Importance of Susceptibility Rate of 'the First' Isolate: Evidence of Real-World Data

Effect of different strategies for excluding duplicate cultures on the correlation between hospital resistance rates and antibiotic consumption

INTRODUCTION

Studies may underestimate the impact of antibiotics on bacterial resistance when correlating hospital antibiotic use with resistance rates (RRs) that exclude duplicate cultures as duplicates usually include more resistant isolates. Comparing correlations between antibiotic consumption and RRs resulting from different strategies for excluding duplicates could help explore how their exclusion affects such correlations.

METHODS

We obtained antibiotics consumption and Pseudomonas aeruginosa susceptibility data from 2017 to 2021 for seven antibiotics and for carbapenems as a group in a university hospital. We calculated RRs using seven different time criteria for excluding duplicates. We assessed the correlations of antibiotic consumption to the same-year and next-year RR rates for the three most distinct rates.

RESULTS

Duplicate cultures represented 53.45% of total cultures. RRs were higher when duplicates were included. We compared RRs resulting from excluding all duplicates, excluding duplicates monthly or admitting one culture per day. All antibiotics except meropenem showed a correlation with same-year RRs, either positive or negative, whereas all antibiotics showed a positive correlation with next-year RRs. For same-year and next-year correlations, the criteria with fewer duplicates (and therefore fewer resistant strains) found more correlations. However, the inclusion of duplicates taken at least 1 month apart found the most correlations. Admitting one culture per day found the fewest correlations.

CONCLUSIONS

Excluding duplicates from RRs affects the correlation of antibiotics consumption with RRs in P. aeruginosa. Including at least some duplicate cultures in correlation analyses, such as those taken 1 month apart, should be considered.

Analysis of Cumulative Antibiogram Reports in Search for Optimal Empirical Urinary Tract Infection Treatment at the Central Teaching Hospital of the Medical University of Lodz, Poland: Results of a 3-Year Surveillance

Urinary tract infections are among the most common bacterial infections, accounting for about two-fifths of all healthcare-associated infections. Appropriate antimicrobial therapy is crucial, e.g., to avoid prolonged hospitalization and limit antimicrobial resistance spread. This study was performed to analyze the microbiological profiles of urinary tract infections in the Central Teaching Hospital in Lodz, Poland, and develop local empirical therapy guidelines. This study was a 3-year retrospective surveillance of the cumulative antibiograms from urine cultures. The procedures were based on the current EUCAST and CLSI guidelines. In 2020-2022, a total of 4656 urine cultures were performed, of which 1134 were positive. The most common bacterial isolates were Escherichia coli, followed by Klebsiella spp. and Enterococcus spp. High levels of susceptibility (>90%) have been observed for carbapenems, piperacillin/tazobactam, amikacin, and nitrofurantoin. Development of the appropriate empirical antimicrobial is a challenging task with persistently high levels of resistance to commonly used antimicrobials. Eventually, we separated the uncomplicated and complicated urinary tract infections in local guidelines and recommended nitrofurantoin and amikacin, respectively, in empiric therapy. The clinicians should make a decision based on the presented symptoms and then-with the urine culture result-correct or continue the therapy.

Combining Genome Surveillance and Metadata To Characterize the Diversity of Staphylococcus aureus Circulating in an Italian Hospital over a 9-Year Period

