A 9-Year retrospective review of antibiotic cycling in a surgical intensive care unit

Towards evolutionary predictions: Current promises and challenges

Evolution has traditionally been a historical and descriptive science, and predicting future evolutionary processes has long been considered impossible. However, evolutionary predictions are increasingly being developed and used in medicine, agriculture, biotechnology and conservation biology. Evolutionary predictions may be used for different purposes, such as to prepare for the future, to try and change the course of evolution or to determine how well we understand evolutionary processes. Similarly, the exact aspect of the evolved population that we want to predict may also differ. For example, we could try to predict which genotype will dominate, the fitness of the population or the extinction probability of a population. In addition, there are many uses of evolutionary predictions that may not always be recognized as such. The main goal of this review is to increase awareness of methods and data in different research fields by showing the breadth of situations in which evolutionary predictions are made. We describe how diverse evolutionary predictions share a common structure described by the predictive scope, time scale and precision. Then, by using examples ranging from SARS-CoV2 and influenza to CRISPR-based gene drives and sustainable product formation in biotechnology, we discuss the methods for predicting evolution, the factors that affect predictability and how predictions can be used to prevent evolution in undesirable directions or to promote beneficial evolution (i.e. evolutionary control). We hope that this review will stimulate collaboration between fields by establishing a common language for evolutionary predictions.

Identification of antibiotic pairs that evade concurrent resistance via a retrospective analysis of antimicrobial susceptibility test results

Background

Some antibiotic pairs display a property known as collateral sensitivity in which the evolution of resistance to one antibiotic increases sensitivity to the other. Alternating between collaterally sensitive antibiotics has been proposed as a sustainable solution to the problem of antibiotic resistance. We aimed to identify antibiotic pairs that could be considered for treatment strategies based on alternating antibiotics.

Methods

We did a retrospective analysis of 448 563 antimicrobial susceptibility test results acquired over a 4-year period (Jan 1, 2015, to Dec 31, 2018) from 23 hospitals in the University of Pittsburgh Medical Center (Pittsburgh, PA, USA) hospital system. We used a score based on mutual information to identify pairs of antibiotics displaying disjoint resistance, wherein resistance to one antibiotic is commonly associated with susceptibility to the other and vice versa. We applied this approach to the six most frequently isolated bacterial pathogens (Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Enterococcus faecalis, Pseudomonas aeruginosa, and Proteus mirabilis) and subpopulations of each created by conditioning on resistance to individual antibiotics. To identify higher-order antibiotic interactions, we predicted rates of multidrug resistance for triplets of antibiotics using Markov random fields and compared these to the observed rates.

Findings

We identified 69 antibiotic pairs displaying varying degrees of disjoint resistance for subpopulations of the six bacterial species. However, disjoint resistance was rarely conserved at the species level, with only 6 (0·7%) of 875 antibiotic pairs showing evidence of disjoint resistance. Instead, more than half of antibiotic pairs (465 [53·1%] of 875) exhibited signatures of concurrent resistance, whereby resistance to one antibiotic is associated with resistance to another. We found concurrent resistance to extend to more than two antibiotics, with observed rates of resistance to three antibiotics being higher than predicted from pairwise information alone.

Interpretation

The high frequency of concurrent resistance shows that bacteria have means of counteracting multiple antibiotics at a time. The almost complete absence of disjoint resistance at the species level implies that treatment strategies based on alternating between antibiotics might require subspecies level pathogen identification and be limited to a few antibiotic pairings.

Funding

US National Institutes of Health.

Surgical Infection Society Research Priorities: A Narrative Review of Fourteen Years of Progress

Background: In 2006, the Surgical Infection Society (SIS) utilized a modified Delphi approach to define 15 specific priority research questions that remained unanswered in the field of surgical infections. The aim of the current study was to evaluate the scientific progress achieved during the ensuing period in answering each of the 15 research questions and to determine if additional research in these fields is warranted. Methods: For each of the questions, a literature search using the National Center for Biotechnology Information (NCBI) was performed by the Scientific Studies Committee of the SIS to identify studies that attempted to address each of the defined questions. This literature was analyzed and summarized. The data on each question were evaluated by a surgical infections expert to determine if the question was answered definitively or remains unanswered. Results: All 15 priority research questions were studied in the last 14 years; six questions (40%) were definitively answered and 9 questions (60%) remain unanswered in whole or in part, mainly because of the low quality of the studies available on this topic. Several of the 9 unanswered questions were deemed to remain research priorities in 2020 and warrant further investigation. These included, for example, the role of empiric antimicrobial agents in nosocomial infections, the use of inotropes/vasopressors versus volume loading to raise the mean arterial pressure, and the role of increased antimicrobial dosing and frequency in the obese patient. Conclusions: Several surgical infection-related research questions prioritized in 2006 remain unanswered. Further high-quality research is required to provide a definitive answer to many of these priority knowledge gaps. An updated research agenda by the SIS is warranted at this time to define research priorities for the future.

