Optimizing drug exposure to minimize selection of antibiotic resistance

Appropriateness of Antibiotic Prescription Among Children Under 5 Years: A Cross-Sectional Study in a Ghanaian Regional Hospital

Background and Aim

Misuse of medications, particularly antibiotics, severely impacts the standard of care and can result in antibiotic resistance. Antibiotic resistance is a growing problem in Ghana, compromising patient outcomes. This study aims to assess antibiotic prescription pattern and level of inappropriateness based on Standard Treatment Guideline (STG) recommendations in children under 5 years.

Methods

An analytical cross-sectional study design was used to assess antibiotic prescription in children under 5 years attending the Wa Regional Hospital in Ghana. Medical records of pediatric outpatients from January to December 2022 were reviewed. Patients' sociodemographic characteristics, prescribed antibiotics, principal diagnosis, dose, and duration were extracted using a semi-structured form. Prescriptions with clinical indication, dose, and duration which did not meet the requirements of the STG were coded as inappropriate. Data were analyzed and factors associated with inappropriate antibiotic prescription were determined using logistic regression.

Results

Children's mean age was 2.95 ± 1.20 years, with males comprising 54.5%. Most patients had NHIS coverage (90.6%). This study reports 62.7% (266/424) inappropriate antibiotic prescriptions in children under 5 years with infections. The most common classes of antibiotics wrongly prescribed were cephalosporin 54.3% (230/424), penicillin 21.7% (92/424), and aminoglycoside 12.5% (53/424). The class of principal diagnoses likely to have inappropriate antibiotic prescriptions included respiratory tract infections (aOR = 3.82; 95% CI = 2.13, 6.85; p < 0.0001) and urinary tract infections (aOR = 0.21; 95% CI = 0.11, 0.41; p < 0.0001).

Conclusion

Prevalence of inappropriate prescription of antibiotics was high among the study population, and this was strongly associated with respiratory and urinary tract infections. This study highlights the need to monitor antibiotic prescriptions in hospitals to ensure treatment effectiveness and combat antimicrobial resistance.

Epigenetic modifications and metabolic gene mutations drive resistance evolution in response to stimulatory antibiotics

The antibiotic resistance crisis, fueled by misuse and bacterial evolution, is a major global health threat. Traditional perspectives tie resistance to drug target mechanisms, viewing antibiotics as mere growth inhibitors. New insights revealed that low-dose antibiotics may also serve as signals, unexpectedly promoting bacterial growth. Yet, the development of resistance under these conditions remains unknown. Our study investigated resistance evolution under stimulatory antibiotics and uncovered new genetic mechanisms of resistance linked to metabolic remodeling. We documented a shift from a fast, reversible mechanism driven by methylation in central metabolic pathways to a slower, stable mechanism involving mutations in key metabolic genes. Both mechanisms contribute to a metabolic profile transition from glycolysis to rapid gluconeogenesis. In addition, our findings demonstrated that rising environmental temperatures associated with metabolic evolution accelerated this process, increasing the prevalence of metabolic gene mutations, albeit with a trade-off in interspecific fitness. These findings expand beyond the conventional understanding of resistance mechanisms, proposing a broader metabolic mechanism within the selective window of stimulatory sub-MIC antibiotics, particularly in the context of climate change.

Insights into durability against resistance from the antibiotic nitrofurantoin

Nitrofurantoin has shown exceptional durability against resistance over 70 years of use. This longevity stems from factors such as rapid achievement of therapeutic concentrations, multiple physiological targets against bacteria, low risk of horizontal gene transfer, and the need to acquire multiple mutations to achieve resistance. These combined features limit resistance emergence and spread of nitrofurantoin resistance. We propose nitrofurantoin as an exemplar for developing other durable treatments.

Drugs Targeting Sirtuin 2 Exhibit Broad-Spectrum Anti-Infective Activity

Direct-acting anti-infective drugs target pathogen-coded gene products and are a highly successful therapeutic paradigm. However, they generally target a single pathogen or family of pathogens, and the targeted organisms can readily evolve resistance. Host-targeted agents can overcome these limitations. One family of host-targeted, anti-infective agents modulate human sirtuin 2 (SIRT2) enzyme activity. SIRT2 is one of seven human sirtuins, a family of NAD+-dependent protein deacylases. It is the only sirtuin that is found predominantly in the cytoplasm. Multiple, structurally distinct SIRT2-targeted, small molecules have been shown to inhibit the replication of both RNA and DNA viruses, as well as intracellular bacterial pathogens, in cell culture and in animal models of disease. Biochemical and X-ray structural studies indicate that most, and probably all, of these compounds act as allosteric modulators. These compounds appear to impact the replication cycles of intracellular pathogens at multiple levels to antagonize their replication and spread. Here, we review SIRT2 modulators reported to exhibit anti-infective activity, exploring their pharmacological action as anti-infectives and identifying questions in need of additional study as this family of anti-infective agents advances to the clinic.

Dynamics of drug delivery determines course of evolution of antibiotic responses in bacteria

To adjust to sudden shifts in conditions, microbes possess regulated genetic mechanisms that sense environmental challenges and induce the appropriate responses. The initial evolution of microbes in new environments is thought to be driven by regulatory mutations, but it is not clear how this evolution is affected by how quickly conditions change (i.e. dynamics). Here, we perform experimental evolution on continuous cultures of tetracycline resistant E. coli in different dynamical regimens of drug administration. We find that cultures evolved under gradually increasing drug concentrations acquire fine-tuning mutations adapting an alternative efflux pump to tetracycline. However, cultures that are instead periodically exposed to large drug doses evolve transposon insertions resulting in loss of regulation of the main mechanism of tetracycline resistance. A mathematical model shows that sudden drug exposures overwhelm regulated responses, which cannot induce resistance fast enough. These results help explain the frequent loss of regulation of resistance in clinical pathogens.

Cell morphology as biomarker of carbapenem exposure

Characterizing the physiological response of bacterial cells to antibiotics is crucial for designing diagnostic techniques, treatment choices, and drug development. While bacterial cells at sublethal doses of antibiotics are commonly characterized, the impact of exposure to high concentrations of antibiotics on bacteria after long-term serial exposure and their effect on withdrawal need attention for further characterization. This study investigated the effect of increasing imipenem concentrations on carbapenem-susceptible (S) and carbapenem-resistant (R) E. coli on their growth adaptation and cell surface structure. We exposed the bacterial population to increasing imipenem concentrations through 30 exposure cycles. Cell morphology was observed using a 3D laser scanning confocal microscope (LSCM) and transmission electron microscope (TEM). Results showed that the exposure resulted in significant morphological changes in E. coli (S) cells, while minor changes were seen in E. coli (R) cells. The rod-shaped E. coli (S) gradually transformed into round shapes. Further, the exposed E. coli (S) cells' surface area-to-volume ratio (SA/V) was also significantly different from the control, which is non-exposed E. coli (S). Then, the exposed E. coli (S) cells were re-grown in antibiotic-free environment for 100 growth cycles to determine if the changes in cells were reversible. The results showed that their cell morphology remained round, showing that the cell morphology was not reversible. The morphological response of these cells to imipenem can assist in understanding the resistance mechanism in the context of diagnostics and antibacterial therapies.

Pyrrole-based inhibitors of RND-type efflux pumps reverse antibiotic resistance and display anti-virulence potential

Efflux pumps of the resistance-nodulation-cell division (RND) superfamily, particularly the AcrAB-TolC, and MexAB-OprM, besides mediating intrinsic and acquired resistance, also intervene in bacterial pathogenicity. Inhibitors of such pumps could restore the activities of antibiotics and curb bacterial virulence. Here, we identify pyrrole-based compounds that boost antibiotic activity in Escherichia coli and Pseudomonas aeruginosa by inhibiting their archetype RND transporters. Molecular docking and biophysical studies revealed that the EPIs bind to AcrB. The identified efflux pump inhibitors (EPIs) inhibit the efflux of fluorescent probes, attenuate persister formation, extend post-antibiotic effect, and diminish resistant mutant development. The bacterial membranes remained intact upon exposure to the EPIs. EPIs also possess an anti-pathogenic potential and attenuate P. aeruginosa virulence in vivo. The intracellular invasion of E. coli and P. aeruginosa inside the macrophages was hampered upon treatment with the lead EPI. The excellent efficacy of the EPI-antibiotic combination was evidenced in animal lung infection and sepsis protection models. These findings indicate that EPIs discovered herein with negligible toxicity are potential antibiotic adjuvants to address life-threatening Gram-negative bacterial infections.

