Nosocomial acquisition of Pseudomonas aeruginosa resistant to both ciprofloxacin and imipenem: a risk factor and laboratory analysis

Antimicrobial Resistance and Mortality in Carbapenem-Resistant Pseudomonas aeruginosa Infections in Southern Thailand

Background/Objectives: Carbapenem-resistant Pseudomonas aeruginosa (CRPA) is an important pathogen associated with high mortality and treatment failure rates. We aimed to assess the susceptibility of CRPA to antipseudomonal agents, identify its resistance mechanisms, and evaluate clinical outcomes in a sample of CRPA isolates. Methods: This was an in vitro study of a clinical isolate of CRPA from hospitalized patients with CRPA infection and a retrospective observational study of these patients, who were diagnosed between 14 February 2021 and 10 August 2023 at Songklanagarind Hospital in Songkhla, Thailand. In vitro experiments were conducted to determine the minimum inhibitory concentrations (MICs) of the antipseudomonal agents using the broth microdilution method. Resistance mechanisms were assessed using the modified carbapenem inactivation method, combined disk tests, and quantitative real-time reverse transcription polymerase chain reaction. Results: A total of 140 CRPA isolates were analyzed. Both traditional and novel β-lactams had high MICs. The most common resistance mechanism was the upregulation of the MexAB-OprM efflux pump (81.3%), followed by the downregulation of the OprD porin (48.9%) and metallo-β-lactamase (MBL) production (45.0%), and the overexpression of blaAmpC (41.0%). The 30-day all-cause mortality rate was 30.5%. The risk factors associated with 30-day mortality included a Charlson Comorbidity Index of ≥5 (OR: 3.43; 95% CI: 1.07-10.99; p = 0.03), sepsis (OR: 10.62; 95% CI: 1.26-89.44; p = 0.03), and septic shock (OR: 4.39; 95% CI: 1.67-11.55; p < 0.01). In contrast, receiving active documented therapy was significantly associated with reduced mortality (OR: 0.17; 95% CI: 0.04-0.74; p = 0.01). Conclusions: This study revealed higher MIC values of all β-lactams for CRPA, while colistin and amikacin remained effective. The resistance mechanisms included MexAB-OprM overexpression, OprD downregulation, MBL production, and blaAmpC overexpression, with a higher prevalence of MBL than in other regions of Thailand. High 30-day mortality was associated with comorbidities, sepsis, and septic shock, but active therapy reduced mortality.

Antibiotic resistance in Pseudomonas aeruginosa: mechanisms and emerging treatment

Pseudomonas aeruginosa, able to survive on the surfaces of medical devices, is a life-threatening pathogen that mainly leads to nosocomial infection especially in immunodeficient and cystic fibrosis (CF) patients. The antibiotic resistance in P. aeruginosa has become a world-concerning problem, which results in reduced and ineffective therapy efficacy. Besides intrinsic properties to decrease the intracellular content and activity of antibiotics, P. aeruginosa develops acquired resistance by gene mutation and acquisition, as well as adaptive resistance under specific situations. With in-depth research on drug resistance mechanisms and the development of biotechnology, innovative strategies have emerged and yielded benefits such as screening for new antibiotics based on artificial intelligence technology, utilizing drugs synergistically, optimizing administration, and developing biological therapy. This review summarizes the recent advances in the mechanisms of antibiotic resistance and emerging treatments for combating resistance, aiming to provide a reference for the development of therapy against drug-resistant P. aeruginosa.

Diagnostic Accuracy of Hospital Antibiograms in Predicting the Risk of Antimicrobial Resistance in Enterobacteriaceae Isolates: A Nationwide Multicenter Evaluation at the Veterans Health Administration

BACKGROUND

Many clinical guidelines recommend that clinicians use antibiograms to inform empiric antimicrobial therapy. However, hospital antibiograms are typically generated by crude aggregation of microbiologic data, and little is known about an antibiogram's reliability in predicting antimicrobial resistance (AMR) risk at the patient-level. We aimed to assess the diagnostic accuracy of antibiograms as a tool for selecting empiric therapy for Escherichia coli and Klebsiella spp. for individual patients.

METHODS

We retrospectively generated hospital antibiograms for the nationwide Veterans Health Administration (VHA) facilities from 2000 to 2019 using all clinical culture specimens positive for E. coli and Klebsiella spp., then assessed the diagnostic accuracy of an antibiogram to predict resistance for isolates in the following calendar year using logistic regression models and predefined 5-step interpretation thresholds.

RESULTS

Among 127 VHA facilities, 1 484 038 isolates from 704 779 patients for E. coli and 671 035 isolates from 340 504 patients for Klebsiella spp. were available for analysis. For E. coli and Klebsiella spp., the discrimination abilities of hospital-level antibiograms in predicting individual patient AMR were mostly poor, with the areas under the receiver operating curve at 0.686 and 0.715 for ceftriaxone, 0.637 and 0.675 for fluoroquinolones, and 0.576 and 0.624 for trimethoprim-sulfamethoxazole, respectively. The sensitivity and specificity of the antibiogram varied widely by antimicrobial groups and interpretation thresholds with substantial trade-offs.

CONCLUSIONS

Conventional hospital antibiograms for E. coli and Klebsiella spp. have limited performance in predicting AMR for individual patients, and their utility in guiding empiric therapy may be low.