Longitudinal comparative trial of antibiotic cycling and mixing on emergence of gram negative bacterial resistance in a pediatric medical intensive care unit

PURPOSE

To compare antibiotic mixing vs. cycling with respect to acquisition of resistance and PICU mortality.

MATERIALS AND METHODS

Children between >1 month to 12 years admitted to a medical PICU were enrolled over three phases (baseline, mixing and cycling) with washout interval of 3 months following each antibiotic strategy. Following a baseline phase, empiric gram negative antibiotic protocol for suspected HCAI, was sequentially subjected to mixing and cycling using Latin Square methodology. Surveillance cultures were taken at admission, 48 h, weekly thereafter and within 2 days of PICU discharge. Acquisition of resistance and PICU mortality were primary and secondary outcomes respectively.

RESULTS

778 children were enrolled; 99 baseline, 146 mixing, 362 cycling, and 171 during two washout phases. Proportion of children with acquired resistance at baseline (56.6%) was significantly higher than mixing (22.6%) and cycling (18.51%) (p < .0001). Adjusted hazards of acquired resistance (HR:0.82; 95% CI: 0.53-1.25, p = .352), and PICU mortality (RR1.07; 95% CI: 0.71-1.60, p = .72) were similar in cycling and mixing strategies.

CONCLUSIONS

Acquisition of resistance was significantly lower in both mixing and cycling as compared to baseline phase. Both were similar with respect to risk of antibiotic resistance as well as incidence of HCAI and PICU mortality.

Effects of Antibiotic Cycling Policy on Incidence of Healthcare-Associated MRSA and Clostridioides difficile Infection in Secondary Healthcare Settings

This quasi-experimental study investigated the effect of an antibiotic cycling policy based on time-series analysis of epidemiologic data, which identified antimicrobial drugs and time periods for restriction. Cyclical restrictions of amoxicillin/clavulanic acid, piperacillin/tazobactam, and clarithromycin were undertaken over a 2-year period in the intervention hospital. We used segmented regression analysis to compare the effect on the incidence of healthcare-associated Clostridioides difficile infection (HA-CDI), healthcare-associated methicillin-resistant Staphylococcus aureus (HA-MRSA), and new extended-spectrum β-lactamase (ESBL) isolates and on changes in resistance patterns of the HA-MRSA and ESBL organisms between the intervention and control hospitals. HA-CDI incidence did not change. HA-MRSA incidence increased significantly in the intervention hospital. The resistance of new ESBL isolates to amoxicillin/clavulanic acid and piperacillin/tazobactam decreased significantly in the intervention hospital; however, resistance to piperacillin/tazobactam increased after a return to the standard policy. The results question the value of antibiotic cycling to antibiotic stewardship.

Assessment of Awareness about Antibiotic Resistance and Practices Followed by Veterinarians for Judicious Prescription of Antibiotics: An Exploratory Study in Eastern Haryana Region of India

The rise of antibiotic resistance and its global outreach has recently become a subject of increasing importance in veterinary research with an objective to reduce the load of antibiotic resistance in dairy farming practices. The present study was designed to analyze antibiotic prescriptions by veterinarians and to evaluate the appropriateness of prescribing behavior in consistent with prudent use of antibiotics. A total of 48 veterinarians were selected randomly from government Veterinary hospitals constituting a total of 48 veterinarians as respondents. The study revealed that most of prescriptions corresponded sound to prudent use of antibiotic and its treatment guidelines. To assess their awareness about antibiotic resistance and its related veterinary practices, an exclusively Awareness Index of antibiotic resistance was developed. It was observed that antibiotics were prescribed in initial encounter of diagnosis; thus, antibiotic conservation practices were found lacking. The ethical awareness of veterinarians was found lacking to establish valid veterinary-client relationship and ensure active involvement of stakeholders. This study largely looks into this angle by unearthing the drug prescribing behavior in order to shape the interdisciplinary research on this biological and profoundly social issue.

