Does plasmid-based beta-lactam resistance increase E. coli infections: Modelling addition and replacement mechanisms

Infections caused by antibiotic-resistant bacteria have become more prevalent during past decades. Yet, it is unknown whether such infections occur in addition to infections with antibiotic-susceptible bacteria, thereby increasing the incidence of infections, or whether they replace such infections, leaving the total incidence unaffected. Observational longitudinal studies cannot separate both mechanisms. Using plasmid-based beta-lactam resistant E. coli as example we applied mathematical modelling to investigate whether seven biological mechanisms would lead to replacement or addition of infections. We use a mathematical neutral null model of individuals colonized with susceptible and/or resistant E. coli, with two mechanisms implying a fitness cost, i.e., increased clearance and decreased growth of resistant strains, and five mechanisms benefitting resistance, i.e., 1) increased virulence, 2) increased transmission, 3) decreased clearance of resistant strains, 4) increased rate of horizontal plasmid transfer, and 5) increased clearance of susceptible E. coli due to antibiotics. Each mechanism is modelled separately to estimate addition to or replacement of antibiotic-susceptible infections. Fitness costs cause resistant strains to die out if other strain characteristics are maintained equal. Under the assumptions tested, increased virulence is the only mechanism that increases the total number of infections. Other benefits of resistance lead to replacement of susceptible infections without changing the total number of infections. As there is no biological evidence that plasmid-based beta-lactam resistance increases virulence, these findings suggest that the burden of disease is determined by attributable effects of resistance rather than by an increase in the number of infections

Molecular Characterization and Clinical Relevance of Taxonomic Reassignment of Staphylococcus schleiferi Subspecies into Two Separate Species, Staphylococcus schleiferi and Staphylococcus coagulans.

Staphylococcus schleiferi is an opportunistic pathogen in humans and dogs. Recent taxonomic reassignment of its subspecies (S. schleiferi subsp. schleiferi and S. schleiferi subsp. coagulans) into two separate species (S. schleiferi and S. coagulans) lacks supporting data for diagnostic implications and clinical relevance. We aimed to confirm the reclassification of S. schleiferi by using genomic and matrix-Assisted laser desorption ionization-time of flight (MALDI-TOF) data for a large set of isolates from humans and animals to investigate their molecular epidemiology and clinical relevance. Routine MALDI-TOF analysis and Illumina sequencing were performed on 165 S. schleiferi isolates from the Netherlands. With 33 publicly available genomes, the study included 198 genomes from 149 dogs, 34 humans, and 15 other sources. The Type Strain Genome Server was used to identify species in the genomes, and the MALDI-TOF MS database was extended to improve species differentiation. MALDI-TOF did not discriminate between S. schleiferi and S. coagulans. Genome phylogeny distinguished the two species in two monophyletic clusters. S. schleiferi isolates originated from humans, while S. coagulans isolates were found in animals and three human isolates clustering with the animal isolates. The sialidase B gene (nanB) was a unique marker gene for S. schleiferi, whereas the chrA gene was exclusive for S. coagulans. The mecA gene was exclusively detected in S. coagulans, as were the lnu(A), blaZ, erm(B/C), tet(O/M), and aac(69)-Aph(299) genes. The MALDI-TOF database extension did not improve differentiation between the two species. Even though our whole-genome sequencing- based approach showed clear differentiation between these two species, it remains critical to identify S. schleiferi and S. coagulans correctly in routine diagnostics. IMPORTANCE This study clearly shows that S. schleiferi is a concern in human hospital settings, whereas S. coagulans predominantly causes infections in animals. S. coagulans is more resistant to antibiotics and can sometimes transmit to humans via exposure to infected dogs. Even though genome-based methods can clearly differentiate the two species, current diagnostic methods used routinely in clinical microbiology laboratories cannot distinguish the two bacterial species

Plasma cytokine profile on admission related to aetiology in Community Acquired Pneumonia

