Standardization of Operator-Dependent Variables Affecting Precision and Accuracy of the Disk Diffusion Method for Antibiotic Susceptibility Testing

Parameters like zone reading, inoculum density, and plate streaking influence the precision and accuracy of disk diffusion antibiotic susceptibility testing (AST). While improved reading precision has been demonstrated using automated imaging systems, standardization of the inoculum and of plate streaking have not been systematically investigated yet. This study analyzed whether photometrically controlled inoculum preparation and/or automated inoculation could further improve the standardization of disk diffusion. Suspensions of Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 29213 of 0.5 McFarland standard were prepared by 10 operators using both visual comparison to turbidity standards and a Densichek photometer (bioMérieux), and the resulting CFU counts were determined. Furthermore, eight experienced operators each inoculated 10 Mueller-Hinton agar plates using a single 0.5 McFarland standard bacterial suspension of E. coli ATCC 25922 using regular cotton swabs, dry flocked swabs (Copan, Brescia, Italy), or an automated streaking device (BD-Kiestra, Drachten, Netherlands). The mean CFU counts obtained from 0.5 McFarland standard E. coli ATCC 25922 suspensions were significantly different for suspensions prepared by eye and by Densichek (P < 0.001). Preparation by eye resulted in counts that were closer to the CLSI/EUCAST target of 10(8) CFU/ml than those resulting from Densichek preparation. No significant differences in the standard deviations of the CFU counts were observed. The interoperator differences in standard deviations when dry flocked swabs were used decreased significantly compared to the differences when regular cotton swabs were used, whereas the mean of the standard deviations of all operators together was not significantly altered. In contrast, automated streaking significantly reduced both interoperator differences, i.e., the individual standard deviations, compared to the standard deviations for the manual method, and the mean of the standard deviations of all operators together, i.e., total methodological variation.