Predicting the unpredictable: the regulatory nature and promiscuity of herbicide cross resistance

The emergence of herbicide-resistant weeds is a significant threat to modern agriculture. Cross resistance, a phenomenon where resistance to one herbicide confers resistance to another, is a particular concern owing to its unpredictability. Nontarget-site (NTS) cross resistance is especially challenging to predict, as it arises from genes that encode enzymes that do not directly involve the herbicide target site and can affect multiple herbicides. Recent advancements in genomic and structural biology techniques could provide new venues for predicting NTS resistance in weed species. In this review, we present an overview of the latest approaches that could be used. We discuss the use of genomic and epigenomics techniques such as ATAC-seq and DAP-seq to identify transcription factors and cis-regulatory elements associated with resistance traits. Enzyme/protein structure prediction and docking analysis are discussed as an initial step for predicting herbicide binding affinities with key enzymes to identify candidates for subsequent in vitro validation. We also provide example analyses that can be deployed toward elucidating cross resistance and its regulatory patterns. Ultimately, our review provides important insights into the latest scientific advancements and potential directions for predicting and managing herbicide cross resistance in weeds. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Diverse mutant selection windows shape spatial heterogeneity in evolving populations

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes in both cancer and infectious diseases. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N * 2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more fully reflect the selection of drug resistant genotypes. Furthermore, using synthetic data and empirical dose-response data in cancer, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. By simulating a tumor treated with cyclic drug therapy, we find that mutant selection windows introduced by drug diffusion promote the proliferation of drug resistant cells. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

A Randomized Clinical Trial of Bayesian-Guided Beta-Lactam Infusion Strategy and Associated Bacterial Resistance and Clinical Outcomes in Patients With Severe Pneumonia

BACKGROUND

Antimicrobial resistance is a growing health concern worldwide. The objective of this study was to evaluate the effect of beta-lactam infusion on the emergence of bacterial resistance in patients with severe pneumonia in the intensive care unit.

METHODS

Adult intensive care patients receiving cefepime, meropenem, or piperacillin-tazobactam for severe pneumonia caused by Gram-negative bacteria were randomized to receive beta-lactams as an intermittent (30 minutes) or continuous (24 hours) infusion. Respiratory samples for culture and susceptibility testing, with minimum inhibitory concentrations (MIC), were collected once a week for up to 4 weeks. Beta-lactam plasma concentrations were measured and therapeutic drug monitoring was performed using Bayesian software as the standard of care.

RESULTS

The study was terminated early owing to slow enrollment. Thirty-five patients were enrolled in this study. Cefepime (n = 22) was the most commonly prescribed drug at randomization, followed by piperacillin (n = 8) and meropenem (n = 5). Nineteen patients were randomized into the continuous infusion arm and 16 into the intermittent infusion arm. Pseudomonas aeruginosa was the most common respiratory isolate (n = 19). Eighteen patients were included in the final analyses. No differences in bacterial resistance were observed between arms ( P = 0.67). No significant differences in superinfection ( P = 1), microbiological cure ( P = 0.85), clinical cure at day 7 ( P = 0.1), clinical cure at end of therapy ( P = 0.56), mortality ( P = 1), intensive care unit length of stay ( P = 0.37), or hospital length of stay ( P = 0.83) were observed. Achieving 100% ƒT > MIC ( P = 0.04) and ƒT > 4 × MIC ( P = 0.02) increased likelihood of clinical cure at day 7 of therapy.

CONCLUSIONS

No differences in the emergence of bacterial resistance or clinical outcomes were observed between intermittent and continuous infusions. Pharmacokinetic/pharmacodynamic target attainment may be associated with a clinical cure on day 7.

Fowl Typhoid Outbreak on a Commercial Turkey Farm in Croatia

Fowl typhoid is a septicemic disease caused by Salmonella enterica subsp. enterica serovar Gallinarum biovar Gallinarum. It is a host-specific disease primarily affecting chickens and turkeys, although it has been reported in various animal species and sporadically in humans. Here, we present a case of a fowl typhoid outbreak on a turkey poult farm where the source of infection was the hatchery. The birds started showing symptoms of growth retardation at 21 days of age, after which the mortality rates gradually started to increase. Post mortem examination revealed that the main lesions were granulomatous proliferations in the small intestines. The results of the histopathological examination indicate that the severity of the infection was alleviated by the application of phytogenic mixtures and probiotics as a supportive treatment, even though the affected flock was eventually culled at 60 days of age. The farmer was advised to apply more strict biosecurity measures to prevent the spread of the disease on the farm and try to eradicate the pathogen from the barn. Since the outbreak, there have been no recurrent infections.

Antimicrobial Multidrug Resistance: Clinical Implications for Infection Management in Critically Ill Patients

The increasing incidence of antimicrobial resistance (AMR) worldwide represents a serious threat in the management of sepsis. Due to resistance to the most common antimicrobials prescribed, multidrug-resistant (MDR) pathogens have been associated with delays in adequate antimicrobial therapy leading to significant increases in mortality, along with prolonged hospital length of stay (LOS) and increases in healthcare costs. In response to MDR infections and the delay of microbiological results, broad-spectrum antibiotics are frequently used in empirical antimicrobial therapy. This can contribute to the overuse and misuse of antibiotics, further promoting the development of resistance. Multiple measures have been suggested to combat AMR. This review will focus on describing the epidemiology and trends concerning MDR pathogens. Additionally, it will explore the crucial aspects of identifying patients susceptible to MDR infections and optimizing antimicrobial drug dosing, which are both pivotal considerations in the fight against AMR. Expert commentary: The increasing AMR in ICUs worldwide makes the empirical antibiotic therapy challenging in septic patients. An AMR surveillance program together with improvements in MDR identification based on patient risk stratification and molecular rapid diagnostic tools may further help tailoring antimicrobial therapies and avoid unnecessary broad-spectrum antibiotics. Continuous infusions of antibiotics, therapeutic drug monitoring (TDM)-based dosing regimens and combination therapy may contribute to optimizing antimicrobial therapy and limiting the emergence of resistance.

In vivo Pharmacokinetic/Pharmacodynamic Analysis of the Efficacy of the Cefepime/Nacubactam Combination Against β-Lactamase-Producing Enterobacterales based on the Instantaneous MIC Concept

PURPOSE

Nacubactam (NAC) is a novel diazabicyclooctane β-lactamase inhibitor used in combination with cefepime (CFPM). In this study, we aimed to determine the target pharmacokinetics (PK) and pharmacodynamics (PD) values of CFPM/NAC in mice infected with β-lactamase-producing Enterobacterales, such as the carbapenemase-producing Enterobacterales.

METHODS

Three strains of β-lactamase-producing Enterobacterales, Klebsiella pneumoniae MSC 21444, Escherichia coli MSC 20662, and K. pneumoniae ATCC BAA-1898, were used for checkerboard assays and fractionation studies and dose-range studies. A PK study was performed in neutropenic mice. Additionally, PK/PD analysis was performed based on the instantaneous minimum inhibitory concentration (MICi) concept.

RESULTS

Checkerboard measurements revealed that higher NAC concentrations decreased the CFPM MIC in a concentration-dependent manner. In all tested strains, fT > MICi calculated from the PK experiments showed a high correlation with the mean change in the bacterial count of thigh-infected mice in the in vivo PD study, suggesting that fT > MICi is an optimal PK/PD parameter for monitoring the CFPM/NAC combination. The target fT > MICi values for CFPM/NAC to achieve a bacteriostatic effect, 1-log10-kill, and 2-log10-kill values were 30, 49, and 94%, respectively.

CONCLUSIONS

Our results indicate that fT > MICi is a PK/PD parameter is suitable for monitoring the CFPM/NAC combination. The minimum target value for achieving a static effect against β-lactamase-producing Enterobacterales is 30%.

Diverse mutant selection windows shape spatial heterogeneity in evolving populations

Mutant selection windows (MSWs), the range of drug concentrations that select for drug-resistant mutants, have long been used as a model for predicting drug resistance and designing optimal dosing strategies in infectious disease. The canonical MSW model offers comparisons between two subtypes at a time: drug-sensitive and drug-resistant. In contrast, the fitness landscape model with N alleles, which maps genotype to fitness, allows comparisons between N genotypes simultaneously, but does not encode continuous drug response data. In clinical settings, there may be a wide range of drug concentrations selecting for a variety of genotypes. Therefore, there is a need for a more robust model of the pathogen response to therapy to predict resistance and design new therapeutic approaches. Fitness seascapes, which model genotype-by-environment interactions, permit multiple MSW comparisons simultaneously by encoding genotype-specific dose-response data. By comparing dose-response curves, one can visualize the range of drug concentrations where one genotype is selected over another. In this work, we show how N-allele fitness seascapes allow for N*2N-1 unique MSW comparisons. In spatial drug diffusion models, we demonstrate how fitness seascapes reveal spatially heterogeneous MSWs, extending the MSW model to more accurately reflect the selection fo drug resistant genotypes. Furthermore, we find that the spatial structure of MSWs shapes the evolution of drug resistance in an agent-based model. Our work highlights the importance and utility of considering dose-dependent fitness seascapes in evolutionary medicine.