Background: Potentially unnecessary antibiotic use for community-acquired pneumonia (CAP) contributes to selection of antibiotic-resistant pathogens. Cytokine expression at the time that treatment is started may assist in identifying patients not requiring antibiotics. We determined plasma cytokine patterns in patients retrospectively categorized as strict viral, pneumococcal or combined viral-bacterial CAP. Objective: To investigate whether cytokine-based prediction models can be used to differentiate strict viral CAP from other aetiologies at admission. Methods: From 344 hospitalized CAP patients, 104 patients were categorized as viral CAP (n = 17), pneumococcal CAP (n = 48) and combined bacterial-viral CAP (n = 39). IL-6, IL-10, IL-27, IFN-γ and C-reactive protein (CRP) were determined on admission in plasma. Prediction of strict viral aetiology was explored with two multivariate regression models and ROC curves. Results: Viral pneumonia was predicted by logistic regression using multiple cytokine levels (IL-6, IL-27 and CRP) with an AUC of 0.911 (95% CI: 0.852-0.971, P <.001). For the same patients the AUC of CRP was 0.813 (95% CI: 0.728-0.898, P <.001). Conclusions: This study demonstrated differences in cytokine expression in selected CAP patients between viral and bacterial aetiology. Prospective validation studies are warranted

Plasma cytokine profile on admission related to aetiology in community-acquired pneumonia

Background: Potentially unnecessary antibiotic use for community-acquired pneumonia (CAP) contributes to selection of antibiotic-resistant pathogens. Cytokine expression at the time that treatment is started may assist in identifying patients not requiring antibiotics. We determined plasma cytokine patterns in patients retrospectively categorized as strict viral, pneumococcal or combined viral-bacterial CAP. Objective: To investigate whether cytokine-based prediction models can be used to differentiate strict viral CAP from other aetiologies at admission. Methods: From 344 hospitalized CAP patients, 104 patients were categorized as viral CAP (n = 17), pneumococcal CAP (n = 48) and combined bacterial-viral CAP (n = 39). IL-6, IL-10, IL-27, IFN-γ and C-reactive protein (CRP) were determined on admission in plasma. Prediction of strict viral aetiology was explored with two multivariate regression models and ROC curves. Results: Viral pneumonia was predicted by logistic regression using multiple cytokine levels (IL-6, IL-27 and CRP) with an AUC of 0.911 (95% CI: 0.852-0.971, P <.001). For the same patients the AUC of CRP was 0.813 (95% CI: 0.728-0.898, P <.001). Conclusions: This study demonstrated differences in cytokine expression in selected CAP patients between viral and bacterial aetiology. Prospective validation studies are warranted

Bruker matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identification of Neisseria gonorrhoeae is improved by a database extension

Bruker MALDI-TOF MS identification of Neisseria gonorrhoeae may be affected by "B consistency categorization". A supplementary database of 17 N. gonorrhoeae main spectra was constructed. 12/64 N. gonorrhoeae identifications were categorized with B consistency, which disappeared using the supplementary database. Database extension did not result in misidentification of Neisseria meningitidis

Bruker matrix-assisted laser desorption/ionization time-of-flight mass spectrometry identification of Neisseria gonorrhoeae is improved by a database extension

Bruker MALDI-TOF MS identification of Neisseria gonorrhoeae may be affected by "B consistency categorization". A supplementary database of 17 N. gonorrhoeae main spectra was constructed. 12/64 N. gonorrhoeae identifications were categorized with B consistency, which disappeared using the supplementary database. Database extension did not result in misidentification of Neisseria meningitidis

Response Adjusted for Days of Antibiotic Risk (RADAR) : evaluation of a novel method to compare strategies to optimise antibiotic use