Evaluation of Risk Factors for Antibiotic Resistance in Patients with Nosocomial Infections Caused by Pseudomonas aeruginosa

Background. Pseudomonas aeruginosa (P. aeruginosa) is resistant to various antibiotics and can cause serious nosocomial infections with high morbidity and mortality. In this clinical study, we investigated the risk factors in patients who were diagnosed with P. aeruginosa-related nosocomial infection. Methods. A retrospective case control study including patients with P. aeruginosa-related nosocomial infection. Patients who were resistant to any of the six antibiotics (imipenem, meropenem, piperacillin-tazobactam, ciprofloxacin, amikacin, and ceftazidime) constituted the study group. Results. One hundred and twenty isolates were isolated. Various risk factors were detected for each antibiotic in the univariate analysis. In the multivariate analysis, previous cefazolin use was found as an independent risk factor for the development of imipenem resistance (OR = 3.33; CI 95% [1.11–10.0]; p = 0.03), whereas previous cerebrovascular attack (OR = 3.57; CI 95% [1.31–9.76]; p = 0.01) and previous meropenem use (OR = 4.13; CI 95% [1.21–14.07]; p = 0.02) were independent factors for the development of meropenem resistance. For the development of resistance to ciprofloxacin, hospitalization in the neurology intensive care unit (OR = 4.24; CI 95% [1.5–11.98]; p = 0.006) and mechanical ventilator application (OR = 11.7; CI 95% [2.24–61.45]; p = 0.004) were independent risk factors. Conclusion. The meticulous application of contact measures can decrease the rate of nosocomial infections.

A systematic review and meta-analyses show that carbapenem use and medical devices are the leading risk factors for carbapenem-resistant Pseudomonas aeruginosa

A systematic review and meta-analyses were performed to identify the risk factors associated with carbapenem-resistant Pseudomonas aeruginosa and to identify sources and reservoirs for the pathogen. A systematic search of PubMed and Embase databases from 1 January 1987 until 27 January 2012 identified 1,662 articles, 53 of which were included in a systematic review and 38 in a random-effects meta-analysis study. The use of carbapenem, use of fluoroquinolones, use of vancomycin, use of other antibiotics, having medical devices, intensive care unit (ICU) admission, having underlying diseases, patient characteristics, and length of hospital stay were significant risk factors in multivariate analyses. The meta-analyses showed that carbapenem use (odds ratio [OR] = 7.09; 95% confidence interval [CI] = 5.43 to 9.25) and medical devices (OR = 5.11; 95% CI = 3.55 to 7.37) generated the highest pooled estimates. Cumulative meta-analyses showed that the pooled estimate of carbapenem use was stable and that the pooled estimate of the risk factor "having medical devices" increased with time. We conclude that our results highlight the importance of antibiotic stewardship and the thoughtful use of medical devices in helping prevent outbreaks of carbapenem-resistant P. aeruginosa.

Epidemiological interpretation of studies examining the effect of antibiotic usage on resistance

Bacterial resistance to antibiotics is a growing clinical problem and public health threat. Antibiotic use is a known risk factor for the emergence of antibiotic resistance, but demonstrating the causal link between antibiotic use and resistance is challenging. This review describes different study designs for assessing the association between antibiotic use and resistance and discusses strengths and limitations of each. Approaches to measuring antibiotic use and antibiotic resistance are presented. Important methodological issues such as confounding, establishing temporality, and control group selection are examined.

Fluoroquinolone use is not associated with the change in imipenem susceptibility of Pseudomonas aeruginosa in 25 hospitals

INTRODUCTION

Evidence suggests use of fluoroquinolones is associated with carbapenem resistance in Pseudomonas aeruginosa, and fluoroquinolone use has been identified as a risk factor for clinical acquisition of imipenem-resistant P. aeruginosa in single-center studies. Imipenem susceptibility and fluoroquinolone use was evaluated within 25 hospitals over 9 years.

METHODS

Use density ratios (UDR) for fluoroquinolones: ciprofloxacin, gatifloxacin, levofloxacin, and moxifloxacin, and for three other antibiotic classes (carbapenems: ertapenem, doripenem, imipenem, and meropenem; other antipseudomonal beta-lactams: cefepime, ceftazidime, and piperacillin/tazobactam; and aminoglycosides: gentamicin and tobramycin) were derived from drug purchase data for up to 9 years, ending in 2008. Susceptibility data were obtained from hospital antibiograms in corresponding years. A mixed model repeated measures ANOVA (Analysis of Variance) explored associations between 9-year repeated imipenem susceptibility and fluoroquinolone UDR in each year while controlling for other drug classes, teaching status, and number of beds.

RESULTS

All sites had 7 years of data; n=22 had 8 years; n=18 had 9 years. Teaching hospitals were 36% of the cohort; median number of beds was 714 for teaching hospitals and 381 for nonteaching hospitals. Fluoroquinolone use declined from year (Y) 1-5; such use then rose over Y6-9, which was heavily influenced by ciprofloxacin/moxifloxacin: mean fluoroquinolone UDR from Y1-9 was: 303.8, 186.5, 156.8, 174.4, 169.1, 275.0, 504.2, 477.0, and 423.3. Mean imipenem susceptibility was (Y1-9 %) 85.2, 82.8, 82.7, 82.2, 82.8, 82.4, 82.3, 81.7, and 80.6; this change across time was not significant (P=0.46). Change in 9-year imipenem susceptibility was not associated with fluoroquinolone UDR (P=0.17), nor with any other drug class (P>0.40 for each). Results were not different when considering only sites with top 25% fluoroquinolone UDR during Y7-9.

CONCLUSION

Single-center studies of fluoroquinolone use have reported changes in P. aeruginosa susceptibility to carbapenems. Our study finds no such association while controlling for other drug classes. As such, resistance development in individual patients versus institutions warrants further research.