Social demographics determinants for resistome and microbiome variation of a multiethnic community in Southern Malaysia

The prevalence of antibiotic-resistant bacteria in Southeast Asia is a significant concern, yet there is limited research on the gut resistome and its correlation with lifestyle and environmental factors in the region. This study aimed to profile the gut resistome of 200 individuals in Malaysia using shotgun metagenomic sequencing and investigate its association with questionnaire data comprising demographic and lifestyle variables. A total of 1038 antibiotic resistance genes from 26 classes were detected with a mean carriage rate of 1.74 ± 1.18 gene copies per cell per person. Correlation analysis identified 14 environmental factors, including hygiene habits, health parameters, and intestinal colonization, that were significantly associated with the resistome (adjusted multivariate PERMANOVA, p < 0.05). Notably, individuals with positive yeast cultures exhibited a reduced copy number of 15 antibiotic resistance genes. Network analysis highlighted Escherichia coli as a major resistome network hub, with a positive correlation to 36 antibiotic-resistance genes. Our findings suggest that E. coli may play a pivotal role in shaping the resistome dynamics in Segamat, Malaysia, and its abundance is strongly associated with the community's health and lifestyle habits. Furthermore, the presence of yeast appears to be associated with the suppression of antibiotic-resistance genes.

Quantifying stochastic establishment of mutants in microbial adaptation

Studies of microbial evolution, especially in applied contexts, have focused on the role of selection in shaping predictable, adaptive responses to the environment. However, chance events - the appearance of novel genetic variants and their establishment, i.e. outgrowth from a single cell to a sizeable population - also play critical initiating roles in adaptation. Stochasticity in establishment has received little attention in microbiology, potentially due to lack of awareness as well as practical challenges in quantification. However, methods for high-replicate culturing, mutant labelling and detection, and statistical inference now make it feasible to experimentally quantify the establishment probability of specific adaptive genotypes. I review methods that have emerged over the past decade, including experimental design and mathematical formulas to estimate establishment probability from data. Quantifying establishment in further biological settings and comparing empirical estimates to theoretical predictions represent exciting future directions. More broadly, recognition that adaptive genotypes may be stochastically lost while rare is significant both for interpreting common lab assays and for designing interventions to promote or inhibit microbial evolution.

A stochastic analysis of the interplay between antibiotic dose, mode of action, and bacterial competition in the evolution of antibiotic resistance

The use of an antibiotic may lead to the emergence and spread of bacterial strains resistant to this antibiotic. Experimental and theoretical studies have investigated the drug dose that minimizes the risk of resistance evolution over the course of treatment of an individual, showing that the optimal dose will either be the highest or the lowest drug concentration possible to administer; however, no analytical results exist that help decide between these two extremes. To address this gap, we develop a stochastic mathematical model of bacterial dynamics under antibiotic treatment. We explore various scenarios of density regulation (bacterial density affects cell birth or death rates), and antibiotic modes of action (biostatic or biocidal). We derive analytical results for the survival probability of the resistant subpopulation until the end of treatment, the size of the resistant subpopulation at the end of treatment, the carriage time of the resistant subpopulation until it is replaced by a sensitive one after treatment, and we verify these results with stochastic simulations. We find that the scenario of density regulation and the drug mode of action are important determinants of the survival of a resistant subpopulation. Resistant cells survive best when bacterial competition reduces cell birth and under biocidal antibiotics. Compared to an analogous deterministic model, the population size reached by the resistant type is larger and carriage time is slightly reduced by stochastic loss of resistant cells. Moreover, we obtain an analytical prediction of the antibiotic concentration that maximizes the survival of resistant cells, which may help to decide which drug dosage (not) to administer. Our results are amenable to experimental tests and help link the within and between host scales in epidemiological models.

Therapeutic drug monitoring of carbapenem antibiotics in critically ill patients: an overview of principles, recommended dosing regimens, and clinical outcomes

INTRODUCTION

The importance of antibiotic treatment for sepsis in critically ill septic patients is well established. Consistently achieving the dose of antibiotics required to optimally kill bacteria, minimize the development of resistance, and avoid toxicity is challenging. The increasing understanding of the pharmacokinetic and pharmacodynamic (PK/PD) characteristics of antibiotics, and the effects of critical illness on key PK/PD parameters, is gradually re-shaping how antibiotics are dosed in critically ill patients.

AREAS COVERED

The PK/PD characteristics of commonly used carbapenem antibiotics, the principles of the application of therapeutic drug monitoring (TDM), and current as well as future methods of utilizing TDM to optimally devise dosing regimens will be reviewed. The limitations and evidence-base supporting the use of carbapenem TDM to improve outcomes in critically ill patients will be examined.

EXPERT OPINION

It is important to understand the principles of TDM in order to correctly inform dosing regimens. Although the concept of TDM is attractive, and the ability to utilize PK software to optimize dosing in the near future is expected to rapidly increase clinicians' ability to meet pre-defined PK/PD targets more accurately, current evidence provides only limited support for the use of TDM to guide carbapenem dosing in critically ill patients.

The pharmacokinetic-pharmacodynamic modelling framework as a tool to predict drug resistance evolution

Pharmacokinetic-pharmacodynamic (PKPD) models, which describe how drug concentrations change over time and how that affects pathogen growth, have proven highly valuable in designing optimal drug treatments aimed at bacterial eradication. However, the fast rise of antimicrobial resistance calls for increased focus on an additional treatment optimization criterion: avoidance of resistance evolution. We demonstrate here how coupling PKPD and population genetics models can be used to determine treatment regimens that minimize the potential for antimicrobial resistance evolution. Importantly, the resulting modelling framework enables the assessment of resistance evolution in response to dynamic selection pressures, including changes in antimicrobial concentration and the emergence of adaptive phenotypes. Using antibiotics and antimicrobial peptides as an example, we discuss the empirical evidence and intuition behind individual model parameters. We further suggest several extensions of this framework that allow a more comprehensive and realistic prediction of bacterial escape from antimicrobials through various phenotypic and genetic mechanisms.

Onset timing and duration of augmented renal clearance in a mixed intensive care unit

BACKGROUND

Augmented renal clearance (ARC) is associated with lower blood plasma concentrations of renally excreted drugs; however, its time course is unknown. The current study aimed to determine the onset timing/duration of ARC, its risk factors, and its association with clinical outcomes by continuous monitoring of urinary creatinine clearance (CrCl) in critically ill patients.

METHODS

Data were retrospectively obtained from the medical records of 2592 critically ill patients admitted to the intensive care unit (ICU) from January 2019 to June 2022 at a tertiary emergency hospital. Among these, patients with continuously measured urinary CrCl were selected and observed over time. We evaluated the onset timing and duration of ARC by plotting Kaplan-Meier curves. Furthermore, by multivariate analyses, factors associated with the onset and persistence of ARC were analyzed, and the association between the ARC time course and clinical outcomes was evaluated.

RESULTS

The prevalence of ARC was 33.4% (245/734). ARC onset was within 3 days of admission in approximately half of the cases, and within 1 week in most of the other cases. In contrast, the persistence duration of ARC varied widely (median, 5 days), and lasted for more than a month in some cases. Multivariate analysis identified younger age, male sex, lower serum creatinine at admission, admission with central nervous system disease, no medical history, use of mechanically assisted ventilation, and vasopressor use as onset factors for ARC. Furthermore, factors associated with ARC persistence such as younger age and higher urinary CrCl on ARC day 1 were detected. The onset of ARC was significantly associated with reduced mortality, but persistent of ARC was significantly associated with fewer ICU-free days.

CONCLUSIONS

Despite the early onset of ARC, its duration varied widely and ARC persisted longer in younger patients with higher urinary CrCl. Since the duration of ARC was associated with fewer ICU-free days, it may be necessary to consider a long-term increased-dose regimen of renally excreted drugs beginning early in patients who are predicted to have a persistent ARC.