Drug-mediated metabolic tipping between antibiotic resistant states in a mixed-species community

Microbes rarely exist in isolation, rather, they form intricate multi-species communities that colonize our bodies and inserted medical devices. However, the efficacy of antimicrobials is measured in clinical laboratories exclusively using microbial monocultures. Here, to determine how multi-species interactions mediate selection for resistance during antibiotic treatment, particularly following drug withdrawal, we study a laboratory community consisting of two microbial pathogens. Single-species dose responses are a poor predictor of community dynamics during treatment so, to better understand those dynamics, we introduce the concept of a dose-response mosaic, a multi-dimensional map that indicates how species' abundance is affected by changes in abiotic conditions. We study the dose-response mosaic of a two-species community with a 'Gene × Gene × Environment × Environment' ecological interaction whereby Candida glabrata, which is resistant to the antifungal drug fluconazole, competes for survival with Candida albicans, which is susceptible to fluconazole. The mosaic comprises several zones that delineate abiotic conditions where each species dominates. Zones are separated by loci of bifurcations and tipping points that identify what environmental changes can trigger the loss of either species. Observations of the laboratory communities corroborated theory, showing that changes in both antibiotic concentration and nutrient availability can push populations beyond tipping points, thus creating irreversible shifts in community composition from drug-sensitive to drug-resistant species. This has an important consequence: resistant species can increase in frequency even if an antibiotic is withdrawn because, unwittingly, a tipping point was passed during treatment.

Ecological effects of cefepime use during antibiotic cycling on the Gram-negative enteric flora of ICU patients

This study examines the impact of cefepime and APP-β (antipseudomonal penicillin/ β-lactamase inhibitor combinations) on Gram-negative bacterial colonization and resistance in two Australian ICUs. While resistance did not cumulatively increase, cefepime (but not APP-β treatment) was associated with acquisition of antibiotic resistant Enterobacteriaceae, consistent with an ecological effect. Analysis of the resident gut E. coli population in a subset of patients showed an increase in markers of horizontal gene transfer after cefepime exposure that helps explain the increase in APP-β resistance and reminds us that unmeasured impacts on the microbiome are key outcome determinants that need to be fully explored.

Modeling antimicrobial cycling and mixing: Differences arising from an individual-based versus a population-based perspective

In order to manage bacterial infections in hospitals in the face of antibiotic resistance, the two treatment protocols "mixing" and "cycling" have received considerable attention both from modelers and clinicians. However, the terms are not used in exactly the same way by both groups. This comes because the standard modeling approach disregards the perspective of individual patients. In this article, we investigate a model that comes closer to clinical practice and compare the predictions to the standard model. We set up two deterministic models, implemented as a set of differential equations, for the spread of bacterial infections in a hospital. Following the traditional approach, the first model takes a population-based perspective. The second model, in contrast, takes the drug use of individual patients into account. The alternative model can indeed lead to different predictions than the standard model. We provide examples for which in the new model, the opposite strategy maximizes the number of uninfected patients or minimizes the rate of spread of double resistance. While the traditional models provide valuable insight, care is hence needed in the interpretation of results.

Modeling antibiotic treatment in hospitals: A systematic approach shows benefits of combination therapy over cycling, mixing, and mono-drug therapies

Multiple treatment strategies are available for empiric antibiotic therapy in hospitals, but neither clinical studies nor theoretical investigations have yielded a clear picture when which strategy is optimal and why. Extending earlier work of others and us, we present a mathematical model capturing treatment strategies using two drugs, i.e the multi-drug therapies referred to as cycling, mixing, and combination therapy, as well as monotherapy with either drug. We randomly sample a large parameter space to determine the conditions determining success or failure of these strategies. We find that combination therapy tends to outperform the other treatment strategies. By using linear discriminant analysis and particle swarm optimization, we find that the most important parameters determining success or failure of combination therapy relative to the other treatment strategies are the de novo rate of emergence of double resistance in patients infected with sensitive bacteria and the fitness costs associated with double resistance. The rate at which double resistance is imported into the hospital via patients admitted from the outside community has little influence, as all treatment strategies are affected equally. The parameter sets for which combination therapy fails tend to fall into areas with low biological plausibility as they are characterised by very high rates of de novo emergence of resistance to both drugs compared to a single drug, and the cost of double resistance is considerably smaller than the sum of the costs of single resistance.

