Antimicrobial Resistance | CMAC

Antimicrobial Resistance

Knowledge architecture in antimicrobial therapy: from cluster stratification to correlation map

Objective. To conduct an in-depth analysis of the competence structure in rational antimicrobial therapy (AMT) among healthcare professionals and students to identify typical knowledge profiles and determine priorities for Antimicrobial Stewardship (AMS) educational programs. Materials and Methods. The study employed a two-stage statistical analysis of survey data. The first stage used the k-means clustering method to stratify respondents based on their knowledge structure. The second stage involved a correlation analysis of responses to assess the internal connectivity («architecture») of key knowledge domains and identify integrative nodes.

Population pharmacokinetic/pharmacodynamic modeling of linezolid in critically ill adult patients

Objective. To evaluate pharmacokinetics using therapeutic drug monitoring (TDM) data and develop a population pharmacokinetic/pharmacodynamic (PK/PD) model of linezolid for individualizing dosage regimens in critically ill adult patients in intensive care unit (ICU). Materials and Methods. A retrospective study of linezolid pharmacokinetics was conducted using TDM data (peak-trough strategy) and included data (n = 23) from patients treated in the ICU and receiving the standard linezolid dosing regimen of 600 mg intravenously twice daily.

Comparative analysis of antimicrobial susceptibility testing results and applied interpretive standards in Russian Federation medical organizations

Objective. To assess the categorization of antimicrobial susceptibility testing results using aggregated data from microbiology laboratories in the Russian Federation for 2023 and 2024, considering interpretation standards, their versions, microorganisms, and federal districts. Materials and Methods. A retrospective descriptive study of aggregated microbiology laboratory data for 2023 and 2024 was performed. Data from 494 laboratories in 2023 and 520 laboratories in 2024 were included. We assessed the use and recency of interpretation standards, the proportion of errors/inaccuracies among tested results, and their distribution by type, microorganism, federal district, and standard recency group.

Genetic mechanisms of in vitro-induced flucytosine resistance in Candidozyma auris

Objective. To develop an in vitro model for the development of Candidozyma auris resistance to flucytosine (5-FC) and characterize its associated mutational profile. Materials and Methods. An adaptive laboratory evolution study was performed on seven clinical C. auris isolates of the South Asian clade obtained from independent epidemiological foci in Russian hospitals. Isolates underwent stepwise selection with increasing 5-FC concentrations, with molecular verification at defined checkpoints. Minimum inhibitory concentrations (MICs) were determined by broth microdilution (EUCAST).

Risk factors and prediction models for the presence of bacterial pathogens with clinically significant antimicrobial resistance phenotypes: a systematic review

Objective. To systematically synthesize factors associated with the presence, colonization, infection, or acquisition of bacterial pathogens with clinically significant antimicrobial resistance phenotypes; to assess the variability of available quantitative estimates of these associations; and, separately, to characterize prediction models, clinical scores, and algorithms developed to estimate the probability of such outcomes. Materials and Methods. A systematic review was conducted of publications identified through a PubMed/MEDLINE search covering the period from January 1, 2000, to April 30, 2026, using terms related to risk factors and prediction, antimicrobial resistance, and clinical infectious syndromes.

Contribution of antimicrobial use surveillance to the prevention of resistance selection

The spread of drug-resistant pathogens, especially multidrug resistant ones, dictates a reassessment of approaches to antimicrobials’ use in the Russian healthcare system. Antimicrobial pharmacotherapy surveillance providing healthcare specialists …

Machine learning methods in predicting antimicrobial resistance

Antimicrobial resistance poses a significant global threat to healthcare systems worldwide. The high cost and short lifespan of new antibiotics due to the rapid evolution of resistance exacerbate this crisis, prompting exploration of diverse …

Genetic determinants of antibiotic resistance in Staphylococcus aureus isolated from patients with chronic lung infection in cystic fibrosis

Objective. To investigate antibiotic resistance of S. aureus isolates from cystic fibrosis (CF) patients with chronic lung infection and to identify its genetic determinants. Materials and Methods. The antibiotic susceptibility of 629 S. aureus isolates from pediatric and adult CF patients was analyzed using the disk diffusion method and E-test in accordance with EUCAST guidelines. All strains were screened by PCR for the presence of the mecA and mecC genes.

Population structure of Pseudomonas aeruginosa in the Russian Federation: role of high-risk clones in spread of carbapenemases and carbapenem resistance

Objective. To determine the population structure of clinical P. aeruginosa isolates recovered from hospitals in different regions of Russia and to assess the role of high-risk clones in the dissemination of carbapenemases and carbapenem resistance. Materials and Methods. The study included consecutive, non-duplicate clinical isolates of P. aeruginosa (N = 1379) obtained from 55 hospitals across 30 Russian cities over a 24-month period. Species identification was performed using MALDI-TOF mass-spectrometry.

Experience in creating a closed digital loop for continuous antimicrobial resistance surveillance based on validated microbiological test results

Objective. To implement a closed digital loop for continuous antimicrobial resistance (AMR) surveillance based on validated microbiological diagnostic results. Materials and Methods. A prospective study was conducted at the Federal State Autonomous Institution «National Medical Research Center for Treatment and Rehabilitation» of the Ministry of Health of the Russian Federation from May 2024 to September 2025. An audit of the initial state of processes, a SWOT analysis, software restructuring, data flow optimization and standardization of diagnostic methods in accordance with EUCAST recommendations were performed.