Retrospective data analysis for definition of multidrug resistance in gram-negative bacteria - a consensus proposal.

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.