History of antibiotic adaptation influences microbial evolutionary dynamics during subsequent treatment

Antibiotic regimens often include the sequential changing of drugs to limit the development and evolution of resistance of bacterial pathogens. It remains unclear how history of adaptation to one antibiotic can influence the resistance profiles when bacteria subsequently adapt to a different antibiotic. Here, we experimentally evolved Pseudomonas aeruginosa to six 2-drug sequences. We observed drug order-specific effects, whereby adaptation to the first drug can limit the rate of subsequent adaptation to the second drug, adaptation to the second drug can restore susceptibility to the first drug, or final resistance levels depend on the order of the 2-drug sequence. These findings demonstrate how resistance not only depends on the current drug regimen but also the history of past regimens. These order-specific effects may allow for rational forecasting of the evolutionary dynamics of bacteria given knowledge of past adaptations and provide support for the need to consider the history of past drug exposure when designing strategies to mitigate resistance and combat bacterial infections.

Optimization of therapy against Pseudomonas aeruginosa with ceftazidime and meropenem using chemostats as model for infections

Pseudomonas aeruginosa is an opportunistic pathogen that can cause life-threatening infections in patients admitted to intensive care units. Resistance rapidly develops against two drugs of choice: ceftazidime and meropenem. Several therapeutic protocols were compared for reduction in viable cells and limiting development of resistance. Chemostat cultures were exposed to antibiotic concentrations measured in the blood of patients at low (5th percentile), medium (50th percentile) or high (95th percentile) levels in several therapy protocols to simulate therapy. Cultures exposed to ceftazidime recovered after 1 day at low, 2 days at medium and 3 days at high concentrations and developed corresponding levels of resistance. Patterns were very similar for meropenem except that recovery was delayed. Fluctuating levels and intermittent treatment achieved similar reduction of cell numbers at lower resistance costs. Treatment alternating ceftazidime and meropenem reduced cell numbers more than monotherapy, while strongly limiting resistance. Combination therapy was even more effective in both respects. Therapeutic goals are best reached with least risk of resistance when ceftazidime and meropenem are used in combination or alternating, at the highest concentrations the patient can endure. Monotherapy should also apply the highest concentration that is safe for the shortest time that achieves treatment objectives.

Antimicrobial Resistance in the Intensive Care Unit

Bacterial infections are a frequent cause of hospitalization, and nosocomial infections are an increasingly common condition, particularly within the acute/critical care setting. Infection control practices and new antimicrobial development have primarily focused on gram-positive bacteria; however, in recent years, the incidence of infections caused by gram-negative bacteria has risen considerably in intensive care units. Infections caused by multidrug-resistant (MDR) gram-negative organisms are associated with high morbidity and mortality, with significant direct and indirect costs resulting from prolonged hospitalizations due to antibiotic treatment failures. Of particular concern is the increasing prevalence of antimicrobial resistance to β-lactam antibiotics (including carbapenems) among Pseudomonas aeruginosa and Acinetobacter baumannii and, recently, among pathogens of the Enterobacteriaceae family. Treatment options for infections caused by these pathogens are limited. Antimicrobial stewardship programs focus on optimizing the appropriate use of currently available antimicrobial agents with the goals of improving outcomes for patients with infections caused by MDR gram-negative organisms, slowing the progression of antimicrobial resistance, and reducing hospital costs. Newly approved treatment options are available, such as β-lactam/β-lactamase inhibitor combinations, which significantly extend the armamentarium against MDR gram-negative bacteria.

Evaluation of a Mixing versus a Cycling Strategy of Antibiotic Use in Critically-Ill Medical Patients: Impact on Acquisition of Resistant Microorganisms and Clinical Outcomes

Objective

To compare the effect of two strategies of antibiotic use (mixing vs. cycling) on the acquisition of resistant microorganisms, infections and other clinical outcomes.

Methods

Prospective cohort study in an 8-bed intensive care unit during 35- months in which a mixing-cycling policy of antipseudomonal beta-lactams (meropenem, ceftazidime/piperacillin-tazobactam) and fluoroquinolones was operative. Nasopharyngeal and rectal swabs and respiratory secretions were obtained within 48h of admission and thrice weekly thereafter. Target microorganisms included methicillin-resistant S. aureus, vancomycin-resistant enterococci, third-generation cephalosporin-resistant Enterobacteriaceae and non-fermenters.

Results

A total of 409 (42%) patients were included in mixing and 560 (58%) in cycling. Exposure to ceftazidime/piperacillin-tazobactam and fluoroquinolones was significantly higher in mixing while exposure to meropenem was higher in cycling, although overall use of antipseudomonals was not significantly different (37.5/100 patient-days vs. 38.1/100 patient-days). There was a barely higher acquisition rate of microorganisms during mixing, but this difference lost its significance when the cases due to an exogenous Burkholderia cepacia outbreak were excluded (19.3% vs. 15.4%, OR 0.8, CI 0.5–1.1). Acquisition of Pseudomonas aeruginosa resistant to the intervention antibiotics or with multiple-drug resistance was similar. There were no significant differences between mixing and cycling in the proportion of patients acquiring any infection (16.6% vs. 14.5%, OR 0.9, CI 0.6–1.2), any infection due to target microorganisms (5.9% vs. 5.2%, OR 0.9, CI 0.5–1.5), length of stay (median 5 d for both groups) or mortality (13.9 vs. 14.3%, OR 1.03, CI 0.7–1.3).

