Benefits and unintended consequences of antimicrobial de-escalation: Implications for stewardship programs

An agent-based model on antimicrobial de-escalation in intensive care units: Implications on clinical trial design

Antimicrobial de-escalation refers to reducing the spectrum of antibiotics used in treating bacterial infections. This strategy is widely recommended in many antimicrobial stewardship programs and is believed to reduce patients' exposure to broad-spectrum antibiotics and prevent resistance. However, the ecological benefits of de-escalation have not been universally observed in clinical studies. This paper conducts computer simulations to assess the ecological effects of de-escalation on the resistance prevalence of Pseudomonas aeruginosa-a frequent pathogen causing nosocomial infections. Synthetic data produced by the models are then used to estimate the sample size and study period needed to observe the predicted effects in clinical trials. Our results show that de-escalation can reduce colonization and infections caused by bacterial strains resistant to the empiric antibiotic, limit the use of broad-spectrum antibiotics, and avoid inappropriate empiric therapies. Further, we show that de-escalation could reduce the overall super-infection incidence, and this benefit becomes more evident under good compliance with hand hygiene protocols among health care workers. Finally, we find that any clinical study aiming to observe the essential effects of de-escalation should involve at least ten arms and last for four years-a size never attained in prior studies. This study explains the controversial findings of de-escalation in previous clinical studies and illustrates how mathematical models can inform outcome expectations and guide the design of clinical studies.

A stochastic dynamical model for nosocomial infections with co-circulation of sensitive and resistant bacterial strains

Nosocomial infections (hospital-acquired) has been an important public health problem, which may make those patients with infections or involved visitors and hospital personnel at higher risk of worse clinical outcomes or infection, and then consume more healthcare resources. Taking into account the stochasticity of the death and discharge rate of patients staying in hospitals, in this paper, we propose a stochastic dynamical model describing the transmission of nosocomial pathogens among patients admitted for hospital stays. The stochastic terms of the model are incorporated to capture the randomness arising from death and discharge processes of patients. Firstly, a sufficient condition is established for the stochastic extinction of disease. It shows that introducing randomness in the model will result in lower potential of nosocomial outbreaks. Further, we establish a threshold criterion on the existence of stationary distribution and ergodicity for any positive solution of the model. Particularly, the spectral radius form of stochastic threshold value is calculated in the special case. Moreover, the numerical simulations are conducted to both validate the theoretical results and investigate the effect of prevention and control strategies on the prevalence of nosocomial infection. We show that enhancing hygiene, targeting colonized and infected patients, improving antibiotic treatment accuracy, shortening treatment periods are all crucial factors to contain nosocomial infections.

Modeling Antibiotic Use Strategies in Intensive Care Units: Comparing De-escalation and Continuation

Antimicrobial de-escalation refers to the treatment mechanism of switching from empiric antibiotics with good coverage to alternatives based on laboratory susceptibility test results, with the aim of avoiding unnecessary use of broad-spectrum antibiotics. In a previous study, we have developed multi-strain and multi-drug models in an intensive care unit setting, to evaluate the benefits and trade-offs of de-escalation in comparison with the conventional strategy called antimicrobial continuation. Our simulation results indicated that for a large portion of credible parameter combinations, de-escalation reduces the use of the empiric antibiotic but increases the probabilities of colonization and infections. In this paper, we first simplify the previous models to compare the long-term dynamical behaviors between de-escalation and continuation systems under a two-strain scenario. The analytical results coincide with our previous findings in the complex models, indicating the benefits and unintended consequences of de-escalation strategy result from the nature of this treatment mechanism, not from the complexity of the high-dimensional systems. By extending the models to three-strain scenarios, we find that de-escalation is superior than continuation in preventing outbreaks of invading strains that are resistant to empiric antibiotics. Thus decisions on antibiotic use strategies should be made specifically according to ICU conditions and intervention objectives.

The Relative Impact of Community and Hospital Antibiotic Use on the Selection of Extended-spectrum Beta-lactamase-producing Escherichia coli

Antibiotic stewardship programs have traditionally focused on reducing hospital antibiotic use. However, reducing community antibiotic prescribing could have substantial impacts in both hospital and community settings. We developed a deterministic model of transmission of extended-spectrum beta-lactamase-producing Escherichia coli in both the community and hospitals. We fit the model to existing, national-level antibiotic use and resistance prevalence data from Sweden. Across a range of conditions, a given relative change in antibiotic use in the community had a greater impact on resistance prevalence in both the community and hospitals than an equivalent relative change in hospital use. However, on a per prescription basis, changes in antibiotic use in hospitals had the greatest impact. The magnitude of changes in prevalence were modest, even with large changes in antimicrobial use. These data support the expansion of stewardship programs/interventions beyond the walls of hospitals, but also suggest that such efforts would benefit hospitals themselves.

