Systematic analysis of the relationship between antibiotic use and extended-spectrum beta-lactamase resistance in Enterobacteriaceae in a French hospital: a time series analysis

2015 ◽  
Vol 34 (10) ◽  
pp. 1957-1963 ◽  
Author(s):  
M.-A. Vibet ◽  
J. Roux ◽  
E. Montassier ◽  
S. Corvec ◽  
M.-E. Juvin ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Antibiotic Use ◽  
Beta Lactamase ◽  
Systematic Analysis ◽  
Extended Spectrum Beta Lactamase ◽  
Series Analysis ◽  
Extended Spectrum ◽  
French Hospital ◽  
The Relationship

scholarly journals Quantifying antibiotic impact on within-patient dynamics of extended-spectrum beta-lactamase resistance

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Rene Niehus ◽  
Esther van Kleef ◽  
Yin Mo ◽  
Agata Turlej-Rogacka ◽  
Christine Lammens ◽  
...  
Keyword(s):  
Bacterial Load ◽  
Antibiotic Use ◽  
Beta Lactamase ◽  
Long Term Effects ◽  
Human Gut ◽  
Extended Spectrum Beta Lactamase ◽  
Extended Spectrum ◽  
Oral Ciprofloxacin ◽  
The Relationship

Antibiotic-induced perturbation of the human gut flora is expected to play an important role in mediating the relationship between antibiotic use and the population prevalence of antibiotic resistance in bacteria, but little is known about how antibiotics affect within-host resistance dynamics. Here we develop a data-driven model of the within-host dynamics of extended-spectrum beta-lactamase (ESBL) producing Enterobacteriaceae. We use blaCTX-M (the most widespread ESBL gene family) and 16S rRNA (a proxy for bacterial load) abundance data from 833 rectal swabs from 133 ESBL-positive patients followed up in a prospective cohort study in three European hospitals. We find that cefuroxime and ceftriaxone are associated with increased blaCTX-M abundance during treatment (21% and 10% daily increase, respectively), while treatment with meropenem, piperacillin-tazobactam, and oral ciprofloxacin is associated with decreased blaCTX-M (8% daily decrease for all). The model predicts that typical antibiotic exposures can have substantial long-term effects on blaCTX-M carriage duration.

scholarly journals Impact of Removal of Automatic 7-Day Stop Orders for Inpatient Antimicrobials

2020 ◽  
Vol 41 (S1) ◽  
pp. s264-s265
Author(s):  
Afia Adu-Gyamfi ◽  
Keith Hamilton ◽  
Leigh Cressman ◽  
Ebbing Lautenbach ◽  
Lauren Dutcher
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Treatment Interruptions ◽  
Days Of Therapy ◽  
Quasi Experimental ◽  
The Impact

Background: Automatic discontinuation of antimicrobial orders after a prespecified duration of therapy has been adopted as a strategy for reducing excess days of therapy (DOT) as part of antimicrobial stewardship efforts. Automatic stop orders have been shown to decrease antimicrobial DOT. However, inadvertent treatment interruptions may occur as a result, potentially contributing to adverse patient outcomes. To evaluate the effects of this practice, we examined the impact of the removal of an electronic 7-day ASO program on hospitalized patients. Methods: We performed a quasi-experimental study on inpatients in 3 acute-care academic hospitals. In the preintervention period (automatic stop orders present; January 1, 2016, to February 28, 2017), we had an electronic dashboard to identify and intervene on unintentionally missed doses. In the postintervention period (April 1, 2017, to March 31, 2018), the automatic stop orders were removed. We compared the primary outcome, DOT per 1,000 patient days (PD) per month, for patients in the automatic stop orders present and absent periods. The Wilcoxon rank-sum test was used to compare median monthly DOT/1,000 PD. Interrupted time series analysis (Prais-Winsten model) was used to compared trends in antibiotic DOT/1,000 PD and the immediate impact of the automatic stop order removal. Manual chart review on a subset of 300 patients, equally divided between the 2 periods, was performed to assess for unintentionally missed doses. Results: In the automatic stop order period, a monthly median of 644.5 antibiotic DOT/1,000 PD were administered, compared to 686.2 DOT/1,000 PD in the period without automatic stop orders (P < .001) (Fig. 1). Using interrupted time series analysis, there was a nonsignificant increase by 46.7 DOT/1,000 PD (95% CI, 40.8 to 134.3) in the month immediately following removal of automatic stop orders (P = .28) (Fig. 2). Even though the slope representing monthly change in DOT/1,000 PD increased in the period without automatic stop orders compared to the period with automatic stop orders, it was not statistically significant (P = .41). Manual chart abstraction revealed that in the period with automatic stop orders, 9 of 150 patients had 17 unintentionally missed days of therapy, whereas none (of 150 patients) in the period without automatic stop orders did. Conclusions: Following removal of the automatic stop orders, there was an overall increase in antibiotic use, although the change in monthly trend of antibiotic use was not significantly different. Even with a dashboard to identify missed doses, there was still a risk of unintentionally missed doses in the period with automatic stop orders. Therefore, this risk should be weighed against the modest difference in antibiotic utilization garnered from automatic stop orders.Funding: NoneDisclosures: None

scholarly journals 1089. Implementation of a Febrile Neutropenia Management Algorithm on Antibiotic Use and Outcomes: An Interrupted Time Series Analysis