Conclusions

A cycling strategy of antibiotic use with a 6-week cycle duration is similar to mixing in terms of acquisition of resistant microorganisms, infections, length of stay and mortality.

Fighting antibiotic resistance in the intensive care unit using antibiotics

Antibiotic resistance is a global and increasing problem that is not counterbalanced by the development of new therapeutic agents. The prevalence of antibiotic resistance is especially high in intensive care units with frequently reported outbreaks of multidrug-resistant organisms. In addition to classical infection prevention protocols and surveillance programs, counterintuitive interventions, such as selective decontamination with antibiotics and antibiotic rotation have been applied and investigated to control the emergence of antibiotic resistance. This review provides an overview of selective oropharyngeal and digestive tract decontamination, decolonization of methicillin-resistant Staphylococcus aureus and antibiotic rotation as strategies to modulate antibiotic resistance in the intensive care unit.

A Review of Quality Measures for Assessing the Impact of Antimicrobial Stewardship Programs in Hospitals

The growing problem of antimicrobial resistance (AMR) has led to calls for antimicrobial stewardship programs (ASP) to control antibiotic use in healthcare settings. Key strategies include prospective audit with feedback and intervention, and formulary restriction and preauthorization. Education, guidelines, clinical pathways, de-escalation, and intravenous to oral conversion are also part of some programs. Impact and quality of ASP can be assessed using process or outcome measures. Outcome measures are categorized as microbiological, patient or financial outcomes. The objective of this review was to provide an overview of quality measures for assessing ASP and the reported impact of ASP in peer-reviewed studies, focusing particularly on patient outcomes. A literature search of papers published in English between 1990 and June 2015 was conducted in five databases using a combination of search terms. Primary studies of any design were included. A total of 63 studies were included in this review. Four studies defined quality metrics for evaluating ASP. Twenty-one studies assessed the impact of ASP on antimicrobial utilization and cost, 25 studies evaluated impact on resistance patterns and/or rate of Clostridium difficile infection (CDI). Thirteen studies assessed impact on patient outcomes including mortality, length of stay (LOS) and readmission rates. Six of these 13 studies reported non-significant difference in mortality between pre- and post-ASP intervention, and five reported reductions in mortality rate. On LOS, six studies reported shorter LOS post intervention; a significant reduction was reported in one of these studies. Of note, this latter study reported significantly (p < 0.001) higher unplanned readmissions related to infections post-ASP. Patient outcomes need to be a key component of ASP evaluation. The choice of metrics is influenced by data and resource availability. Controlling for confounders must be considered in the design of evaluation studies to adequately capture the impact of ASP and it is important for unintended consequences to be considered. This review provides a starting point toward compiling standard outcome metrics for assessing ASP.

Temporal variation in antibiotic environments slows down resistance evolution in pathogenic Pseudomonas aeruginosa

Antibiotic resistance is a growing concern to public health. New treatment strategies may alleviate the situation by slowing down the evolution of resistance. Here, we evaluated sequential treatment protocols using two fully independent laboratory-controlled evolution experiments with the human pathogen Pseudomonas aeruginosa PA14 and two pairs of clinically relevant antibiotics (doripenem/ciprofloxacin and cefsulodin/gentamicin). Our results consistently show that the sequential application of two antibiotics decelerates resistance evolution relative to monotherapy. Sequential treatment enhanced population extinction although we applied antibiotics at sublethal dosage. In both experiments, we identified an order effect of the antibiotics used in the sequential protocol, leading to significant variation in the long-term efficacy of the tested protocols. These variations appear to be caused by asymmetric evolutionary constraints, whereby adaptation to one drug slowed down adaptation to the other drug, but not vice versa. An understanding of such asymmetric constraints may help future development of evolutionary robust treatments against infectious disease.