Staphylococcus aureus is an opportunistic pathogen and a leading cause of morbidity and mortality worldwide. Genomic-based surveillance has greatly improved our ability to track the emergence and spread of high-risk clones, but the full potential of genomic data is only reached when used in conjunction with detailed metadata. Here, we demonstrate the utility of an integrated approach by leveraging a curated collection of clinical and epidemiological metadata of S. aureus in the San Matteo Hospital (Italy) through a semisupervised clustering strategy. We sequenced 226 sepsis S. aureus samples, recovered over a period of 9 years. By using existing antibiotic profiling data, we selected strains that capture the full diversity of the population. Genome analysis revealed 49 sequence types, 16 of which are novel. Comparative genomic analyses of hospital- and community-acquired infection ruled out the existence of genomic features differentiating them, while evolutionary analyses of genes and traits of interest highlighted different dynamics of acquisition and loss between antibiotic resistance and virulence genes. Finally, highly resistant clones belonging to clonal complexes (CC) 8 and 22 were found to be responsible for abundant infections and deaths, while the highly virulent CC30 was responsible for rare but deadly episodes of infections. IMPORTANCE Genome sequencing is an important tool in clinical microbiology, as it allows in-depth characterization of isolates of interest and can propel genome-based surveillance studies. Such studies can benefit from ad hoc methods of sample selection to capture the genomic diversity present in a data set. Here, we present an approach based on clustering of antibiotic resistance profiles that allows optimal sample selection for bacterial genomic surveillance. We apply the method to a 9-year collection of Staphylococcus aureus from a large hospital in northern Italy. Our method allows us to sequence the genomes of a large variety of strains of this important pathogen, which we then leverage to characterize the epidemiology in the hospital and to perform evolutionary analyses on genes and traits of interest. These analyses highlight different dynamics of acquisition and loss between antibiotic resistance and virulence genes.

Better antimicrobial resistance data analysis and reporting in less time

Objectives

Insights about local antimicrobial resistance (AMR) levels and epidemiology are essential to guide decision-making processes in antimicrobial use. However, dedicated tools for reliable and reproducible AMR data analysis and reporting are often lacking. We aimed to compare traditional data analysis and reporting versus a new approach for reliable and reproducible AMR data analysis in a clinical setting.

Methods

Ten professionals who routinely work with AMR data were provided with blood culture test results including antimicrobial susceptibility results. Participants were asked to perform a detailed AMR data analysis in a two-round process: first using their software of choice and next using our newly developed software tool. Accuracy of the results and time spent were compared between both rounds. Finally, participants rated the usability using the System Usability Scale (SUS).

Results

The mean time spent on creating the AMR report reduced from 93.7 to 22.4 min (P < 0.001). Average task completion per round changed from 56% to 96% (P < 0.05). The proportion of correct answers in the available results increased from 37.9% in the first to 97.9% in the second round (P < 0.001). Usability of the new tools was rated with a median of 83.8 (out of 100) on the SUS.

Conclusions

This study demonstrated the significant improvement in efficiency and accuracy in standard AMR data analysis and reporting workflows through open-source software. Integrating these tools in clinical settings can democratize the access to fast and reliable insights about local microbial epidemiology and associated AMR levels. Thereby, our approach can support evidence-based decision-making processes in the use of antimicrobials.

Recovery of antimicrobial susceptibility in methicillin-resistant Staphylococcus aureus (MRSA): a retrospective, epidemiological analysis in a secondary care hospital, Sapporo, Japan

Anti-methicillin-resistant Staphylococcus aureus (MRSA) drugs are critical final options for treating MRSA infection. This study investigated the percentage of all S. aureus isolates that are resistant to methicillin and also MRSA susceptibility to other antimicrobial agents in the JR Sapporo Hospital inpatient service. The inpatient service MRSA percentages for Japan, Hokkaido, and JR Sapporo Hospital from 2010-2019 were compared, exploring the annual rate of change in the MRSA percentage. We also investigated the antimicrobial use density (AUD) and its relationship with MRSA antimicrobial susceptibility in the JR Sapporo Hospital during 2019. The MRSA percentage in JR Sapporo Hospital was 61.5% (95% CI [52.6-69.7]) in 2010 but was only 51.6% (95% CI [41.6-61.5]) in 2019, which is a 1.43% (95% CI [0.42-2.43]) annual decrease (p = 0.05). Regarding the MRSA antimicrobial susceptibility rate in JR Sapporo Hospital, the highest rates of annual increase were seen for minocycline (3.11% (95% CI [2.25-3.94])) followed by fosfomycin (2.85% (95% CI [1.83-3.85])). Positive correlations with the AUD of anti-MRSA drugs were identified for susceptibility to erythromycin (p < 0.01), clindamycin (p = 0.002), and levofloxacin (p = 0.0005). A recovery of MRSA antimicrobial susceptibility was observed in our antibiogram dataset. Our study supports the potential for appropriate antimicrobial agent use in reviving MRSA antimicrobial susceptibility.