Antimicrobial consumption in an acute NHS Trust during the COVID-19 pandemic: intervention time series analysis.

Objective: To determine the impact of the COVID-19 pandemic on antimicrobial consumption and trends of therapeutic drugs for COVID-19 treatments, including corticosteroids, remdesivir and monoclonal antibodies (tocilizumab) from April 2017 to September 2022 in a secondary care NHS Trust in England. Methods: A retrospective intervention time series analysis was conducted for April 2017 to September 2022 at the Mid Yorkshire Teaching NHS Trust. Data were retrieved from the pharmacy dispensing system as defined daily doses (DDDs) monthly and reported per 1000 occupied bed days (OBDs). Antimicrobial consumption and COVID-19 treatment options were measured. DDDs were calculated according to the classification of antimicrobials for systemic use (J01) and for other drugs classification. Trends for antimicrobial consumption and other therapeutic drugs for treating COVID-19 were also determined in each wave in England. Results: During the pandemic: total antibiotic consumption decreased from 826.4 to 728.2 DDDs per 1000 OBDs (P = 0.0067); piperacillin/tazobactam use increased (P < 0.0001) and ciprofloxacin use decreased (P < 0.0001); there were no changes in Access, Watch, Reserve antibiotic use, and the proportion of antifungal consumption was consistent throughout the study. The use of total antibiotics (P = 0.024), levofloxacin (P = 0.0007), piperacillin/tazobactam (P = 0.0015) and co-amoxiclav (P = 0.0198) increased during wave one. Consumption of COVID-19 treatment drugs was highest during wave two, with 624.3 DDDs per 1000 OBDs for dexamethasone (P = 0.4441), 6.8 DDDs per 1000 OBDs for remdesivir (P < 0.0001) and 35.01 DDDs per 1000 OBDs for tocilizumab (P = 0.2544). Discussion: This study determined the consumption of antimicrobials trends before and during the pandemic. The individual wave antimicrobial consumption indicates maximum consumption in the first wave, advocating for antimicrobial stewardship and preparedness for future pandemics.

Identification of antibiotic consumption targets for the management of Clostridioides difficile infection in hospitals- a threshold logistic modelling approach.

BACKGROUND: This study aims to demonstrate the utility of a threshold logistic approach to identifying thresholds for specific antibiotic use associated with Clostridioides difficile infection (CDI) in an English teaching hospital. METHODS: A combined approach of nonlinear modeling and logistic regression, named threshold logistic, was used to identify thresholds and risk scores in hospital-level antibiotic use associated with hospital-onset, healthcare-associated (HOHA) CDI cases. RESULTS: Using a threshold logistic regression approach, an incidence greater than 0.2645 cases/1000 occupied bed-days (OBD; 85th percentile) was determined as the cutoff rate to define a critical (high) incidence rate of HOHA CDI. Fluoroquinolones and piperacillin-tazobactam were found to have thresholds at 84.8 and 54 defined daily doses (DDD)/1000 OBD, respectively. Analysis of data allowed calculating risk scores for HOHA CDI incidence rates exceeding the 85th percentile, i.e. entering critical incidence level. The threshold-logistic model also facilitated performing 'what-if scenarios' on future values of fluoroquinolones and piperacillin-tazobactam use to understand how HOHA CDI incidence rates may be affected. CONCLUSION: Using threshold logistic analysis, critical incidence levels and antibiotic use targets to control HOHA CDI were determined. Threshold logistic models can be used to inform and enhance the effective design and implementation of antimicrobial stewardship programs.

A Threshold Logistic Modelling Approach for Identifying Thresholds between Antibiotic Use and Methicillin-Resistant Staphylococcus aureus Incidence Rates in Hospitals.

The aim of this study was to demonstrate the utility of threshold logistic modelling, an innovative approach in identifying thresholds and risk scores in the context of population antibiotic use associated with methicillin-resistant Staphylococcus aureus (MRSA) incidence rates in hospitals. The study also aimed to assess the impact of exceeding those thresholds that resulted in increased MRSA rates. The study was undertaken in a 700-bed hospital in England between January 2015 and December 2021 (84 monthly observations). By employing the threshold logistic modelling approach, we: (i) determined the cut-off percentile value of MRSA incidence that defines a critical level of MRSA; (ii) identified thresholds for fluoroquinolone and co-amoxiclav use that would accelerate MRSA incidence rates and increase the probability of reaching critical incidence levels; (iii) enabled a better understanding of the effect of antibiotic use on the probability of reaching a critical level of resistant pathogen incidence; (iv) developed a near real-time performance monitoring feedback system; (v) provided risk scores and alert signals for antibiotic use, with the ability to inform hospital policies, and control MRSA incidence; and (vi) provided recommendations and an example for the management of pathogen incidence in hospitals. Threshold logistic models can help hospitals determine quantitative targets for antibiotic usage and can also inform effective antimicrobial stewardship to control resistance in hospitals. Studies should work toward implementing and evaluating the proposed approach prospectively, with the aim of determining the best counter-measures to mitigate the risk of increased resistant pathogen incidence in hospitals.

Identifying Antibiotic Use Targets for the Management of Antibiotic Resistance Using an Extended-Spectrum ß-Lactamase-Producing Escherichia coli Case: A Threshold Logistic Modeling Approach.

The aim of this study was to develop a logistic modeling concept to improve understanding of the relationship between antibiotic use thresholds and the incidence of resistant pathogens. A combined approach of nonlinear modeling and logistic regression, named threshold logistic, was used to identify thresholds and risk scores in hospital-level antibiotic use associated with hospital-level incidence rates of extended-spectrum ß-lactamase (ESBL)-producing Escherichia coli (E. coli). Threshold logistic models identified thresholds for fluoroquinolones (61.1 DDD/1000 occupied bed days (OBD)) and third-generation cephalosporins (9.2 DDD/1000 OBD) to control hospital ESBL-producing E. coli incidence. The 60th percentile of ESBL-producing E. coli was determined as the cutoff for defining high incidence rates. Threshold logistic analysis showed that for every one-unit increase in fluoroquinolones and third-generation cephalosporins above 61.1 and 9.2 DDD/1000 OBD levels, the average odds of the ESBL-producing E. coli incidence rate being ≥60th percentile of historical levels increased by 4.5% and 12%, respectively. Threshold logistic models estimated the risk scores of exceeding the 60th percentile of a historical ESBL-producing E. coli incidence rate. Threshold logistic models can help hospitals in defining critical levels of antibiotic use and resistant pathogen incidence and provide targets for antibiotic consumption and a near real-time performance monitoring feedback system.