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S386-S387
Author(s):  
Trang D Trinh ◽  
Luke Strnad ◽  
Lloyd E Damon ◽  
John H Dzundza ◽  
Larissa R Graff ◽  
...  
Keyword(s):  
Time Series ◽  
Febrile Neutropenia ◽  
Time Series Analysis ◽  
Clinical Outcomes ◽  
Interrupted Time Series ◽  
Antibiotic Use ◽  
Evidence Based ◽  
Interrupted Time Series Analysis ◽  
Series Analysis ◽  
Management Algorithm

Abstract Background Febrile neutropenia (FN) is a common complication of cancer therapy and often necessitates prolonged antibiotic treatment. Antibiotic de-escalation can be challenging given tenuous clinical status. Furthermore, a microbiological or clinical etiology is identified in a minority of FN patients. In 2016 we implemented several evidence-based strategies to guide antibiotic use in high-risk FN patients including specifying vancomycin use indications, minimizing carbapenem escalation in stable patients with ongoing fevers, and defining antibiotic durations regardless of neutrophil count. The study objective was to characterize and evaluate our experience implementing these strategies on antibiotic use and clinical outcomes. Methods Interrupted time series analysis of all admissions to the Malignant Hematology service at the University of California, San Francisco between June 2014 and December 2018. The primary outcome was monthly days of therapy (DOT) per 1,000 patient-days of broad-spectrum IV antibiotics (aztreonam, cefepime, piperacillin–tazobactam, meropenem, and vancomycin). Secondary outcomes included DOT/1,000 patient-days for each IV antibiotic, incidence rates of bloodstream infections (BSI) and C. difficile infections (CDI), and in-hospital all-cause mortality. A segmented regression analysis was conducted to evaluate the impact of the FN management algorithm implementation on antibiotic use and clinical outcomes. Summary statistics and time series scatter plots were used to visualize the trends and outliers. Results 2319 unique patients with 6,788 encounters were included. The median (IQR) age was 59 (46–68) years and 60% were male. Regression results and time series plots are shown in Table 1 and Figures 1–3. Conclusion Implementation of an evidence-based FN management algorithm led to decreased vancomycin and meropenem use without a statistically significant impact on overall antibiotic use, CDI rates, or mortality.While BSI rates fluctuated in the 2 months post-implementation, rates returned to baseline thereafter. A multidisciplinary effort facilitated successful implementation of this stewardship project. This collaboration remains essential to addressing future antimicrobial management strategies in this population. Disclosures All authors: No reported disclosures.

scholarly journals Market Response, Competitive Behavior, and Time Series Analysis

1980 ◽  
Vol 17 (4) ◽  
pp. 470-485 ◽  
Author(s):  
Dominique M. Hanssens
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Model Building ◽  
Competitive Reaction ◽  
Marketing Model ◽  
Series Analysis ◽  
Marketing Variables ◽  
Major Airlines ◽  
Market Variables ◽  
The Relationship

The author's principal objective is to present a framework for market analysis which specifically models primary demand, competitive reaction, and feedback effects of the market variables. The approach is an extension of earlier work by Clarke and by Lambin, Naert, and Bultez on the relationship among the elasticities of the marketing variables. The author develops this framework and formulates an approach for empirical applications based on principles of time series analysis. In particular, Granger's well-known causality definition is used in conjunction with Box-Jenkins analysis to find the nonzero elements in the marketing model. These principles are applied empirically to the case of a city pair of the U.S. domestic air travel market, where three major airlines compete on the basis of flight scheduling and advertising. The analysis reveals that flight scheduling has a market-expansive or a competitive effect, depending on the competitor, and that advertising does not have a significant impact on performance. In addition, several patterns of competitive reactions are found. The author offers observations on the theoretical and empirical aspects of this approach to marketing model building.

Impact of administrative restrictions on antibiotic use and expenditure in Ontario: time series analysis

2006 ◽  
Vol 11 (1) ◽  
pp. 13-20 ◽  
Author(s):  
Deborah Marshall ◽  
Jacqueline Gough ◽  
Paul Grootendorst ◽  
Melanie Buitendyk ◽  
Barbara Jaszewski ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Antibiotic Use ◽  
Series Analysis

Television and protest in East Germany’s revolution, 1989–1990: A mixed-methods analysis

2014 ◽  
Vol 47 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Marko Grdešić
Keyword(s):  
Time Series ◽  
Mixed Methods ◽  
Time Series Analysis ◽  
Qualitative Analysis ◽  
Event Data ◽  
Mixed Methods Approach ◽  
Series Analysis ◽  
East German ◽  
Television Coverage ◽  
The Relationship

This article uses a mixed-methods approach to analyze the relationship between television and protest during East Germany’s revolution. The content of television newscasts, both West German and East German, is analyzed together with protest event data. There are two key findings. First, West German coverage of protests is associated with an increase in protest in the first phase of the revolution. This finding emerges from time series analysis. Second, West German and East German television coverage were interacting, with the latter reacting to the former. This finding emerges from both quantitative and qualitative analysis.

Sign in / Sign up

Export Citation Format

Share Document