serteser4, Ibrahim Unsal4, Elena Guerra3, William A Bartlett5,2, Sverre Sandberg6,7,2, Aasne Karine Aarsand6,2, Marit Sverresdotter Sylte6, Thomas Røraas7,2, Una Ørvim Sølvik8, Pilar Fernandez-Calle9,2, Jorge Díaz-Garzón9, Francesca Tosato10, Mario Plebani10, Niels Jonker11,2, Gerhard Barla11, Ferruccio Ceriotti12.   

Abstract

BACKGROUND: The European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) European Biological Variation Study (EuBIVAS) has been established to deliver rigorously determined biological variation (BV) indices. EuBIVAS determined BV for serum creatinine using the enzymatic and alkaline picrate measurement methods.
METHOD: In total, 91 healthy individuals (38 males, 53 females; age range, 21-69 years) were bled for 10 consecutive weeks at 6 European laboratories. An equivalent protocol was followed at each center. Sera were stored at -80 °C before analysis. Analyses for each patient were performed in duplicate within a single run on an ADVIA 2400 system (San Raffaele Hospital, Milan). The data were subjected to outlier and homogeneity analysis before performing CV-ANOVA to determine BV and analytical variation (CVA) estimates with confidence intervals (CI).
RESULTS: The within-subject BV estimates [CVI (95% CI)] were similar for enzymatic [4.4% (4.2-4.7)] and alkaline picrate [4.7% (4.4-4.9)] methods and lower than the estimate presently available online (CVI = 5.9%). No significant male/female BV differences were found. Significant differences were observed in mean creatinine values between men and women and between Turkish individuals and those of other nationalities. Between-subject BV (CVG) estimates, stratified accordingly, produced CVG values similar to historical BV data. CVA was 1.1% for the enzymatic and 4.4% for alkaline picrate methods, indicating that alkaline picrate methods fail to fulfill analytical performance specifications for imprecision (CVAPS).
CONCLUSIONS: The serum creatinine CVI obtained by EuBIVAS specifies a more stringent CVAPS than previously identified. The alkaline picrate method failed to meet this CVAPS, raising questions regarding its future use.
© 2017 American Association for Clinical Chemistry.

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Year:  2017        PMID: 28720681     DOI: 10.1373/clinchem.2017.275115

Source DB:  PubMed          Journal:  Clin Chem        ISSN: 0009-9147            Impact factor:   8.327


  8 in total

1.  European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates for serum biointact parathyroid hormone based on weekly samplings from 91 healthy participants.

Authors:  Michela Bottani; Giuseppe Banfi; Elena Guerra; Massimo Locatelli; Aasne K Aarsand; Abdurrahman Coşkun; Jorge Díaz-Garzón; Pilar Fernandez-Calle; Sverre Sandberg; Ferruccio Ceriotti; Elisabet González-Lao; Margarita Simon; Anna Carobene
Journal:  Ann Transl Med       Date:  2020-07

2.  Biological variation in the serum and urine kidney injury markers of a healthy population measured within 24 hours.

Authors:  Li-Rui Kong; Fei Wei; Da-Hai He; Chao-Qiong Zhou; Hong-Chuan Li; Feng Wu; Yu Luo; Jian-Wei Luo; Qian-Rong Xie; Hai Peng; Yan Zhang
Journal:  BMC Nephrol       Date:  2022-05-24       Impact factor: 2.585

Review 3.  Sigma metrics in laboratory medicine revisited: We are on the right road with the wrong map.

Authors:  Wytze P Oosterhuis; Abdurrahman Coskun
Journal:  Biochem Med (Zagreb)       Date:  2018-06-15       Impact factor: 2.313

Review 4.  Analytical Sigma metrics: A review of Six Sigma implementation tools for medical laboratories.

Authors:  Sten Westgard; Hassan Bayat; James O Westgard
Journal:  Biochem Med (Zagreb)       Date:  2018-06-15       Impact factor: 2.313

5.  Evaluation of biological variation of glycated hemoglobin and glycated albumin in healthy Chinese subjects.

Authors:  Libo Liang; He He; Yuping Zeng; Mei Zhang; Xia Wang; Xiaoling Li; Shanshan Liang; Zhenmei An; Hengjian Huang
Journal:  J Clin Lab Anal       Date:  2018-11-21       Impact factor: 2.352

6.  Avoiding insufficient therapies and overdosing with co-reporting eGFRs (estimated glomerular filtration rate) for personalized drug therapy and improved outcomes - a simulation of the financial benefits.

Authors:  Adrian Hoenle; Karin Johanna Haase; Sebastian Maus; Manfred Hofmann; Matthias Orth
Journal:  EJIFCC       Date:  2021-02-28

7.  Mechanistic Models as Framework for Understanding Biomarker Disposition: Prediction of Creatinine-Drug Interactions.

Authors:  Daniel Scotcher; Vikram Arya; Xinning Yang; Ping Zhao; Lei Zhang; Shiew-Mei Huang; Amin Rostami-Hodjegan; Aleksandra Galetin
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-05-14

8.  Physiologically-Based Pharmacokinetic Modelling of Creatinine-Drug Interactions in the Chronic Kidney Disease Population.

Authors:  Hiroyuki Takita; Daniel Scotcher; Rajkumar Chinnadurai; Philip A Kalra; Aleksandra Galetin
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-11-23
  8 in total

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