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

Correlation between Antimicrobial Resistance and the Hospital-Wide Diverse Use of Broad-Spectrum Antibiotics by the Antimicrobial Stewardship Program in Japan

Increased antibiotic use and antibiotic homogeneity cause selective pressure. This study investigated the correlation between antibiotic diversity and antimicrobial resistance (AMR) in Gram-negative organisms. The days of therapy/100 patient-days (DOT) for four broad-spectrum antibiotic classes were evaluated for 2015-2022. The antibiotic heterogeneity index (AHI) for the equal use of four classes (25%) and the modified AHI for the equal use of three classes (30%), excluding fluoroquinolones (10%), were measured (target: 1.0). Quarterly antibiotic use markers and the resistance rates against ≥2 anti-Pseudomonas antibiotics were compared. The DOT value was 9.94, and the relative DOT were 34.8% for carbapenems, 32.1% for piperacillin/tazobactam, 24.3% for fourth generation cephalosporins/ceftazidime/aztreonam, and 8.9% for fluoroquinolones. Although no correlation was found between the total DOT and the resistance rate for any bacterium, a significant negative correlation was found between the heterogeneity indices and resistance rates for Pseudomonas aeruginosa and Klebsiella pneumoniae. The significant cutoffs that discriminate the risk of resistance were 0.756 for the AHI and 0.889 for the modified AHI for K. pneumoniae. Antibiotic diversity is more important in preventing AMR than overall antibiotic use. The ideal ratio of broad-spectrum antibiotics should be studied for diversified use to prevent AMR.

Comparing optimization criteria in antibiotic allocation protocols

Clinicians prescribing antibiotics in a hospital context follow one of several possible 'treatment protocols'-heuristic rules designed to balance the immediate needs of patients against the long-term threat posed by the evolution of antibiotic resistance and multi-resistant bacteria. Several criteria have been proposed for assessing these protocols; unfortunately, these criteria frequently conflict with one another, each providing a different recommendation as to which treatment protocol is best. Here, we review and compare these optimization criteria. We are able to demonstrate that criteria focused primarily on slowing evolution of resistance are directly antagonistic to patient health both in the short and long term. We provide a new optimization criteria of our own, intended to more meaningfully balance the needs of the future and present. Asymptotic methods allow us to evaluate this criteria and provide insights not readily available through the numerical methods used previously in the literature. When cycling antibiotics, we find an antibiotic switching time which proves close to optimal across a wide range of modelling assumptions.

Systematic Study on a Quantitative Analysis of Multicomponents by Single Marker (QAMS) Method for Simultaneous Determination of Eight Constituents in Pneumonia Mixture by UPLC-MS/MS

Pneumonia mixture was formulated and is available to treat children acute pneumonia and acute bronchitis in our hospital for nearly forty years, but there are few studies of its quality evaluation or control. In this paper, a new strategy for quality evaluation of pneumonia mixture was explored and verified through qualitative and quantitative analyses of multicomponents by single marker (QAMS) by UPLC-MS/MS. Baicalein was selected as an internal reference, and the relative correction factors (RCFs) and the relative retention time (RRT) of (R, S)-goitrin, amygdalin, chlorogenic acid, pseudoephedrine hydrochloride, ephedrine hydrochloride, ammonium glycyrrhizinate, and baicalin were established. The robustness and durability of the QAMS method were investigated. RCF values calculated by the average (AVG) method and linear regression (LRG) method had good repeatability and were acceptable for quantitative analysis, and the RTT combined with the exact masses of precursor and fragment ions and their abundance could be adopted for accurately positioning the chromatographic peak of the eight constituents. The consistency and feasibility of the QAMS method were verified by comparing the contents of the seven components calculated by a classic and validated external standard method (ESM) with those of the QAMS method, which reduces analytical cost and time of detection and avoids the problem of the diversity and large quantity of reference standards. The results demonstrated that the QAMS method developed in this paper could provide a new, alternative, and promising method to comprehensively and effectively determine multicomponents and control the quality of pneumonia mixture or even a group of similar medicines.

Systematic review of the effects of antimicrobial cycling on bacterial resistance rates within hospital settings

AIMS

Antimicrobial resistance is an evolving phenomenon with alarming public health consequences. Antibiotic cycling is a widely known antimicrobial stewardship initiative that encompasses periodical shifts in empirical treatment protocols with the aim of limiting selective pressures on bacterial populations. We present a review of the evidence regarding the actual impact of antimicrobial cycling on bacterial resistance control within hospitals.

METHODS

A systematic literature review was conducted using the PubMed/MedLine, Embase, CINAHL Plus and Global Health databases.

RESULTS

A systematic search process retrieved a sole randomised study, and so we broadened inclusion criteria to encompass quasi-experimental designs. Fifteen studies formed our dataset including seven prospective trials and eight before-and-after studies. Nine studies evaluated cycling vs. a control group and produced conflicting results whilst three studies compared cycling with antibiotic mixing, with none of the strategies appearing superior. The rest evaluated resistance dynamics of each of the on-cycle antibiotics with contradictory findings. Research protocols differed in parameters such as the cycle length, the choice of antibiotics, the opportunity to de-escalate to narrow-spectrum agents and the measurement of indicators of collateral damage. This limited our ability to evaluate the replicability of findings and the overall policy effects.

CONCLUSION

Dearth of robust designs and standardised protocols limits our ability to reach safe conclusions. Nonetheless, in view of the available data we find no reason to believe that cycling should be expected to improve antibiotic resistance rates within hospitals.

A game theoretic approach reveals that discretizing clinical information can reduce antibiotic misuse

The overuse of antibiotics is exacerbating the antibiotic resistance crisis. Since this problem is a classic common-goods dilemma, it naturally lends itself to a game-theoretic analysis. Hence, we designed a model wherein physicians weigh whether antibiotics should be prescribed, given that antibiotic usage depletes its future effectiveness. The physicians' decisions rely on the probability of a bacterial infection before definitive laboratory results are available. We show that the physicians' equilibrium decision rule of antibiotic prescription is not socially optimal. However, we prove that discretizing the information provided to physicians can mitigate the gap between their equilibrium decisions and the social optimum of antibiotic prescription. Despite this problem's complexity, the effectiveness of the discretization solely depends on the type of information available to the physician to determine the nature of infection. This is demonstrated on theoretic distributions and a clinical dataset. Our results provide a game-theory based guide for optimal output of current and future decision support systems of antibiotic prescription.