Optimizing antibiotic dosing regimens for nosocomial pneumonia: a window of opportunity for pharmacokinetic and pharmacodynamic modeling

INTRODUCTION

Determining antibiotic exposure in the lung and the threshold(s) needed for effective antibacterial killing is paramount during development of new antibiotics for the treatment of nosocomial pneumonia, as these exposures directly affect clinical outcomes and resistance development. The use of pharmacokinetic and pharmacodynamic modeling is recommended by regulatory agencies to evaluate antibiotic pulmonary exposure and optimize dosage regimen selection. This process has been implemented in newer antibiotic development.

AREAS COVERED

This review will discuss the basis for conducting pharmacokinetic and pharmacodynamic studies to support dosage regimen selection and optimization for the treatment of nosocomial pneumonia. Pharmacokinetic/pharmacodynamic data that supported recent hospital-acquired bacterial pneumonia/ventilator-associated bacterial pneumonia indications for ceftolozane/tazobactam, ceftazidime/avibactam, imipenem/cilastatin/relebactam, and cefiderocol will be reviewed.

EXPERT OPINION

Optimal drug development requires the integration of preclinical pharmacodynamic studies, healthy volunteers and ideally patient bronchoalveolar lavage pharmacokinetic studies, Monte-Carlo simulation, and clinical trials. Currently, plasma exposure has been successfully used as a surrogate for lung exposure threshold. Future studies are needed to identify the value of lung pharmacodynamic thresholds in nosocomial pneumonia antibiotic dosage optimization.

Use of pharmacokinetic/pharmacodynamic approaches for dose optimization: a case study of plazomicin

With limited treatment options available for multidrug-resistant bacteria, dose optimization is critical for achieving effective drug concentrations at the site of infection. Yet, selecting an appropriate dose and appropriate time to administer the dose with dosing frequency requires extensive understanding of the interplay between drug pharmacokinetics/pharmacodynamics (PK/PD), the host immune system, and bacterial-resistant mechanisms. Model-informed dose optimization (MIDO) uses PK/PD models (e.g. population PK, mechanism-based models, etc.) that incorporate preclinical and clinical data to simulate/predict performance of treatment regimens in appropriate patient populations and/or infection types that may not be well-represented in clinical trials. Here, we highlight the stages of a MIDO approach for designing optimized regimens by reviewing current clinical, preclinical, and PK/PD modeling data available for plazomicin. Plazomicin is an aminoglycoside approved in 2018 for the treatment of complicated urinary tract infections in adults. Applying knowledge gained by PK/PD modeling can guide therapeutic drug monitoring to ensure that drug exposure is appropriate for clinical efficacy while limiting drug-related toxicity.

Pharmacokinetics, Pharmacodynamics, and Dosing Considerations of Novel β-Lactams and β-Lactam/β-Lactamase Inhibitors in Critically Ill Adult Patients: Focus on Obesity, Augmented Renal Clearance, Renal Replacement Therapies, and Extracorporeal Membrane Oxygenation

OBJECTIVE

Dose optimization of novel β-lactam antibiotics (NBLA) has become necessary given the increased prevalence of multidrug-resistant infections in intensive care units coupled with the limited number of available treatment options. Unfortunately, recommended dose regimens of NBLA based on PK/PD indices are not well-defined for critically ill patients presenting with special situations (i.e., obesity, extracorporeal membrane oxygenation (ECMO), augmented renal clearance (ARC), and renal replacement therapies (RRT)). This review aimed to discuss and summarize the available literature on the PK/PD attained indices of NBLA among critically ill patients with special circumstances.

DATA SOURCES

PubMed, MEDLINE, Scopus, Google Scholar, and Embase databases were searched for studies published between January 2011 and May 2022.

STUDY SELECTION AND DATA EXTRACTION

Articles relevant to NBLA (i.e., ceftolozane/tazobactam, ceftazidime/avibactam, cefiderocol, ceftobiprole, imipenem/relebactam, and meropenem/vaborbactam) were selected. The MeSH terms of "obesity", "augmented renal clearance", "renal replacement therapy", "extracorporeal membrane oxygenation", "pharmacokinetic", "pharmacodynamic" "critically ill", and "intensive care" were used for identification of articles. The search was limited to adult humans' studies that were published in English. A narrative synthesis of included studies was then conducted accordingly.

DATA SYNTHESIS

Available evidence surrounding the use of NBLA among critically ill patients presenting with special situations was limited by the small sample size of the included studies coupled with high heterogeneity. The PK/PD target attainments of NBLA were reported to be minimally affected by obesity and/or ECMO, whereas the effect of renal functionality (in the form of either ARC or RRT) was more substantial.

CONCLUSION

Critically ill patients presenting with special circumstances might be at risk of altered NBLA pharmacokinetics, particularly in the settings of ARC and RRT. More robust, well-designed trials are still required to define effective dose regimens able to attain therapeutic PK/PD indices of NBLA when utilized in those special scenarios, and thus aid in improving the patients' outcomes.

Can breeders prevent pathogen adaptation when selecting for increased resistance to infectious diseases?

Background

Recent research shows that genetic selection has high potential to reduce the prevalence of infectious diseases in livestock. However, like all interventions that target infectious diseases, genetic selection of livestock can exert selection pressure on pathogen populations. Such selection on the pathogen may lead to escape strategies and reduce the effect of selection of livestock for disease resistance. Thus, to successfully breed livestock for lower disease prevalence, it is essential to develop strategies that prevent the invasion of pathogen mutants that escape host resistance. Here we investigate the conditions under which such “escape mutants” can replace wild-type pathogens in a closed livestock population using a mathematical model of disease transmission.

Results

Assuming a single gene that confers sufficient resistance, results show that genetic selection for resistance in livestock typically leads to an “invasion window” within which an escape mutant of the pathogen can invade. The bounds of the invasion window are determined by the frequency of resistant hosts in the population. The lower bound occurs when the escape mutant has an advantage over the wild-type pathogen in the population. The upper bound occurs when local eradication of the pathogen is expected. The invasion window is smallest when host resistance is strong and when infection with the wild-type pathogen provides cross immunity to infection with the escape mutant.

Conclusions

To minimise opportunities for pathogens to adapt, under the assumptions of our model, the aim of disease control through genetic selection should be to achieve herd-level eradication of the infection faster than the rate of emergence of escape mutants of the pathogen. Especially for microparasitic infections, this could be achieved by placing animals into herds according to their genetic resistance, such that these herds stay completely out of the invasion window. In contrast to classical breeding theory, our model suggests that multi-trait selection with gradual improvement of each trait of the breeding goal might not be the best strategy when resistance to infectious disease is part of the breeding goal. Temporally, combining genetic selection with other interventions helps to make the invasion window smaller, and thereby reduces the risk of invasion of escape mutants.

Antibiotic treatment duration in diverticulitis, complicated urinary tract infection and endocarditis: a retrospective, single center study

OBJECTIVES

Despite the availability of international guidelines advocating shorter treatment durations, non-adherence to them is common. We assessed duration of antibiotic treatment (DAT) in diverticulitis, complicated urinary tract infection (UTI) and endocarditis.

METHODS

Medical records of patients hospitalized with the above stated diseases in 2017 and 2018 were randomly selected at a Swiss tertiary care hospital. Appropriateness of antibiotic treatment duration was assessed according to international and local guidelines.

RESULTS

243 patients were included into the study: 100 with diverticulitis and complicated UTI each, and 43 patients with endocarditis. Adherence to local and international guidelines was 11% and 18% in diverticulitis, 39% and 40% in complicated UTI and 84% and 86% in endocarditis, respectively. Non-adherence was primarily due to prolonged treatment in diverticulitis and complicated UTI with a median DAT of 11 days (IQR 10-13) and 14 days (IQR 10-15), respectively. When pooling diverticulitis and complicated UTI cases, the identification of a pathogen in any microbiological sample was associated with an improved adherence to local guidelines in addition to hospitalization in a medical ward and infectious diseases consultation.

CONCLUSIONS

Prolonged courses of antibiotic treatment were common and treatment adherence to guidelines poor in diverticulitis, moderate in complicated UTI and excellent in endocarditis.

The red thread between methylation and mutation in bacterial antibiotic resistance: How third-generation sequencing can help to unravel this relationship

DNA methylation is an important mechanism involved in bacteria limiting foreign DNA acquisition, maintenance of mobile genetic elements, DNA mismatch repair, and gene expression. Changes in DNA methylation pattern are observed in bacteria under stress conditions, including exposure to antimicrobial compounds. These changes can result in transient and fast-appearing adaptive antibiotic resistance (AdR) phenotypes, e.g., strain overexpressing efflux pumps. DNA methylation can be related to DNA mutation rate, because it is involved in DNA mismatch repair systems and because methylated bases are well-known mutational hotspots. The AdR process can be the first important step in the selection of antibiotic-resistant strains, allowing the survival of the bacterial population until more efficient resistant mutants emerge. Epigenetic modifications can be investigated by third-generation sequencing platforms that allow us to simultaneously detect all the methylated bases along with the DNA sequencing. In this scenario, this sequencing technology enables the study of epigenetic modifications in link with antibiotic resistance and will help to investigate the relationship between methylation and mutation in the development of stable mechanisms of resistance.

