Comparison of Antibiotic Susceptibility Patterns in Carbapenem Resistant Gram-Negative Bacteria by Disc Diffusion and Automated Testing Methods.

Abstract

Background: Rapid and accurate identification of carbapenem resistance is a need, to reduce the burden of emergence and spread of carbapenem resistant Gram-negative bacteria (CR-GNB).

Objective: To compare the carbapenem susceptibility results by Clinical Laboratory Standard Institute disk diffusion method (DDM) and Minimum Inhibitory Concentration (MIC) by BD PheonixTM automated system (PAS)

Method: A descriptive cross-sectional study was conducted from January to December 2023 in University Hospital Kotelawala Defence University and Apeksha hospital to identify CR-GNB from urine specimens received to microbiology laboratories, by both DDM and PAS. Organisms were identified by biochemical tests and PAS while antibiotic susceptibility testing was performed by DDM and PAS. Inter-rater agreement, Very Major Errors (VME), Major Errors (ME) and Minor Errors (MiE) for imipenem and meropenem were calculated. Descriptive statistics were analyzed by SPSS version 25.0.

Results: A total of 100 urinary CR-GNB were included. Organisms were identified up to the genus level by biochemical tests where Coliforms were the commonest genus while, PAS identified Klebsilla pneumoniae as the commonest species. AST results of meropenem and imipenem were reported for all isolates in DDM while PAS reported for 96 isolates as the taxonomy data of four organisms were not available. The PAS and DDM results showed a good inter-rater agreement for both imipenem (p=0.00, k=0.70) and meropenem (p=0.00. k=0.70). Though, VME rate of meropenem (0.00%) was acceptable, imipenem was beyond the acceptable level (2.08%). No ME were reported in both carbapenems while, MiE were equal (2.08%).

Conclusion: Findings emaphazise the compatibility of PAS and DDM in detecting CR. Although, vigilance is necessary for VME rate of imipenem. Further analysis should be performed to identify specific factors like unclear assessment criteria and differing interpretations. However, species identification by automated system will be helpful in early identification of outbreaks.