Antibiotic stewardship programmes in intensive care units: Why, how, and where are they leading us

Antibiotic usage and increasing antimicrobial resistance (AMR) mount significant challenges to patient safety and management of the critically ill on intensive care units (ICU). Antibiotic stewardship programmes (ASPs) aim to optimise appropriate antibiotic treatment whilst minimising antibiotic resistance. Different models of ASP in intensive care setting, include “standard” control of antibiotic prescribing such as “de-escalation strategies”through to interventional approaches utilising biomarker-guided antibiotic prescribing. A systematic review of outcomes related studies for ASPs in an ICU setting was conducted. Forty three studies were identified from MEDLINE between 1996 and 2014. Of 34 non-protocolised studies, [1 randomised control trial (RCT), 22 observational and 11 case series], 29 (85%) were positive with respect to one or more outcome: These were the key outcome of reduced antibiotic use, or ICU length of stay, antibiotic resistance, or prescribing cost burden. Limitations of non-standard antibiotic initiation triggers, patient and antibiotic selection bias or baseline demographic variance were identified. All 9 protocolised studies were RCTs, of which 8 were procalcitonin (PCT) guided antibiotic stop/start interventions. Five studies addressed antibiotic escalation, 3 de-escalation and 1 addressed both. Six studies reported positive outcomes for reduced antibiotic use, ICU length of stay or antibiotic resistance. PCT based ASPs are effective as antibiotic-stop (de-escalation) triggers, but not as an escalation trigger alone. PCT has also been effective in reducing antibiotic usage without worsening morbidity or mortality in ventilator associated pulmonary infection. No study has demonstrated survival benefit of ASP. Ongoing challenges to infectious disease management, reported by the World Health Organisation global report 2014, are high AMR to newer antibiotics, and regional knowledge gaps in AMR surveillance. Improved AMR surveillance data, identifying core aspects of successful ASPs that are transferable, and further well-conducted trials will be necessary if ASPs are to be an effective platform for delivering desired patient outcomes and safety through best antibiotic policy.

Controlling resistant bacteria with a novel class of β-lactamase inhibitor peptides: from rational design to in vivo analyses

Peptide rational design was used here to guide the creation of two novel short β-lactamase inhibitors, here named dBLIP-1 and -2, with length of five amino acid residues. Molecular modeling associated with peptide synthesis improved bactericidal efficacy in addition to amoxicillin, ampicillin and cefotaxime. Docked structures were consistent with calorimetric analyses against bacterial β-lactamases. These two compounds were further tested in mice. Whereas commercial antibiotics alone failed to cure mice infected with Staphylococcus aureus and Escherichia coli expressing β-lactamases, infection was cleared when treated with antibiotics in combination with dBLIPs, clearly suggesting that peptides were able to neutralize bacterial resistance. Moreover, immunological assays were also performed showing that dBLIPs were unable to modify mammalian immune response in both models, reducing the risks of collateral effects. In summary, the unusual peptides here described provide leads to overcome β-lactamase-based resistance, a remarkable clinical challenge.

Antibiotic rotation strategies to reduce antimicrobial resistance in Gram-negative bacteria in European intensive care units: study protocol for a cluster-randomized crossover controlled trial

Background

Intensive care units (ICU) are epicenters for the emergence of antibiotic-resistant Gram-negative bacteria (ARGNB) because of high rates of antibiotic usage, rapid patient turnover, immunological susceptibility of acutely ill patients, and frequent contact between healthcare workers and patients, facilitating cross-transmission.

Antibiotic stewardship programs are considered important to reduce antibiotic resistance, but the effectiveness of strategies such as, for instance, antibiotic rotation, have not been determined rigorously. Interpretation of available studies on antibiotic rotation is hampered by heterogeneity in implemented strategies and suboptimal study designs. In this cluster-randomized, crossover trial the effects of two antibiotic rotation strategies, antibiotic mixing and cycling, on the prevalence of ARGNB in ICUs are determined. Antibiotic mixing aims to create maximum antibiotic heterogeneity, and cycling aims to create maximum antibiotic homogeneity during consecutive periods.

Methods/Design

This is an open cluster-randomized crossover study of mixing and cycling of antibiotics in eight ICUs in five European countries. During cycling (9 months) third- or fourth-generation cephalosporins, piperacillin-tazobactam and carbapenems will be rotated during consecutive 6-week periods as the primary empiric treatment in patients suspected of infection caused by Gram-negative bacteria. During mixing (9 months), the same antibiotics will be rotated for each consecutive antibiotic course. Both intervention periods will be preceded by a baseline period of 4 months. ICUs will be randomized to consecutively implement either the mixing and then cycling strategy, or vice versa. The primary outcome is the ICU prevalence of ARGNB, determined through monthly point-prevalence screening of oropharynx and perineum. Secondary outcomes are rates of acquisition of ARGNB, bacteremia and appropriateness of therapy, length of stay in the ICU and ICU mortality. Results will be adjusted for intracluster correlation, and patient- and ICU-level variables of case-mix and infection-prevention measures using advanced regression modeling.