Antimicrobial Stewardship at Transitions of Care to Outpatient Settings: Synopsis and Strategies

Inappropriate antibiotic use and associated consequences, including pathogen resistance and Clostridioides difficile infection, continue to serve as significant threats in the United States, with increasing incidence in the community setting. While much attention has been granted towards antimicrobial stewardship in acute care settings, the transition to the outpatient setting represents a significant yet overlooked area to target optimized antimicrobial utilization. In this article, we highlight notable areas for improved practices and present an interventional approach to stewardship tactics with a framework of disease, drug, dose, and duration. In doing so, we review current evidence regarding stewardship strategies at transitional settings, including diagnostic guidance, technological clinical support, and behavioral and educational approaches for both providers and patients.

Machine Learning Approach to Predicting Absence of Serious Bacterial Infection at PICU Admission

BACKGROUND AND OBJECTIVES

Serious bacterial infection (SBI) is common in the PICU. Antibiotics can mitigate associated morbidity and mortality but have associated adverse effects. Our objective is to develop machine learning models able to identify SBI-negative children and reduce unnecessary antibiotics.

METHODS

We developed models to predict SBI-negative status at PICU admission using vital sign, laboratory, and demographic variables. Children 3-months to 18-years-old admitted to our PICU, between 2011 and 2020, were included if evaluated for infection within 24-hours, stratified by documented antibiotic exposure in the 48-hours prior. Area under the receiver operating characteristic curve (AUROC) was the primary model accuracy measure; secondarily, we calculated the number of SBI-negative children subsequently provided antibiotics in the PICU identified as low-risk by each model.

RESULTS

A total of 15 074 children met inclusion criteria; 4788 (32%) received antibiotics before PICU admission. Of these antibiotic-exposed patients, 2325 of 4788 (49%) had an SBI. Of the 10 286 antibiotic-unexposed patients, 2356 of 10 286 (23%) had an SBI. In antibiotic-exposed children, a radial support vector machine model had the highest AUROC (0.80) for evaluating SBI, identifying 48 of 442 (11%) SBI-negative children provided antibiotics in the PICU who could have been spared a median 3.7 (interquartile range 0.9-9.0) antibiotic-days per patient. In antibiotic-unexposed children, a random forest model performed best, but was less accurate overall (AUROC 0.76), identifying 33 of 469 (7%) SBI-negative children provided antibiotics in the PICU who could have been spared 1.1 (interquartile range 0.9-3.7) antibiotic-days per patient.

CONCLUSIONS

Among children who received antibiotics before PICU admission, machine learning models can identify children at low risk of SBI and potentially reduce antibiotic exposure.

Unraveling the Nature of Antibiotics: Is It a Cure or a New Hurdle to the Patient Treatment?

Antimicrobial resistance is an increasing problem worldwide that has been exacerbated by antibiotic misuse worldwide. Growing antibiotic resistance can be attributed to as well as leads to severe infections, complications, prolonged hospital admissions, and higher mortality. One of the most important goals of administering antimicrobials is to avoid establishing antibiotic resistance during therapy. This can be done by drastically lowering worldwide antimicrobial usage, both in present and future. While current management methods to legislate antimicrobials and educate the healthcare community on the challenges are beneficial, they do not solve the problem of attaining an overall reduction in antimicrobial usage in humans. Application of rapid microbiological diagnostics for identification and antimicrobial susceptibility testing, use of inflammation markers to guide initiation and duration of therapies, reduction of standard antibiotic course durations, individualization of antibiotic treatments, and dosing considering pharmacokinetics are all possible strategies to optimize antibiotic use in everyday clinical practice and reduce the risk of inducing bacterial resistance. Furthermore, to remove any impediments to proper prescribing, strategies to improve antibiotic prescribing and antibiotic stewardship programs should enable clinical reasoning and enhance the prescribing environment. In addition, the well-established association between antimicrobial usage and resistance should motivate efforts to develop antimicrobial treatment regimens that facilitate the evolution of resistance. This review discusses the role of antibiotics, their current application in human medicine, and how the resistance has evolved to the existing antibiotics based on the existing literature.

A Microbe-Derived Efflux Pump Inhibitor of the Resistance-Nodulation-Cell Division Protein Restores Antibiotic Susceptibility in Escherichia coli and Pseudomonas aeruginosa

The use of efflux pump inhibitors (EPIs) as potentiators along with the traditional antibiotics assists in the warfare against antibiotic-resistant superbugs. Efflux pumps of the resistance-nodulation-cell division (RND) family play crucial roles in multidrug resistance in Escherichia coli and Pseudomonas aeruginosa. Despite several efforts, clinically useful inhibitors are not available at present. This study describes ethyl 4-bromopyrrole-2-carboxylate (RP1) isolation, an inhibitor of RND transporters from the library of 4000 microbial exudates. RP1 acts synergistically with antibiotics by reducing their minimum inhibitory concentration in strains overexpressing archetype RND transporters (AcrAB-TolC and MexAB-OprM). It also improves the accumulation of Hoechst 33342 and inhibits its efflux (a hallmark of EPI functionality). The antibiotic-RP1 combinations prolong the postantibiotic effects and reduce the mutation prevention concentration of antibiotics. Additionally, from Biolayer Interferometry spectra, it appears that RP1 is bound to AcrB. RP1 displays low mammalian cytotoxicity, no Ca²⁺ channel inhibitory effects, and reduces the intracellular invasion of E. coli and P. aeruginosa in macrophages. Furthermore, the RP1-levofloxacin combination is nontoxic, well-tolerated, and notably effective in a murine lung infection model. In sum, RP1 is a potent EPI and worthy of further consideration as a potentiator to improve the effectiveness of existing antibiotics.

In vivo Pharmacokinetic/Pharmacodynamic (PK/PD) Profiles of Tulathromycin in an Experimental Intraperitoneal Haemophilus parasuis Infection Model in Neutropenic Guinea Pigs

Tulathromycin is a semi-synthetic macrolide antimicrobial that has an important role in veterinary medicine for respiratory disease. The objective of the study was to develop a pharmacokinetic/pharmacodynamic (PK/PD) model to examine the efficacy and determine an optimal dosage of tulathromycin intramuscular (IM) treatment against Haemophilus parasuis infection induced after intraperitoneal inoculation in neutropenic guinea pigs. The PKs of tulathromycin in serum and lung tissue after intramuscular administration at doses of 1, 10, and 20 mg/kg in H. parasuis-infected neutropenic guinea pigs were evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The tulathromycin minimum inhibitory concentration (MIC) against H. parasuis was ~16 times lower in guinea pig serum (0.03 μg/mL) than in cation-adjusted Mueller-Hinton broth (CAMHB) (0.5 μg/mL). The ratio of the 168-h area under the concentration-time curve (AUC) to MIC (AUC168h/MIC) positively correlated with the in vivo antibacterial effectiveness of tulathromycin (R 2 = 0.9878 in serum and R 2 = 0.9911 in lung tissue). The computed doses to achieve a reduction of 2-log10 CFU/lung from the ratios of AUC72h/MIC were 5.7 mg/kg for serum and 2.5 mg/kg for lung tissue, which lower than the values of 13.2 mg/kg for serum and 8.9 mg/kg for lung tissue with AUC168h/MIC. In addition, using as objective a 2-log10 reduction and an AUC0-72h as the value of the PK/PD index could be more realistic. The results of this study could provide a solid foundation for the application of PK/PD models in research on macrolide antibiotics used to treat respiratory diseases.

Are Efficient-Dose Mixtures a Solution to Reduce Fungicide Load and Delay Evolution of Resistance? An Experimental Evolutionary Approach

Pesticide resistance poses a critical threat to agriculture, human health and biodiversity. Mixtures of fungicides are recommended and widely used in resistance management strategies. However, the components of the efficiency of such mixtures remain unclear. We performed an experimental evolutionary study on the fungal pathogen Z. tritici to determine how mixtures managed resistance. We compared the effect of the continuous use of single active ingredients to that of mixtures, at the minimal dose providing full control of the disease, which we refer to as the "efficient" dose. We found that the performance of efficient-dose mixtures against an initially susceptible population depended strongly on the components of the mixture. Such mixtures were either as durable as the best mixture component used alone, or worse than all components used alone. Moreover, efficient dose mixture regimes probably select for generalist resistance profiles as a result of the combination of selection pressures exerted by the various components and their lower doses. Our results indicate that mixtures should not be considered a universal strategy. Experimental evaluations of specificities for the pathogens targeted, their interactions with fungicides and the interactions between fungicides are crucial for the design of sustainable resistance management strategies.

