Aim of the study: The main objective of this study was to propose a common definition of multidrug-resistant gram-negative organisms (GN-MDRO), which may be used for epidemiological surveillance and benchmarking.

Methods: In this retrospective data analysis, we used interpreted qualitative susceptibility data (SIR) from blood culture isolates of different gram-negative microorganisms from the ANRESIS database from 2017-2021. We first analysed testing algorithms used by different Swiss laboratories and investigated cross-resistance patterns within antibiotic groups. Comparing these data with existing international definitions, we developed two different GN-MDRO definitions, an extended one for surveillance purposes (ANRESIS-extended) and a more stringent one for clinical purposes, aimed primarily at the identification of difficult-to-treat GN-MDRO (ANRESIS-restricted). Using these novel algorithms, the rates of invasive GN-MDRO identified in our national dataset were compared with international and national definitions: the European Centre for Disease Prevention and Control (ECDC) definition, the Commission for Hospital Hygiene and Infection (KRINKO) definition and the definition proposed by the University Hospital Zurich.

Results: SIR data of a total of 41,785 Enterobacterales, 2,919 , and 419 spp. isolates were used for the analyses. Five antibiotic categories were used for our MDRO definition: aminoglycosides, piperacillin-tazobactam, third- and fourth-generation cephalosporins, carbapenems and fluoroquinolones. Large differences were found between the testing algorithms of the different laboratories. Cross-resistance analysis within an antibiotic group revealed that the substance most likely to be effective against a particular gram-negative bacterium was not preferentially tested (e.g. amikacin for the aminoglycosides). For all bacterial species tested, the highest rates of multidrug-resistant isolates were found using the ECDC-MDR definition, followed by the ANRESIS-extended definition. The number of MDR-Enterobacterales identified using the ANRESIS-restricted definition (n = 627) was comparable to those identified using the KRINKO (n = 622) and UHZ definitions (n = 437). However, the isolates classified as MDR-Enterobacterales according to the KRINKO, UHZ and ANRESIS-restricted definitions (total n = 870) differed considerably. Only 242 of the isolates (27.8%) were uniformly classified as MDRO according to the KRINKO, UHZ and ANRESIS-restricted definitions. Comparable findings were made for Klebsiella spp. and Pseudomonas aeruginosa.

Conclusions: The application of different MDRO definitions leads to significant differences in not only MDRO rates but also the isolates that are eventually classified as MDRO. Therefore, defining a nationwide MDRO algorithm is crucial if data are compared between hospitals. The definition of a minimal antibiotic susceptibility testing panel would improve comparability further.