Frontiers in Microbiology (May 2022)
Statistical Investigation of High Culture Contamination Rates in Mycobacteriology Laboratory
Abstract
BackgroundCulture of Mycobacterium tuberculosis remains the gold standard in mycobacteriology laboratories, constrained by the very high risk of contamination; therefore, contamination rate is an important key performance indicator (KPI) for laboratory monitoring and evaluation processes.AimThis study aimed to investigate the factors that contribute to elevated contamination rates in the Sudan National Tuberculosis Reference Laboratory.MethodA laboratory-based retrospective study was applied; a TB culture register-book was carefully reviewed and data from 2 January 2019 to 31 December 2019 were entered, cleaned, and analyzed using IBM SPSS 20. A multivariate logistic regression model was performed to examine two dependent variables, the massive contamination, and the single tube contamination against predictors of reason for cultivation, type of specimen, experiment team, and the quarter of cultivation.ResultsIt has been found that in 2019 contamination rates were frequently higher; the highest rates were recorded in January and November, 28.2 and 25.2%, respectively. August is an exception with an accepted contamination rate of 4.6%. Of 1,149 specimens requested for culture, 945 (82.2%) samples were eligible to be included in multivariate logistic regression analysis. The team conducting the experiment was significantly associated with a high single tube contamination p value 0.007; adjusted odds ratio AOR 3.570 (1.415–9.005). The correlation between the single tube contamination and the massive contamination is significant; p value 0.01.ConclusionThe study concludes that high culture contamination is the greatest risk to the quality of laboratory service and can end in either the loss of specimens or delay in the decisions of initiating patient treatment. In addition, the low quality or incompleteness of data increases the uncertainty and undermines the measurement of key performance indicators.
Keywords