Role of bacterial motility in differential resistance mechanisms of silver nanoparticles and silver ions

Unlike conventional antimicrobials, the study of bacterial resistance to silver nanoparticles (AgNPs) remains in its infancy and the mechanism(s) through which it evolves are limited and inconclusive. The central question remains whether bacterial resistance is driven by the AgNPs, released Ag(I) ions or a combination of these and other factors. Here, we show a specific resistance in an Escherichia coli K-12 MG1655 strain to subinhibitory concentrations of AgNPs, and not Ag(I) ions, as indicated by a statistically significant greater-than-twofold increase in the minimum inhibitory concentration occurring after eight repeated passages that was maintained after the AgNPs were removed and reintroduced. Whole-population genome sequencing identified a cusS mutation associated with the heritable resistance that possibly increased silver ion efflux. Finally, we rule out the effect of particle aggregation on resistance and suggest that the mechanism of resistance may be enhanced or mediated by flagellum-based motility.

Antibiotic pharmacokinetic/pharmacodynamic modelling: MIC, pharmacodynamic indices and beyond

The dramatic increase in antimicrobial resistance and the limited pharmacological treatment options highlight the urgent need to optimize therapeutic regimens of new and available anti-infectives. Several in-vitro and in-vivo infection models are employed to understand the relationship between drug exposure profiles in plasma or at the site of infection (pharmacokinetics) and the time course of therapeutic response (pharmacodynamics) to select and optimize dosage regimens for new and approved drugs. Well-designed preclinical studies, combined with mathematical-model-based pharmacokinetic/pharmacodynamic analysis and in-silico simulations, are critical for the effective translation of preclinical data and design of appropriate and successful clinical trials. Integration with population pharmacokinetic modelling and simulations allows for the incorporation of interindividual variability that occurs in both pharmacokinetics and pharmacodynamics, and helps to predict the probability of target attainment and treatment outcome in patients. This article reviews the role of pharmacokinetic/pharmacodynamic approaches in the optimization of dosage regimens to maximize antibacterial efficacy while minimizing toxicity and emergence of resistance, and to achieve a high likelihood of therapeutic success. Polymyxin B, an approved drug with a narrow therapeutic window, serves as an illustrative example to highlight the importance of pharmacokinetic/pharmacodynamic modelling in conjunction with experimentation, employing static time-kill studies followed by dynamic in-vitro or in-vivo models, or both, to learn and confirm mechanistic insights necessary for translation to the bedside.

Multi-step vs. single-step resistance evolution under different drugs, pharmacokinetics, and treatment regimens

The success of antimicrobial treatment is threatened by the evolution of drug resistance. Population genetic models are an important tool in mitigating that threat. However, most such models consider resistance emergence via a single mutational step. Here, we assembled experimental evidence that drug resistance evolution follows two patterns: (i) a single mutation, which provides a large resistance benefit, or (ii) multiple mutations, each conferring a small benefit, which combine to yield high-level resistance. Using stochastic modeling, we then investigated the consequences of these two patterns for treatment failure and population diversity under various treatments. We find that resistance evolution is substantially limited if more than two mutations are required and that the extent of this limitation depends on the combination of drug type and pharmacokinetic profile. Further, if multiple mutations are necessary, adaptive treatment, which only suppresses the bacterial population, delays treatment failure due to resistance for a longer time than aggressive treatment, which aims at eradication.

Adaptation at different points along antibiotic concentration gradients

Antibiotic concentrations vary dramatically in the body and the environment. Hence, understanding the dynamics of resistance evolution along antibiotic concentration gradients is critical for predicting and slowing the emergence and spread of resistance. While it has been shown that increasing the concentration of an antibiotic slows resistance evolution, how adaptation to one antibiotic concentration correlates with fitness at other points along the gradient has not received much attention. Here, we selected populations of Escherichia coli at several points along a concentration gradient for three different antibiotics, asking how rapidly resistance evolved and whether populations became specialized to the antibiotic concentration they were selected on. Populations selected at higher concentrations evolved resistance more slowly but exhibited equal or higher fitness across the whole gradient. Populations selected at lower concentrations evolved resistance rapidly, but overall fitness in the presence of antibiotics was lower. However, these populations readily adapted to higher concentrations upon subsequent selection. Our results indicate that resistance management strategies must account not only for the rates of resistance evolution but also for the fitness of evolved strains.

Meropenem, Cefepime, and Piperacillin Protein Binding in Patient Samples

BACKGROUND

The mortality rate of patients with a drug-resistant bacterial infection is high, as are the associated treatment costs. To overcome these issues, optimization of the available therapeutic options is required. Beta-lactams are time-dependent antibiotics and their efficacy is determined by the amount of time the free concentration remains above the minimum inhibitory concentration. Therefore, the aim of this study was to assess the extent and variability of protein binding for meropenem, cefepime, and piperacillin.

METHODS

Plasma samples for the analysis of meropenem, cefepime, and piperacillin were collected from patients admitted to a tertiary care hospital as part of the standard care. The bound and unbound drug fractions in the samples were separated by ultrafiltration. Validated liquid chromatography-tandem mass spectrometry assays were used to quantify the total and free plasma concentrations, and the protein binding was determined.

RESULTS

Samples from 95 patients were analyzed. The median (range) age of patients was 56 years (17-87) and the median (range) body mass index was 25.7 kg/m (14.7-74.2). Approximately 59% of the patients were men. The median (range) unbound fraction (fu) was 62.5% (41.6-99.1) for meropenem, 61.4% (51.6-99.2) for cefepime, and 48.3% (39.4-71.3) for piperacillin. In the bivariate analysis, as the total meropenem concentration increased, the fu increased (r = 0.37, P = 0.045). A decrease in piperacillin fu was observed as the albumin concentration increased (r = -0.56, P = 0.005).

CONCLUSIONS

The average fu values were lower than those reported in the literature. There was also a large variability in fu; hence, it should be considered when managing patients administered with these drugs through direct measurements of free drug concentrations.

Effectiveness of Shorter Versus Longer Durations of Therapy for Common Inpatient Infections Associated With Bacteremia: A Multicenter, Propensity-Weighted Cohort Study

BACKGROUND

National guidelines for pneumonia (PNA), urinary tract infection (UTI), and acute bacterial skin and skin structure infection (ABSSSI) do not address treatment duration for infections associated with bacteremia. We evaluated clinical outcomes of patients receiving shorter (5-9 days) versus longer (10-15 days) duration of antibiotics.

METHODS

This was a multicenter retrospective cohort study of inpatients with uncomplicated PNA, UTI, or ABSSSI and associated bacteremia. The primary outcome was clinical failure, a composite of rehospitalization, reinitiation of antibiotics, or all-cause mortality within 30 days of antibiotic completion. Secondary outcomes included individual components of the primary outcome, Clostridioides difficile infection, and antibiotic-related adverse effects necessitating change in therapy. A propensity score-weighted logistic regression model was used to mitigate potential bias associated with nonrandom assignment of treatment duration.

RESULTS

Of 408 patients included, 123 received a shorter treatment duration (median 8 days) and 285 received a longer duration (median 13 days). In the propensity-weighted analysis, the probability of the primary outcome was 13.5% in the shorter group and 11.1% in the longer group (average treatment effect, 2.4%; odds ratio [OR], 1.25; 95% confidence interval [CI], .65-2.40; P = .505). However, shorter courses were associated with higher probability of restarting antibiotics (OR, 1.62; 95% CI, 1.01-2.61; P = .046) and C. difficile infection (OR, 4.01; 95% CI, 2.21-7.59; P < .0001).

CONCLUSIONS

Shorter courses of antibiotic treatment for PNA, UTI, and ABSSSI with bacteremia were not associated with increased overall risk of clinical failure; however, prospective studies are needed to further evaluate the effectiveness of shorter treatment durations.

