[Multidrug-resistant gram-negative rods in the intensive care unit : Epidemiology, prevention and treatment options]

Clinical Distribution and Drug Resistance of Pseudomonas aeruginosa in Guangzhou, China from 2017 to 2021

The aim of the current study was to analyse the distribution of antimicrobial drug resistance (AMR) among Pseudomonas aeruginosa (P. aeruginosa, PA) isolates from Guangdong Provincial People's Hospital (GDPH) from 2017 to 2021, and the impact of the COVID-19 outbreak on changes in the clinical distribution and drug resistance rate of P. aeruginosa to establish guidelines for empiric therapy. Electronic clinical data registry records from 2017 to 2021 were retrospectively analysed to study the AMR among P. aeruginosa strains from GDPH. The strains were identified by VITEK 2 Compact and MALDI-TOF MS, MIC method or Kirby-Bauer method for antibiotic susceptibility testing. The results were interpreted according to the CLSI 2020 standard, and the data were analysed using WHONET 5.6 and SPSS 23.0 software. A total of 3036 P. aeruginosa strains were detected in the hospital from 2017 to 2021, and they were primarily distributed in the ICU (n = 1207, 39.8%). The most frequent specimens were respiratory tract samples (59.6%). The detection rate for P. aeruginosa in 5 years was highest in September, and the population distribution was primarily male(68.2%). For the trend in the drug resistance rate, the 5-year drug resistance rate of imipenem (22.4%), aztreonam (21.5%) and meropenem (19.3%) remained at high levels. The resistance rate of cefepime decreased from 9.4% to 4.8%, showing a decreasing trend year by year (p < 0.001). The antibiotics with low resistance rates were aminoglycoside antibiotics, which were gentamicin (4.4%), tobramycin (4.3%), and amikacin (1.4%), but amikacin showed an increasing trend year by year (p = 0.008). Our analysis indicated that the detection rate of clinically resistant P. aeruginosa strains showed an upwards trend, and the number of multidrug-resistant (MDR) strains increased year by year, which will lead to stronger pathogenicity and mortality. However, after the outbreak of COVID-19 in 2020, the growth trend in the number of MDR bacteria slowed, presumably due to the strict epidemic prevention and control measures in China. This observation suggests that we should reasonably use antibiotics and treatment programs in the prevention and control of P. aeruginosa infection. Additionally, health prevention and control after the outbreak of the COVID-19 epidemic (such as wearing masks, washing hands with disinfectant, etc., which reduced the prevalence of drug resistance) led to a slowdown in the growth of the drug resistance rate of P. aeruginosa in hospitals, effectively reducing the occurrence and development of drug resistance, and saving patient's treatment costs and time.

Bacterial Community and Genomic Analysis of Carbapenem-Resistant Acinetobacter baumannii Isolates from the Environment of a Health Care Facility in the Western Region of Saudi Arabia

The escalating transmission of hospital-acquired infections, especially those due to antimicrobial-resistant bacteria, is a major health challenge worldwide. In this study, a culturomic analysis of bacterial community in a tertiary care hospital in the western region of Saudi Arabia is performed using environmental samples. The genome sequencing of four Acinetobacter baumannii was performed on isolates recovered from an intensive care unit (ICU) environment and clinical samples. A total of 361 bacterial isolates from surface and air samples were identified by MALDI-TOF technique or 16S rRNA gene sequencing. The isolates were classified into 70 distinct species, including ESKAPE pathogens. Resistance in Gram-positive isolates was mainly found to be against benzylpenicillin, azithromycin, ampicillin, and trimethoprim/sulfamethoxazole. Carbapenem- and multidrug-resistant isolates of A. baumannii and Klebsiella pneumonia were found on the ICU surfaces. Genome sequencing revealed that the carbapenem-resistant A. baumannii isolate from ICU environment was linked with those of clinical origin. The isolate Ab133-HEnv was classified as a novel sequence type (ST2528) based on a new allele of Oxf_gdhB-286. Three beta-lactam-antibiotic-resistance genes, bla_ADC-25, bla_OXA-23, and bla_OXA-66, were found in most of the analyzed genomes. Collectively, the results of this study highlight the spread of antimicrobial-resistant nosocomial pathogens in a health care facility in Saudi Arabia.

[Screening for 4MRGN in German emergency departments]

BACKGROUND

Multiresistant Gram-negative bacteria (MRGN) are a growing clinical problem. The practical implementation of the recommendation of the Commission for Hospital Hygiene and Infection Prevention (KRINKO) for screening according to 4MRGN (MRGN resistant to all four categories of antibiotics), however, varies considerably between emergency departments.

OBJECTIVES

This study is intended to give an overview of the status quo and the quality assurance of 4MRGN screening and to show possibilities for process optimization.

MATERIALS AND METHODS

In 2018, a web-based survey was conducted among emergency room directors and directors of clinics in the Association of Hospital Directors in Germany (VKD).

RESULTS

The response rate of the 267 clinics surveyed was 31.1%. In all, 83.4% of the emergency rooms surveyed routinely screen for multiresistant pathogens. In 71.8% a standard procedure (SOP) is defined and 82.0% of the test criteria refer to the KRINKO recommendation. Only 39.7% of the clinics follow it without in-house adaptation. No clinic can give an exact number of actual risk patients per year. According to the median, 55 patients in an emergency room met the KRINKO screening criteria in 2017. Only 40 patients were screened for suspected 4MRGN. Quality assurance of the screening was performed by 41.0% of emergency departments. The responsibility lies mainly with the hygiene department.

CONCLUSIONS

Even if screenings are carried out as far as possible, there is a lack of standardization in the recording of case numbers and quality assurance. Therefore, it can be assumed that there are numerous individuals with undetected 4MRGN. As a quality indicator, SOPs could clearly assign responsibilities and improve infection hygiene.