An improved algorithm to screen for carbapenemase production in Pseudomonas aeruginosa
Year: 2025
Type: article
Abstract: Objectives One of the biggest challenges for healthcare providers is the difficulty with screening for carbapenemase-producing, carbapenem-resistant Pseudomonas aeruginosa (CP-CRPa; P. aeruginosa), given the variety of mechanisms that can mediate carbapenem resistance in P. aeruginosa. We sought to develop an improved algorithm to screen for carbapenemase activity in P. aeruginosa using routine antimicrobial susceptibility testing readily available in most clinical microbiology laboratories. Methods Antibiograms of a reference set of P. aeruginosa (n = 100) with diverse phenotypic and genotypic profiles were compared to determine which antibiotics optimally screen for and differentiate CP-CRPa from CRPa and non-CRPa. The developed algorithm was then applied to 1482 clinical P. aeruginosa isolates. Carbapenemase PCR and the modified carbapenem inactivation method were performed on all meropenem-resistant P. aeruginosa isolates. Results The CP-CRPa screening algorithm developed here uses meropenem, ceftazidime and tobramycin. Carbapenem resistance was identified in 85 (5.7%) isolates, of which 26 (1.8%) were confirmed as CP-CRPa. blaGES (57.7%) was the predominant carbapenemase detected, whilst blaNDM, blaVIM, blaIMP and blaKPC carbapenemases were also detected. The CP-CRPa screening algorithm was 100% sensitive (CI95% 84.0%–100%) and 96.6% specific (CI95% 87.3%–99.4%). Conclusions We present an antimicrobial susceptibility testing-based screening algorithm that uses meropenem, ceftazidime, and tobramycin to screen for CP-CRPa. When appropriate screening criteria are utilized, confirmatory testing can be significantly reduced, resulting in substantial time and resource savings, without compromising sensitivity, particularly in settings with varying carbapenemase epidemiology.
Source: JAC-Antimicrobial Resistance
Institutions: Charles Sturt University, Westmead Hospital, NSW Health Pathology
Language: English
Subfield: Molecular Medicine
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,609
Funder: NSW Health Pathology
OpenAlex ID: W7119159973
