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Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models

Background: The validity of the entire renal function tests as a diagnostic tool depends substantially on the Biological Reference Interval (BRI) of urea. Establishment of BRI of urea is difficult partly because exclusion criteria for selection of reference data are quite rigid and partly due to the...

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Autor principal: Sarkar, Rajarshi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Communications and Publications Division (CPD) of the IFCC 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4975168/
https://www.ncbi.nlm.nih.gov/pubmed/27683439
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author Sarkar, Rajarshi
author_facet Sarkar, Rajarshi
author_sort Sarkar, Rajarshi
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description Background: The validity of the entire renal function tests as a diagnostic tool depends substantially on the Biological Reference Interval (BRI) of urea. Establishment of BRI of urea is difficult partly because exclusion criteria for selection of reference data are quite rigid and partly due to the compartmentalization considerations regarding age and sex of the reference individuals. Moreover, construction of Biological Reference Curve (BRC) of urea is imperative to highlight the partitioning requirements. Materials and Methods: This a priori study examines the data collected by measuring serum urea of 3202 age and sex matched individuals, aged between 1 and 80 years, by a kinetic UV Urease/GLDH method on a Roche Cobas 6000 auto-analyzer. Results: Mann-Whitney U test of the reference data confirmed the partitioning requirement by both age and sex. Further statistical analysis revealed the incompatibility of the data for a proposed parametric model. Hence the data was non-parametrically analysed. BRI was found to be identical for both sexes till the 2(nd) decade, and the BRI for males increased progressively 6(th) decade onwards. Four non-parametric models were postulated for construction of BRC: Gaussian kernel, double kernel, local mean and local constant, of which the last one generated the best-fitting curves. Conclusion: Clinical decision making should become easier and diagnostic implications of renal function tests should become more meaningful if this BRI is followed and the BRC is used as a desktop tool in conjunction with similar data for serum creatinine.
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spelling pubmed-49751682016-09-28 Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models Sarkar, Rajarshi EJIFCC Research Article Background: The validity of the entire renal function tests as a diagnostic tool depends substantially on the Biological Reference Interval (BRI) of urea. Establishment of BRI of urea is difficult partly because exclusion criteria for selection of reference data are quite rigid and partly due to the compartmentalization considerations regarding age and sex of the reference individuals. Moreover, construction of Biological Reference Curve (BRC) of urea is imperative to highlight the partitioning requirements. Materials and Methods: This a priori study examines the data collected by measuring serum urea of 3202 age and sex matched individuals, aged between 1 and 80 years, by a kinetic UV Urease/GLDH method on a Roche Cobas 6000 auto-analyzer. Results: Mann-Whitney U test of the reference data confirmed the partitioning requirement by both age and sex. Further statistical analysis revealed the incompatibility of the data for a proposed parametric model. Hence the data was non-parametrically analysed. BRI was found to be identical for both sexes till the 2(nd) decade, and the BRI for males increased progressively 6(th) decade onwards. Four non-parametric models were postulated for construction of BRC: Gaussian kernel, double kernel, local mean and local constant, of which the last one generated the best-fitting curves. Conclusion: Clinical decision making should become easier and diagnostic implications of renal function tests should become more meaningful if this BRI is followed and the BRC is used as a desktop tool in conjunction with similar data for serum creatinine. The Communications and Publications Division (CPD) of the IFCC 2013-07-16 /pmc/articles/PMC4975168/ /pubmed/27683439 Text en Copyright © 2015 International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). All rights reserved. http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Sarkar, Rajarshi
Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models
title Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models
title_full Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models
title_fullStr Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models
title_full_unstemmed Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models
title_short Establishment of Biological Reference Intervals and Reference Curve for Urea by Exploratory Parametric and Non-Parametric Quantile Regression Models
title_sort establishment of biological reference intervals and reference curve for urea by exploratory parametric and non-parametric quantile regression models
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4975168/
https://www.ncbi.nlm.nih.gov/pubmed/27683439
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