Liposomes as Antibiotic Delivery Systems: A Promising Nanotechnological Strategy against Antimicrobial Resistance

Antimicrobial drugs are key tools to prevent and treat bacterial infections. Despite the early success of antibiotics, the current treatment of bacterial infections faces serious challenges due to the emergence and spread of resistant bacteria. Moreover, the decline of research and private investment in new antibiotics further aggravates this antibiotic crisis era. Overcoming the complexity of antimicrobial resistance must go beyond the search of new classes of antibiotics and include the development of alternative solutions. The evolution of nanomedicine has allowed the design of new drug delivery systems with improved therapeutic index for the incorporated compounds. One of the most promising strategies is their association to lipid-based delivery (nano)systems. A drug's encapsulation in liposomes has been demonstrated to increase its accumulation at the infection site, minimizing drug toxicity and protecting the antibiotic from peripheral degradation. In addition, liposomes may be designed to fuse with bacterial cells, holding the potential to overcome antimicrobial resistance and biofilm formation and constituting a promising solution for the treatment of potential fatal multidrug-resistant bacterial infections, such as methicillin resistant Staphylococcus aureus. In this review, we aim to address the applicability of antibiotic encapsulated liposomes as an effective therapeutic strategy for bacterial infections.

An optimized method for the detection and spatial distribution of aminoglycoside and vancomycin antibiotics in tissue sections by mass spectrometry imaging

Suboptimal antibiotic dosing has been identified as one of the key drivers in the development of multidrug-resistant (MDR) bacteria that have become a global health concern. Aminoglycosides and vancomycin are broad-spectrum antibiotics used to treat critically ill patients infected by a variety of MDR bacterial species. Resistance to these antibiotics is becoming more prevalent. In order to design proper antibiotic regimens that maximize efficacy and minimize the development of resistance, it is pivotal to obtain the in situ pharmacokinetic-pharmacodynamic profiles at the sites of infection. Mass spectrometry imaging (MSI) is the ideal technique to achieve this. Aminoglycosides, due to their structure, suffer from poor ionization efficiency. Additionally, ion suppression effects by endogenous molecules greatly inhibit the detection of aminoglycosides and vancomycin at therapeutic levels. In the current study, an optimized method was developed that enabled the detection of these antibiotics by MSI. Tissue spotting experiments demonstrated a 5-, 15-, 35-, and 54-fold increase in detection sensitivity in the washed samples for kanamycin, amikacin, streptomycin, and vancomycin, respectively. Tissue mimetic models were utilized to optimize the washing time and matrix additive concentration. These studies determined the improved limit of detection was 40 to 5 μg/g of tissue for vancomycin and streptomycin, and 40 to 10 μg/g of tissue for kanamycin and amikacin. The optimized protocol was applied to lung sections from mice dosed with therapeutic levels of kanamycin and vancomycin. The washing protocol enabled the first drug distribution investigations of aminoglycosides and vancomycin by MSI, paving the way for site-of-disease antibiotic penetration studies.

Population Pharmacokinetic Models of Antituberculosis Drugs in Patients: A Systematic Critical Review

BACKGROUND

Tuberculosis (TB) remains one of the most important infectious diseases. Population pharmacokinetic (pop-PK) models are widely used to individualize dosing regimens of several antibiotics, but their application in anti-TB drug studies is scant. The aim of this study was to provide an insight regarding the status of pop-PK for these drugs and to compare results obtained through both parametric and nonparametric approaches to design precise dosage regimens.

METHODS

First, a systematic approach was implemented, searching in PubMed and Google Scholar. Articles that did not include human patients, that lacked an explicit structural model, that analyzed drugs inactive against M. tuberculosis, or were without full-text access, were excluded. Second, the PK parameters were summarized and categorized as parametric versus nonparametric results. Third, a Monte Carlo simulation was performed in Pmetrics using the results of both groups, and an error term was built to describe the imprecision of each PK modeling approach.

RESULTS

Thirty-three articles reporting at least 1 pop-PK model of 19 anti-TB drug were found; 46 different models including PK parameter estimates and their relevant covariates were also reported. Only 9 models were based on nonparametric approaches. Rifampin was the drug most studied, but only using parametric approaches. The simulations showed that nonparametric approaches improve the error term compared with parametric approaches.

CONCLUSIONS

More and better models, ideally using nonparametric approaches linked with clear pharmacodynamic goals, are required to optimize anti-TB drug dosing, as recommended in the WHO End TB strategy.

Advancing pediatric antimicrobial stewardship: Has pharmacodynamic dosing for gram-negative infections taken effect?

Objective:

To characterize pharmacodynamic dosing strategies used at children’s hospitals using a national survey.

Design:

Survey.

Setting:

Children’s hospitals.

Participants:

Volunteer sample of antimicrobial stewardship program (ASP) respondents.

Methods:

A nationwide survey was conducted to gain greater insight into the current adoption of nontraditional dosing methods and monitoring of select β-lactam and fluoroquinolone antibiotics used to treat serious gram-negative infections in pediatric populations. The survey was performed through the Sharing Antimicrobial Reports for Pediatric Stewardship (SHARPS) Collaborative.

Results:

Of the 75 children’s hospitals that responded, 68% of programs reported adoption of pharmacodynamically optimized dosing using prolonged β-lactam infusions and 35% using continuous β-lactam infusions, although use was infrequent. Factors including routine MIC monitoring and formal postgraduate training and board certification of ASP pharmacists were associated with increased utilization of pharmacodynamic dosing. In addition, 60% of programs reported using pharmacodynamically optimized ciprofloxacin and 14% reported using pharmacodynamically optimized levofloxacin. Only 20% of programs monitored β-lactam levels; they commonly cited lack of published guidance, practitioner experience, and laboratomory support as reasons for lack of utilization. Less physician time dedicated to ASP programs was associated with lower adoption of optimized dosing.

Conclusions:

Use of pharmacodynamic dosing through prolonged and continuous infusions of β-lactams have not yet been routinely adopted at children’s hospitals. Further guidance from trials and literature are needed to continue to guide pediatric pharmacodynamic dosing efforts. Children’s hospitals should utilize these data to compare practices and to prioritize further research and education efforts.

Treatment timing shifts the benefits of short and long antibiotic treatment over infection

Antibiotics are the major tool for treating bacterial infections. Rising antibiotic resistance, however, calls for a better use of antibiotics. While classical recommendations favor long and aggressive treatments, more recent clinical trials advocate for moderate regimens. In this debate, two axes of 'aggression' have typically been conflated: treatment intensity (dose) and treatment duration. The third dimension of treatment timing along each individual's infection course has rarely been addressed. By using a generic mathematical model of bacterial infection controlled by immune response, we examine how the relative effectiveness of antibiotic treatment varies with its timing, duration and antibiotic kill rate. We show that short or long treatments may both be beneficial depending on treatment onset, the target criterion for success and on antibiotic efficacy. This results from the dynamic trade-off between immune response build-up and resistance risk in acute, self-limiting infections, and uncertainty relating symptoms to infection variables. We show that in our model early optimal treatments tend to be 'short and strong', while late optimal treatments tend to be 'mild and long'. This suggests a shift in the aggression axis depending on the timing of treatment. We find that any specific optimal treatment schedule may perform more poorly if evaluated by other criteria, or under different host-specific conditions. Our results suggest that major advances in antibiotic stewardship must come from a deeper empirical understanding of bacterial infection processes in individual hosts. To guide rational therapy, mathematical models need to be constrained by data, including a better quantification of personal disease trajectory in humans. Lay summary: Bacterial infections are becoming more difficult to treat worldwide because bacteria are becoming resistant to the antibiotics used. Addressing this problem requires a better understanding of how treatment along with other host factors impact antibiotic resistance. Until recently, most theoretical research has focused on the importance of antibiotic dosing on antibiotic resistance, however, duration and timing of treatment remain less explored. Here, we use a mathematical model of a generic bacterial infection to study three aspects of treatment: treatment dose/efficacy (defined by the antibiotic kill rate), duration, and timing, and their impact on several infection endpoints. We show that short and long treatment success strongly depends on when treatment begins (defined by the symptom threshold), the target criterion to optimize, and on antibiotic efficacy. We find that if administered early in an infection, "strong and short" therapy performs better, while if treatment begins at higher bacterial densities, a "mild and long" course of antibiotics is favored. In the model host immune defenses are key in preventing relapses, controlling antibiotic resistant bacteria and increasing the effectiveness of moderate intervention. In order to improve rational treatments of human infections, we call for a better quantification of individual disease trajectories in bacteria-immunity space.

Modification of empirical antimicrobial regimens in large animal medicine

BACKGROUND

Empirical antimicrobial regimens can be modified following new diagnostic information or when empirical treatment fails. Little is known about the frequency or clinical context in which these modifications occur. We characterised these modifications in a large animal hospital to identify when antimicrobial use could be optimised.