OBJECTIVES: The Response Adjusted for Days of Antibiotic Risk (RADAR)-statistic was proposed to improve efficiency of trials comparing antibiotic stewardship strategies to optimize antibiotic use. We studied the behaviour of RADAR in a non-inferiority trial in which a beta-lactam monotherapy strategy (BL, n=656) was non-inferior to fluoroquinolone monotherapy (FQL, n=888) for moderately-severe community-acquired pneumonia (CAP) patients. METHODS: Patients were ranked according to clinical outcome, using five or eight categories, and antibiotic use. RADAR was calculated as the probability that the BL group had a more favourable ranking than the FQL group. To investigate the sensitivity of RADAR to detrimental clinical outcome we simulated increasing rates of 90-day mortality in the BL group and performed the RADAR and non-inferiority analysis. RESULTS: The RADAR of the BL-group compared to the FQL group was 60.3% (95% confidence interval 57.9%-62.7%) using five and 58.4% (95% CI 56.0%-60.9%) using eight clinical outcome categories, all in favour of BL. Sample sizes for RADAR were 38% (250/653) and 89% (580/653) of the non-inferiority sample size calculation, using five or eight clinical outcome categories respectively. With simulated mortality rates, loss of non-inferiority of the BL-group occurred at a relative risk of 1.125 in the conventional analysis, whereas using RADAR the BL-group lost superiority at a relative risk of mortality of 1.25 and 1.5, with eight and five clinical outcome categories, respectively. CONCLUSIONS: RADAR favoured BL over FQL therapy for CAP. Although RADAR required fewer patients than conventional non-inferiority analysis, the statistic was less sensitive to detrimental outcomes

Inappropriate Use of Antimicrobials for Lower Respiratory Tract Infections in Elderly Patients : Patient- and Community-Related Implications and Possible Interventions

The elderly are more susceptible to infections, which is reflected in the incidence and mortality of lower respiratory tract infections (LRTIs) increasing with age. Several aspects of antimicrobial use for LRTIs in elderly patients should be considered to determine appropriateness. We discuss possible differences in microbial etiology between elderly and younger adults, definitions of inappropriate antimicrobial use for LRTIs currently found in the literature, along with their results, and the possible negative impact of antimicrobial therapy at both an individual and community level. Finally, we propose that both antimicrobial stewardship interventions and novel rapid diagnostic techniques may optimize antimicrobial use in elderly patients with LRTIs

Response Adjusted for Days of Antibiotic Risk (RADAR) : evaluation of a novel method to compare strategies to optimise antibiotic use

OBJECTIVES: The Response Adjusted for Days of Antibiotic Risk (RADAR)-statistic was proposed to improve efficiency of trials comparing antibiotic stewardship strategies to optimize antibiotic use. We studied the behaviour of RADAR in a non-inferiority trial in which a beta-lactam monotherapy strategy (BL, n=656) was non-inferior to fluoroquinolone monotherapy (FQL, n=888) for moderately-severe community-acquired pneumonia (CAP) patients. METHODS: Patients were ranked according to clinical outcome, using five or eight categories, and antibiotic use. RADAR was calculated as the probability that the BL group had a more favourable ranking than the FQL group. To investigate the sensitivity of RADAR to detrimental clinical outcome we simulated increasing rates of 90-day mortality in the BL group and performed the RADAR and non-inferiority analysis. RESULTS: The RADAR of the BL-group compared to the FQL group was 60.3% (95% confidence interval 57.9%-62.7%) using five and 58.4% (95% CI 56.0%-60.9%) using eight clinical outcome categories, all in favour of BL. Sample sizes for RADAR were 38% (250/653) and 89% (580/653) of the non-inferiority sample size calculation, using five or eight clinical outcome categories respectively. With simulated mortality rates, loss of non-inferiority of the BL-group occurred at a relative risk of 1.125 in the conventional analysis, whereas using RADAR the BL-group lost superiority at a relative risk of mortality of 1.25 and 1.5, with eight and five clinical outcome categories, respectively. CONCLUSIONS: RADAR favoured BL over FQL therapy for CAP. Although RADAR required fewer patients than conventional non-inferiority analysis, the statistic was less sensitive to detrimental outcomes

Role and perception of clinical microbiology and infectious diseases trainees during the COVID-19 crisis

Aim: To evaluate the role and perceptions of trainees during the COVID-19 pandemic. Method: An online survey was designed to provide an insight into the significance of the COVID-19 pandemic on working conditions of infectious diseases and clinical microbiology trainees. Results: The main roles of trainees included management of patients hospitalized for COVID-19 (55%), research (53%) and diagnostic procedures (43%). The majority (82%) of trainees felt useful in managing the crisis. However, more than two-thirds felt more stressed and more tired compared with other rotations. Only 39% of the participants had access to psychological support. Conclusion: Due to the significant impact of the pandemic on infectious diseases and clinical microbiology trainees, further research should focus on their health and welfare in the post-pandemic period.PostprintPeer reviewe