The application of sigma metrics in the laboratory to assess quality control processes in South Africa

Objective: This study aimed to determine the sigma metrics of analytes when using different total allowable error guidelines.Methods: A retrospective analysis was performed on 19 general chemistry analytes at Charlotte Maxeke Johannesburg Academic Hospital in South Africa between January 2017 and December 2017. Sigma metrics were calculated on two identical analysers, using internal quality control data and total allowable error guidelines from the Ricos biological variation database and three alternative sources (the Royal College of Pathologists of Australasia, the Clinical Laboratory Improvements Amendment, and the European Federation of Clinical Chemistry and Laboratory Medicine). Results: The sigma performance was similar on both analysers but varied based on the guideline used, with the Clinical Laboratory Improvements Amendment guidelines resulting in the best sigma metrics (53% of analytes on one analyser and 46% on the other had acceptable sigma metrics) and the Royal College of Pathologists of Australia guidelines being the most stringent (21% and 23%). Sodium and chloride performed poorly across all guidelines (sigma < 3). There were also month-to-month variations that may result in acceptable sigma despite poor performance during certain months.Conclusion: The sigma varies greatly depending on the total allowable error, but could be a valuable tool to save time and decrease costs in high-volume laboratories. Sigma metrics calculations need to be standardised

Sentinel seroprevalence of SARS-CoV-2 in the Gauteng province, South Africa August to October 2020.

BackgroundEstimates of prevalence of anti-SARS-CoV-2 antibody positivity (seroprevalence) are for tracking the Covid-19 epidemic and are lacking for most African countries. ObjectivesTo determine the prevalence of antibodies against SARS-CoV2 in a sentinel cohort of patient samples received for routine testing at tertiary laboratories in Johannesburg, South Africa MethodsThis sentinel study was conducted using remnant serum samples received at three National Health Laboratory Services laboratories situated in the City of Johannesburg (COJ) district, South Africa. Collection was from 1 August until the 31 October 2020. We extracted accompanying laboratory results for haemoglobin A1c, creatinine, HIV, viral load, and CD4+ T cell count. An anti-SARS -CoV-2 targeting the nucleocapsid (N) protein of the coronavirus with higher affinity for IgM and IgG antibodies was used. We reported crude as well as population weighted and test adjusted seroprevalence. Multivariate logistic regression method was used to determine if age, sex, HIV and diabetic status were associated with increased risk for seropositivity. ResultsA total of 6477 samples were analysed; the majority (5290) from the COJ region. After excluding samples with no age or sex stated, the model population weighted and test adjusted seroprevalence for COJ (N=4393) was 27.0 % (95% CI: 25.4-28.6%). Seroprevalence was highest in those aged 45-49 [29.8% (95% CI: 25.5-35.0 %)] and in those from the most densely populated areas of COJ. Risk for seropositivity was highest in those aged 18-49 as well as samples from diabetics (aOR =1.52; 95% CI: 1.13-2.13; p=0.0005) and (aOR=1.36; 95% CI: 1.13-1.63; p=0.001) respectively. ConclusionOur study conducted during the first wave of the pandemic shows high levels of infection among patients attending public health facilities in Gauteng.