METHODS

Chart reviews were performed for all inpatients and outpatients administered antimicrobials at a large animal veterinary referral and teaching hospital in 2017-2018 (n=1163 visits) to determine when and why empirical regimens were modified. Multinomial logistic regression was performed to identify factors associated with reasons for modification.

RESULTS

Empirical antimicrobial regimens were modified in 17.3 per cent of visits. The main reasons were parenteral-oral conversions in horses and failure of disease prevention or treatment in ruminants. Empirical therapy for disease prevention was more likely to be modified because of complications in ruminants and in animals on the emergency/critical care service. Empirical therapy for disease treatment was more often modified for reasons other than de-escalation in ruminants and in animals with longer lengths of stay.

CONCLUSIONS

Empirical antimicrobial regimens were modified infrequently and mostly for purposes of parenteral-oral conversion in horses and lack of response in ruminants. De-escalation of antimicrobials administered for disease treatment, when guided by diagnostics, is a major tenet of judicious antimicrobial use. However, more research is needed to determine when and how antimicrobial regimens administered for disease prevention should be modified.

Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells

A better understanding of how antibiotic exposure impacts the evolution of resistance in bacterial populations is crucial for designing more sustainable treatment strategies. The conventional approach to this question is to measure the range of concentrations over which resistant strain(s) are selectively favored over a sensitive strain. Here, we instead investigate how antibiotic concentration impacts the initial establishment of resistance from single cells, mimicking the clonal expansion of a resistant lineage following mutation or horizontal gene transfer. Using two Pseudomonas aeruginosa strains carrying resistance plasmids, we show that single resistant cells have <5% probability of detectable outgrowth at antibiotic concentrations as low as one-eighth of the resistant strain's minimum inhibitory concentration (MIC). This low probability of establishment is due to detrimental effects of antibiotics on resistant cells, coupled with the inherently stochastic nature of cell division and death on the single-cell level, which leads to loss of many nascent resistant lineages. Our findings suggest that moderate doses of antibiotics, well below the MIC of resistant strains, may effectively restrict de novo emergence of resistance even though they cannot clear already-large resistant populations.

Bacterial sepsis : Diagnostics and calculated antibiotic therapy

The mortality of patients with sepsis and septic shock is still unacceptably high. An effective calculated antibiotic treatment within 1 h of recognition of sepsis is an important target of sepsis treatment. Delays lead to an increase in mortality; therefore, structured treatment concepts form a rational foundation, taking relevant diagnostic and treatment steps into consideration. In addition to the assumed infection and individual risks of each patient, local resistance patterns and specific problem pathogens must be taken into account during the selection of anti-infective treatment. Many pathophysiologic alterations influence the pharmacokinetics (PK) of antibiotics during sepsis. The principle of standard dosing should be abandoned and replaced by an individual treatment approach with stronger weighting of the pharmacokinetics/pharmacodynamics (PK/PD) index of the substance groups. Although this is not yet the clinical standard, prolonged (or continuous) infusion of β‑lactam antibiotics and therapeutic drug monitoring (TDM) can help to achieve defined PK targets. Prolonged infusion is sufficient without TDM, but for continuous infusion, TDM is generally necessary. A further argument for individual PK/PD-oriented antibiotic approaches is the increasing number of infections due to multidrug-resistant (MDR) pathogens in the intensive care unit. For effective treatment, antibiotic stewardship teams (ABS teams) are becoming more established. Interdisciplinary cooperation of the ABS team with infectious disease (ID) specialists, microbiologists, and clinical pharmacists leads not only to rational administration of antibiotics, but also has a positive influence on treatment outcome. The gold standards for pathogen identification are still culture-based detection and microbiologic resistance testing for the various antibiotic groups. Despite the rapid investigation time, novel polymerase chain reaction(PCR)-based procedures for pathogen identification and resistance determination are currently only an adjunct to routine sepsis diagnostics, due to the limited number of studies, high costs, and limited availability. In complicated septic courses with multiple anti-infective therapies or recurrent sepsis, PCR-based procedures can be used in addition to treatment monitoring and diagnostics. Novel antibiotics represent potent alternatives in the treatment of MDR infections. Due to the often defined spectrum of pathogens and the practically (still) absent resistance, they are suitable for targeted treatment of severe MDR infections (therapy escalation). (Contribution available free of charge by "Free Access" [ https://link.springer.com/article/10.1007/s00101-017-0396-z ].).

Aryl Hydrocarbon Receptor Modulation by Tuberculosis Drugs Impairs Host Defense and Treatment Outcomes

Antimicrobial resistance in tuberculosis (TB) is a public health threat of global dimension, worsened by increasing drug resistance. Host-directed therapy (HDT) is an emerging concept currently explored as an adjunct therapeutic strategy for TB. One potential host target is the ligand-activated transcription factor aryl hydrocarbon receptor (AhR), which binds TB virulence factors and controls antibacterial responses. Here, we demonstrate that in the context of therapy, the AhR binds several TB drugs, including front line drugs rifampicin (RIF) and rifabutin (RFB), resulting in altered host defense and drug metabolism. AhR sensing of TB drugs modulates host defense mechanisms, notably impairs phagocytosis, and increases TB drug metabolism. Targeting AhR in vivo with a small-molecule inhibitor increases RFB-treatment efficacy. Thus, the AhR markedly impacts TB outcome by affecting both host defense and drug metabolism. As a corollary, we propose the AhR as a potential target for HDT in TB in adjunct to canonical chemotherapy.

Development, optimization, standardization, and validation of a simple in-house agar gradient method to determine minimum inhibitory concentration of vancomycin for Staphylococcus aureus

BACKGROUND:

The Clinical and Laboratory Standards Institute recommends reporting minimum inhibitory concentration (MIC) values of vancomycin for Staphylococcus aureus. Commercial MIC strips are expensive, and the traditional broth microdilution method is cumbersome. With this background, we attempted to develop and standardize an in-house agar gradient method to determine MIC values of vancomycin for S. aureus.

OBJECTIVES:

To develop and validate an in-house vancomycin MIC strip, based on simple agar gradient method for S. aureus as per bioassay development guidelines.

MATERIALS AND METHODS:

Filter paper gradient strips were made in house and impregnated with varying concentrations of vancomycin to create an antibiotic gradient. During standardization, MICs of ninety clinical strains of S. aureus and ATCC 29213 were tested by the broth microdilution and commercial strip followed by the in-house strip. During the validation stage, MICs of ninety different clinical strains of S. aureus and ATCC 29213 were determined by the in-house strip followed by MIC detection by broth microdilution and commercial strips. A reading of more than ± 1log₂ dilution compared with broth microdilution was considered as an outlier.

RESULTS:

During the initial stage, there were 7/90 outliers in the clinical strains, and no outliers were seen with the ATCC 29213 control strain. Corrective action included increasing precaution during the antibiotic impregnation on the strip. During validation stage, only 4/90 outliers were observed in the clinical strains. The commercial strips had 29/90 among clinical and 15/30 outliers in the control strain during the prevalidation phase. Despite maintaining cold chain during the validation phase, the outliers for commercial strip were 18/90 and 4/30 for clinical and control strains, respectively.

CONCLUSION:

Reporting vancomycin MIC for S. aureus may be attempted using the in-house method after validating it with a gold standard broth microdilution method and quality control as per protocol.

Antimicrobial Resistance Profiling of Gallibacterium anatis from Layers Reveals High Number of Multiresistant Strains and Substantial Variability Even Between Isolates from the Same Organ

In this investigation, data on antimicrobial resistance (AMR) profiles of 213 Gallibacterium anatis isolates were determined from 93 laying hens originating from 39 flocks. Each flock was sampled three times during its life time for the presence of G. anatis. The broth microdilution method was applied comprising 21 antimicrobial substances. Multidrug resistance was found in 96.2% of the G. anatis isolates. Most of the isolates were resistant to tetracycline (89.2%), tylosin (94.8%), enrofloxacin (58.2%), nalidixic acid (77.4%), and sulfamethoxazole (77.0%). Resistance against antimicrobial substances increased significantly with the age of birds. A total of 99 different AMR profiles were detected. On flock level, different AMR profiles were found in 71.8% of the flocks independent of the sampling time point. On bird level, identical AMR profiles were mostly found in isolates originating from the same organ of a single bird, but 22 such paired isolates differed in their AMR profile. Variations of AMR profiles were found within isolates from a single bird, but from different organs. Isolates from systemic organs were significantly more resistant to different antimicrobial substances compared to isolates from the reproductive tract. No influence could be found in regard to an increase of resistance and applied antibiotic treatment.