Discussion

This trial will determine the effects of antibiotic mixing and cycling on the unit-wide prevalence of ARGNB in ICUs.

Trial registration

ClinicalTrials.gov NCT01293071 December 2010.

Cycling empirical antibiotic therapy in hospitals: meta-analysis and models

The rise of resistance together with the shortage of new broad-spectrum antibiotics underlines the urgency of optimizing the use of available drugs to minimize disease burden. Theoretical studies suggest that coordinating empirical usage of antibiotics in a hospital ward can contain the spread of resistance. However, theoretical and clinical studies came to different conclusions regarding the usefulness of rotating first-line therapy (cycling). Here, we performed a quantitative pathogen-specific meta-analysis of clinical studies comparing cycling to standard practice. We searched PubMed and Google Scholar and identified 46 clinical studies addressing the effect of cycling on nosocomial infections, of which 11 met our selection criteria. We employed a method for multivariate meta-analysis using incidence rates as endpoints and find that cycling reduced the incidence rate/1000 patient days of both total infections by 4.95 [9.43–0.48] and resistant infections by 7.2 [14.00–0.44]. This positive effect was observed in most pathogens despite a large variance between individual species. Our findings remain robust in uni- and multivariate metaregressions. We used theoretical models that reflect various infections and hospital settings to compare cycling to random assignment to different drugs (mixing). We make the realistic assumption that therapy is changed when first line treatment is ineffective, which we call “adjustable cycling/mixing”. In concordance with earlier theoretical studies, we find that in strict regimens, cycling is detrimental. However, in adjustable regimens single resistance is suppressed and cycling is successful in most settings. Both a meta-regression and our theoretical model indicate that “adjustable cycling” is especially useful to suppress emergence of multiple resistance. While our model predicts that cycling periods of one month perform well, we expect that too long cycling periods are detrimental. Our results suggest that “adjustable cycling” suppresses multiple resistance and warrants further investigations that allow comparing various diseases and hospital settings.

The rise of antibiotic resistance is a major concern for public health. In hospitals, frequent usage of antibiotics leads to high resistance levels; at the same time the patients are especially vulnerable. We therefore urgently need treatment strategies that limit resistance without compromising patient care. Here, we investigate two strategies that coordinate the usage of different antibiotics in a hospital ward: “cycling”, i.e. scheduled changes in antibiotic treatment for all patients, and “mixing”, i.e. random assignment of patients to antibiotics. Previously, theoretical and clinical studies came to different conclusions regarding the usefulness of these strategies. We combine meta-analyses of clinical studies and epidemiological modeling to address this question. Our meta-analyses suggest that cycling is beneficial in reducing the total incidence rate of hospital-acquired infections as well as the incidence rate of resistant infections, and that this is most pronounced at low baseline levels of resistance. We corroborate our findings with theoretical epidemiological models. When incorporating treatment adjustment upon deterioration of a patient's condition (“adjustable cycling”), we find that our theoretical model is in excellent accordance with the clinical data. With this combined approach we present substantial evidence that adjustable cycling can be beneficial for suppressing the emergence of multiple resistance.

Use of collateral sensitivity networks to design drug cycling protocols that avoid resistance development

New drug deployment strategies are imperative to address the problem of drug resistance, which is limiting the management of infectious diseases and cancers. We evolved resistance in Escherichia coli toward 23 drugs used clinically for treating bacterial infections and mapped the resulting collateral sensitivity and resistance profiles, revealing a complex collateral sensitivity network. On the basis of these data, we propose a new treatment framework--collateral sensitivity cycling--in which drugs with compatible collateral sensitivity profiles are used sequentially to treat infection and select against drug resistance development. We identified hundreds of such drug sets and demonstrated that the antibiotics gentamicin and cefuroxime can be deployed cyclically such that the treatment regimen selected against resistance to either drug. We then validated our findings with related bacterial pathogens. These results provide proof of principle for collateral sensitivity cycling as a sustainable treatment paradigm that may be generally applicable to infectious diseases and cancer.

