Literature DB >> 16306852

Hematocrit influences immunoassay performance for the measurement of tacrolimus in whole blood.

Yolanda Armendáriz1, Sarela García, Rosa M Lopez, Leonor Pou.   

Abstract

The comparison between the MEIA II and the EMIT assays for tacrolimus measurement and the interference by the hematocrit were evaluated in 93 samples from routine therapeutic monitoring at tacrolimus concentrations less than 9 microg/L (group A). Additionally, the incidence of false-positive results were determined in samples (n=46) from patients who were not receiving the drug (group B). In group A, no statistical differences were observed between the mean+/-SD values obtained by MEIA II (5.14+/-2.28 microg/L) and EMIT (4.61+/-1.79 microg/L). The correlation coefficient and the regression equation (95% CI) between both assays, were 0.761 and EMIT=1.088 (0.90, 1.35) MEIA II -0.38 (-1.65, -0.46), respectively. When the samples were stratified according to the hematocrit, the median differences between the methods (MEIA II minus EMIT) were as follows: hematocrit<or=25%, 0.45 microg/L; hematocrit 25%-35%, 0.30 microg/L; and hematocrit>35%, 0.25 microg/L (P=0.02). In group B, false-positive results (above the detection limit) were observed in 63.04% of samples analyzed by MEIA II and in 2.17% of samples analyzed by EMIT. The median differences in apparent tacrolimus results were significantly higher in the samples with the lowest hematocrit: 2.2 microg/L, 1.4 microg/L, and 0.0 microg/L in samples with hematocrit<or=25%, 25%-35%, and >35%, respectively. In conclusion, the differences in the tacrolimus results obtained by MEIA and EMIT assays were higher in samples from patients with hematocrit less than 25%, and the MEIA assay demonstrated a high incidence of false-positive results.

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Year:  2005        PMID: 16306852     DOI: 10.1097/01.ftd.0000185769.36878.00

Source DB:  PubMed          Journal:  Ther Drug Monit        ISSN: 0163-4356            Impact factor:   3.681


  3 in total

1.  External evaluation of published population pharmacokinetic models of tacrolimus in adult renal transplant recipients.

Authors:  Chen-Yan Zhao; Zheng Jiao; Jun-Jun Mao; Xiao-Yan Qiu
Journal:  Br J Clin Pharmacol       Date:  2016-02-26       Impact factor: 4.335

2.  The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients.

Authors:  Kelly A Birdwell; Ben Grady; Leena Choi; Hua Xu; Aihua Bian; Josh C Denny; Min Jiang; Gayle Vranic; Melissa Basford; James D Cowan; Danielle M Richardson; Melanie P Robinson; Talat Alp Ikizler; Marylyn D Ritchie; Charles Michael Stein; David W Haas
Journal:  Pharmacogenet Genomics       Date:  2012-01       Impact factor: 2.089

3.  Combined approach with therapeutic drug monitoring and pharmacogenomics in renal transplant recipients.

Authors:  S Manvizhi; B S Mathew; D H Fleming; G Basu; G T John
Journal:  Indian J Nephrol       Date:  2013-01
  3 in total

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