English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Background Laboratories use quality control (QC) testing to monitor the extent of normal variation. Assay lot number changes contribute the greatest amount of variation in infectious disease serology testing. An unexpected change in six lots of an anti-HCV assay allowed the determination of the effect these lot changes made to the assay's clinical sensitivity. Methods Two sets of seroconversion samples comprising of 44 individual samples and 9 external quality assessment scheme (EQAS) samples, all positive to anti-HCV, were tested in affected and unaffected assay lots, and the difference in the quantitative and qualitative results of the samples was analyzed. Results Of 44 low-positive seroconversion samples tested in affected and unaffected assay lots, only three samples had results reported below the assay cutoff when tested on two of the six affected assay lot. A further sample had results below the cutoff for only one affected lot. None of the EQAS samples reported false-negative results. Samples having a signal to cutoff value of less than 6.0 generally had lower results in the affected lots compared with the unaffected lots. Conclusions Unexpected changes in QC reactivity related to variation, in particular assay lot changes, may affect patient results. This study demonstrated that QConnect Limits facilitated the detection of an unexpectedly large variation in QC test results, allowed for the identification of the root cause of the change, and showed that the risk associated with the change was low but credible. The use of evidence-based QC program is essential to detect changes in test systems.

Does a change in quality control results influence the sensitivity of an anti-HCV test?