Positively interacting strains that co-circulate within a network structured population induce cycling epidemics of Mycoplasma pneumoniae

Mycoplasma pneumoniae (MP) is considered a common cause of pneumonia, causing about 15–20% of adult community-acquired pneumonia (CAP) and up to 40% of cases in children. It has often been observed that MP epidemics last approximately 1–2 years and occur every 3–7 years, with the dominant strains alternating between epidemics. However, the underlying mechanism by which these cycles and changes in the dominant strains occur remains unclear. The traditional models for the periodicity of MP epidemics neglected two phenomena: structured contact patterns among people and co-circulating strains of MP. We also believe that the two distinctive aspects of MP epidemics: prevalent serotype shifts among epidemics and incidence cycling of MP, are interconnected. We propose a network transmission model that assumes two strains of MP are transmitted within a network structured population and they can interact as secondary infections with primary infections. Our studies show that multiple strains that co-circulate within a network structured population and interact positively generate the observed patterns of recurrent epidemics of MP. Hence our study provides a possible mechanism for the cycling epidemics of MP, and could provide useful information for future vaccine design and vaccine evaluation/monitoring processes.

The GISA call to action for the appropriate use of antimicrobials and the control of antimicrobial resistance in Italy

The spread of antibiotic resistance is one of the leading public health problems in Italy. A European Centre for Disease Prevention and Control country visit recently confirmed the major challenges and made important suggestions. In response, the Ministry of Health published the National Plan for Antimicrobial Resistance Containment, and a group of experts belonging to the Italian Group of Antimicrobial Stewardship (GISA) convened to develop a summary of practical recommendations. The GISA document is intended for use by practising physicians; it aims to increase the rational use of antimicrobials in the treatment of infections, and to change the culture of infection control of antibiotic-resistant bacteria, through the translation of theoretical knowledge into priority actions. This document has been endorsed by several national scientific societies, and reflects the particular challenges that are faced in Italy. Nevertheless, it is considered that the general principles and approaches discussed are relevant, particularly to other developed economies.

Effects of Clinically Meaningful Concentrations of Antipseudomonal β-Lactams on Time to Detection and Organism Growth in Blood Culture Bottles

The effectiveness of antimicrobial binding resins present in blood culture (BC) bottles in removing meropenem, ceftolozane-tazobactam, and ceftazidime-avibactam is unknown. We assessed the time to detection (TTD) and growth of 2 Pseudomonas aeruginosa isolates in the presence of clinically meaningful concentrations of these antibiotics. Bactec Plus Aerobic/F and BacT/Alert FA Plus BC bottles were inoculated with one of two isolates (1 meropenem susceptible and 1 resistant), followed by fresh whole blood containing the peak, midpoint, or trough plasma concentrations for meropenem, ceftolozane-tazobactam, and ceftazidime-avibactam. Matching bottles were loaded into their respective detection instruments and a standard incubator at 37°C, with TTD and CFU being monitored for up to 72 h. Bacterial growth was observed for 11/48 (22.9%), 22/48 (45.8%), and 47/48 (97.9%) of all BC bottles inoculated with the peak, midpoint, and trough concentrations, respectively (P ≤ 0.001). When P. aeruginosa was isolated, the TTD was typically <26 h, and no differences between Bactec and BacT/Alert bottles were observed. In both systems, meropenem was removed to a greater degree than were ceftolozane and ceftazidime; however, concentrations for all antibiotics remained above the MIC for the susceptible organisms at 12 h. BC bottles containing antibiotic binding resins may not sufficiently inactivate achievable concentrations of meropenem, ceftolozane-tazobactam, and ceftazidime-avibactam. The consistent identification of both P. aeruginosa isolates was observed only in the presence of antibiotic trough concentrations. To minimize false-negative BC results for patients already receiving these antibiotics, cultures should be collected just prior to the next dose, when antibiotic concentrations are lowest.