Of stewardship, motherhood and apple pie

Antibiotic stewardship is universally agreed to be desirable, but optimal models for stewardship remain uncertain. UK stewardship targets the particular antibiotic families-cephalosporins and fluoroquinolones-blamed for the selection of Clostridium-difficile-associated disease. To balance this there have been dramatic increases in the use of penicillin-β-lactamase inhibitor combinations. By channelling selection pressure in this way, we hazard destroying the utility of these antibiotic classes in turn, as happened with gonorrhoea where penicillins, fluoroquinolones and cefixime were sequentially lost as therapies. Strikingly, in context, almost all carbapenemase-producers are highly resistant to penicillin-β-lactamase inhibitor combinations, which may select for them. There is an urgent need to explore an alternative stewardship model, seeking to limit total antibiotic use but to maintain heterogeneity in what is used, avoiding concentrated selection pressure. There is also a great need to improve and accelerate diagnostics for infection and resistance, reducing or removing the need for protracted empirical treatment with broad-spectrum agents.

Strategies to minimize antibiotic resistance

Antibiotic resistance can be reduced by using antibiotics prudently based on guidelines of antimicrobial stewardship programs (ASPs) and various data such as pharmacokinetic (PK) and pharmacodynamic (PD) properties of antibiotics, diagnostic testing, antimicrobial susceptibility testing (AST), clinical response, and effects on the microbiota, as well as by new antibiotic developments. The controlled use of antibiotics in food animals is another cornerstone among efforts to reduce antibiotic resistance. All major resistance-control strategies recommend education for patients, children (e.g., through schools and day care), the public, and relevant healthcare professionals (e.g., primary-care physicians, pharmacists, and medical students) regarding unique features of bacterial infections and antibiotics, prudent antibiotic prescribing as a positive construct, and personal hygiene (e.g., handwashing). The problem of antibiotic resistance can be minimized only by concerted efforts of all members of society for ensuring the continued efficiency of antibiotics.

Designing antibiotic cycling strategies by determining and understanding local adaptive landscapes

The evolution of antibiotic resistance among bacteria threatens our continued ability to treat infectious diseases. The need for sustainable strategies to cure bacterial infections has never been greater. So far, all attempts to restore susceptibility after resistance has arisen have been unsuccessful, including restrictions on prescribing [1] and antibiotic cycling [2], [3]. Part of the problem may be that those efforts have implemented different classes of unrelated antibiotics, and relied on removal of resistance by random loss of resistance genes from bacterial populations (drift). Here, we show that alternating structurally similar antibiotics can restore susceptibility to antibiotics after resistance has evolved. We found that the resistance phenotypes conferred by variant alleles of the resistance gene encoding the TEM β-lactamase (bla_TEM) varied greatly among 15 different β-lactam antibiotics. We captured those differences by characterizing complete adaptive landscapes for the resistance alleles bla_TEM-50 and bla_TEM-85, each of which differs from its ancestor bla_TEM-1 by four mutations. We identified pathways through those landscapes where selection for increased resistance moved in a repeating cycle among a limited set of alleles as antibiotics were alternated. Our results showed that susceptibility to antibiotics can be sustainably renewed by cycling structurally similar antibiotics. We anticipate that these results may provide a conceptual framework for managing antibiotic resistance. This approach may also guide sustainable cycling of the drugs used to treat malaria and HIV.

The ecology of antibiotic use in the ICU: homogeneous prescribing of cefepime but not tazocin selects for antibiotic resistant infection

Background

Antibiotic homogeneity is thought to drive resistance but in vivo data are lacking. In this study, we determined the impact of antibiotic homogeneity per se, and of cefepime versus antipseudomonal penicillin/β-lactamase inhibitor combinations (APP-β), on the likelihood of infection or colonisation with antibiotic resistant bacteria and/or two commonly resistant nosocomial pathogens (methicillin-resistant Staphylococcus aureus and Pseudomonas aeruginosa). A secondary question was whether antibiotic cycling was associated with adverse outcomes including mortality, length of stay, and antibiotic resistance.

Methods

We evaluated clinical and microbiological outcomes in two similar metropolitan ICUs, which both alternated cefepime with APP-β in four-month cycles. All microbiological isolates and commensal samples were analysed for the presence of antibiotic-resistant bacteria including MRSA and P. aeruginosa.

Results

Length of stay, mortality and overall antibiotic resistance were unchanged after sixteen months. However, increased colonisation and infection by antibiotic-resistant bacteria were observed in cefepime cycles, returning to baseline in APP-β cycles. Cefepime was the strongest risk factor for acquisition of antibiotic-resistant infection.

Conclusions

Ecological effects of different β-lactam antibiotics may be more important than specific activity against the causative agents or the effect of antibiotic homogeneity in selection for antibiotic resistance. This has important implications for antibiotic policy.