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Sigma metrics application for validated and non‐validated detecting systems performance assessment

BACKGROUND: Sigma metrics provide an objective and quantitative methodology for analytical quality evaluation of clinical laboratory. This study investigated the testing performance of validated systems and non‐validated systems based on sigma metrics, and explored the major parameters affecting the...

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Autores principales: Xia, Yong, Li, Mingyang, Li, Bowen, Xue, Hao, Lin, Yu, Li, Jie, Ji, Ling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957966/
https://www.ncbi.nlm.nih.gov/pubmed/33314338
http://dx.doi.org/10.1002/jcla.23676
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author Xia, Yong
Li, Mingyang
Li, Bowen
Xue, Hao
Lin, Yu
Li, Jie
Ji, Ling
author_facet Xia, Yong
Li, Mingyang
Li, Bowen
Xue, Hao
Lin, Yu
Li, Jie
Ji, Ling
author_sort Xia, Yong
collection PubMed
description BACKGROUND: Sigma metrics provide an objective and quantitative methodology for analytical quality evaluation of clinical laboratory. This study investigated the testing performance of validated systems and non‐validated systems based on sigma metrics, and explored the major parameters affecting the system performance. METHODS: Sigma metrics were evaluated by six biochemistry assays based on Beckman and Mindray validated and non‐validated systems through crossing the reagents and analyzers. Imprecision and bias were assessed for all assays based on trueness programs organized by National Centre for Clinical Laboratory. Total error allowance obtained from the Chinese Ministry of Health Clinical Laboratory Centre Industry Standard (WS/T403‐2012). RESULTS: The imprecision for all systems meets the quality specifications except TP assay (2.19%) detected by Mindray non‐validated system, and the bias for four assays measured by non‐validated systems cannot fulfill the criterion, including lactate dehydrogenase (LDH), total protein (TP), triglycerides (TG), and glucose (GLU). Higher biases were detected in six assays at different levels among non‐validated and validated systems. Systems performed poorly or unacceptably for TP assay with sigma metrics lower than 3 except Mindray non‐validated system. The sigma metrics for other assays with four systems were greater than 3 except the LDH evaluated on Mindray non‐validated systems. CONCLUSION: Non‐validated systems may introduce performance uncertainty compared with validated systems based on sigma metrics evaluation, and lower bias was provided by validated systems. The performance of non‐validated systems should be evaluated thoroughly in the clinical laboratory before they were adopted for routine use.
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spelling pubmed-79579662021-03-19 Sigma metrics application for validated and non‐validated detecting systems performance assessment Xia, Yong Li, Mingyang Li, Bowen Xue, Hao Lin, Yu Li, Jie Ji, Ling J Clin Lab Anal Research Articles BACKGROUND: Sigma metrics provide an objective and quantitative methodology for analytical quality evaluation of clinical laboratory. This study investigated the testing performance of validated systems and non‐validated systems based on sigma metrics, and explored the major parameters affecting the system performance. METHODS: Sigma metrics were evaluated by six biochemistry assays based on Beckman and Mindray validated and non‐validated systems through crossing the reagents and analyzers. Imprecision and bias were assessed for all assays based on trueness programs organized by National Centre for Clinical Laboratory. Total error allowance obtained from the Chinese Ministry of Health Clinical Laboratory Centre Industry Standard (WS/T403‐2012). RESULTS: The imprecision for all systems meets the quality specifications except TP assay (2.19%) detected by Mindray non‐validated system, and the bias for four assays measured by non‐validated systems cannot fulfill the criterion, including lactate dehydrogenase (LDH), total protein (TP), triglycerides (TG), and glucose (GLU). Higher biases were detected in six assays at different levels among non‐validated and validated systems. Systems performed poorly or unacceptably for TP assay with sigma metrics lower than 3 except Mindray non‐validated system. The sigma metrics for other assays with four systems were greater than 3 except the LDH evaluated on Mindray non‐validated systems. CONCLUSION: Non‐validated systems may introduce performance uncertainty compared with validated systems based on sigma metrics evaluation, and lower bias was provided by validated systems. The performance of non‐validated systems should be evaluated thoroughly in the clinical laboratory before they were adopted for routine use. John Wiley and Sons Inc. 2020-12-13 /pmc/articles/PMC7957966/ /pubmed/33314338 http://dx.doi.org/10.1002/jcla.23676 Text en © 2020 The Authors. Journal of Clinical Laboratory Analysis published by Wiley Periodicals LLC This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Xia, Yong
Li, Mingyang
Li, Bowen
Xue, Hao
Lin, Yu
Li, Jie
Ji, Ling
Sigma metrics application for validated and non‐validated detecting systems performance assessment
title Sigma metrics application for validated and non‐validated detecting systems performance assessment
title_full Sigma metrics application for validated and non‐validated detecting systems performance assessment
title_fullStr Sigma metrics application for validated and non‐validated detecting systems performance assessment
title_full_unstemmed Sigma metrics application for validated and non‐validated detecting systems performance assessment
title_short Sigma metrics application for validated and non‐validated detecting systems performance assessment
title_sort sigma metrics application for validated and non‐validated detecting systems performance assessment
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7957966/
https://www.ncbi.nlm.nih.gov/pubmed/33314338
http://dx.doi.org/10.1002/jcla.23676
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