Application of a six sigma model to evaluate the analytical performance of urinary biochemical analytes and design a risk-based statistical quality control strategy for these assays: A multicenter study.

BACKGROUND: The six sigma model has been widely used in clinical laboratory quality management. In this study, we first applied the six sigma model to (a) evaluate the analytical performance of urinary biochemical analytes across five laboratories, (b) design risk-based statistical quality control (SQC) strategies, and (c) formulate improvement measures for each of the analytes when needed. METHODS: Internal quality control (IQC) and external quality assessment (EQA) data for urinary biochemical analytes were collected from five laboratories, and the sigma value of each analyte was calculated based on coefficients of variation, bias, and total allowable error (TEa). Normalized sigma method decision charts for these urinary biochemical analytes were then generated. Risk-based SQC strategies and improvement measures were formulated for each laboratory according to the flowchart of Westgard sigma rules, including run sizes and the quality goal index (QGI). RESULTS: Sigma values of urinary biochemical analytes were significantly different at different quality control levels. Although identical detection platforms with matching reagents were used, differences in these analytes were also observed between laboratories. Risk-based SQC strategies for urinary biochemical analytes were formulated based on the flowchart of Westgard sigma rules, including run size and analytical performance. Appropriate improvement measures were implemented for urinary biochemical analytes with analytical performance lower than six sigma according to the QGI calculation. CONCLUSIONS: In multilocation laboratory systems, a six sigma model is an excellent quality management tool and can quantitatively evaluate analytical performance and guide risk-based SQC strategy development and improvement measure implementation.

Application of a six sigma model to the evaluation of the analytical performance of serum enzyme assays and the design of a quality control strategy for these assays: A multicentre study.

BACKGROUND: Six medical testing laboratories at six different sites in China participated in this study. We applied a six sigma model for (a) the evaluation of the analytical performance of serum enzyme assays at each of the laboratories, (b) the design of individualized quality control programs and (c) the development of improvement measures for each of the assays, as appropriate. METHODS: Internal quality control (IQC) and external quality assessment (EQA) data for selected serum enzyme assays were collected from each of the laboratories. Sigma values for these assays were calculated using coefficients of variation, bias, and total allowable error (TEa). Normalized sigma method decision charts were generated using these parameters. IQC design and improvement measures were defined using the Westgard sigma rules. The quality goal index (QGI) was used to assist with identification of deficiencies (bias problems, precision problems, or their combination) affecting the analytical performance of assays with sigma values <6. RESULTS: Sigma values for the selected serum enzyme assays were significantly different at different levels of enzyme activity. Differences in assay quality in different laboratories were also seen, despite the use of identical testing instruments and reagents. Based on the six sigma data, individualized quality control programs were outlined for each assay with sigma <6 at each laboratory. CONCLUSIONS: In multi-location laboratory systems, a six sigma model can evaluate the quality of the assays being performed, allowing management to design individualized IQC programs and strategies for continuous improvement as appropriate for each laboratory. This will improve patient care, especially for patients transferred between sites within multi-hospital systems.

Overproduction, Purification and Characterization of Adenylate Deaminase from Aspergillus oryzae.

Adenylate deaminase (AMPD, EC 3.5.4.6) is an aminohydrolase that widely used in the food and medicine industries. In this study, the gene encoding Aspergillus oryzae AMPD was cloned and expressed in Escherichia coli. Induction with 0.75 mM isopropyl ß-D-l-thiogalactopyranoside resulted in an enzyme activity of 1773.9 U/mL. Recombinant AMPD was purified to electrophoretic homogeneity using nickel affinity chromatography, and its molecular weight was calculated as 78.6 kDa. Purified AMPD exhibited maximal activity at 35 °C, pH 6.0 and 30 mM K+, with apparent K m and V max values of 2.7 × 10-4 M and 77.5 µmol/mg/min under these conditions. HPLC revealed that recombinant AMPD could effectively catalyse the synthesis of inosine-5'-monophosphate (IMP) with minimal by-products, indicating high specificity and suggesting that it could prove useful for IMP production.

Organocatalyzed enantioselective Michael additions of nitroalkanes to enones by using primary-secondary diamine catalysts.

Primary-secondary diamines perform as efficient organocatalysts for the asymmetric addition of nitroalkanes to enones, giving the Michael adducts with excellent yields and enantioselectivities.