ArticleJournal of family medicine and primary care2026
A comparative study of sigma metrics and statistical quality control rules in clinical biochemistry laboratories using a Cobas pure analyzer.
Article in Journal of family medicine and primary care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Longitudinal Sigma-Metric Profiling of Two Clinical Chemistry Platforms Using Peer-Group Internal Quality Control.Diagnostics (Basel, Switzerland) · 2026Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: The aim of this study was to use the Six Sigma metrics to assess the analytical quality of automated clinical chemistry tests in Dubai Health centers. Clinical laboratories face ongoing challenges to maintaining analytical quality, but it is difficult to measure the quality of assays objectively and quantitatively. The study assessed the quality of each analyte of general chemistry for bias, coefficient of variation (CV), sigma metrics based on the total allowable error and the applicability of Westgard rules. Material and Methods: Sigma metrics are an important quality planning tool for assessing total allowable error, bias, and imprecision. In this study, sigma metrics were calculated for 28 clinical chemistry analytes performed on a Roche Cobas pure analyzer. Two levels of quality control, normal and abnormal, were run daily. The coefficient of variation was calculated over a period from January to December 2024. Bias was assessed based on the laboratory results of College of American Pathologists (CAP) proficiency testing cycles and peer group comparison. Sigma metrics were calculated based on Clinical Laboratory Improvement Amendments (CLIA) total allowable error and minimum biological variation. The normalized operational specification chart assessed the applicability of the Westgard rules for the analytes. Results: The sigma metrics were calculated through tabulation of the two levels of internal quality controls, imprecision (CV%) and inaccuracy. The quality control rules were implemented based on the normalized operating points from the operational specifications chart. Conclusions: Sigma metrics application of quality control planning tools supported the detection of false rejection and true error detection in our medical laboratories.
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