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Review
. 2023 Sep 12;12(1):100.
doi: 10.1186/s13756-023-01302-3.

Usefulness of dynamic regression time series models for studying the relationship between antimicrobial consumption and bacterial antimicrobial resistance in hospitals: a systematic review

Paul Laffont-Lozes  1   2 , Romaric Larcher  3   4   5 , Florian Salipante  6 , Geraldine Leguelinel-Blache  1   6 , Catherine Dunyach-Remy  7   8 , Jean-Philippe Lavigne  7   8 , Albert Sotto  2   8 , Paul Loubet  2   8
Affiliations
Review

Usefulness of dynamic regression time series models for studying the relationship between antimicrobial consumption and bacterial antimicrobial resistance in hospitals: a systematic review

Paul Laffont-Lozes et al. Antimicrob Resist Infect Control. .

Erratum in

Abstract

Backgroung: Antimicrobial resistance (AMR) is on the rise worldwide. Tools such as dynamic regression (DR) models can correlate antimicrobial consumption (AMC) with AMR and predict future trends to help implement antimicrobial stewardship programs (ASPs).

Main body: We carried out a systematic review of the literature up to 2023/05/31, searching in PubMed, ScienceDirect and Web of Science. We screened 641 articles and finally included 28 studies using a DR model to study the correlation between AMC and AMR at a hospital scale, published in English or French. Country, bacterial species, type of sampling, antimicrobials, study duration and correlations between AMC and AMR were collected. The use of β-lactams was correlated with cephalosporin resistance, especially in Pseudomonas aeruginosa and Enterobacterales. Carbapenem consumption was correlated with carbapenem resistance, particularly in Pseudomonas aeruginosa, Klebsiella pneumoniae and Acinetobacter baumannii. Fluoroquinolone use was correlated with fluoroquinolone resistance in Gram-negative bacilli and methicillin resistance in Staphylococcus aureus. Multivariate DR models highlited that AMC explained from 19 to 96% of AMR variation, with a lag time between AMC and AMR variation of 2 to 4 months. Few studies have investigated the predictive capacity of DR models, which appear to be limited.

Conclusion: Despite their statistical robustness, DR models are not widely used. They confirmed the important role of fluoroquinolones, cephalosporins and carbapenems in the emergence of AMR. However, further studies are needed to assess their predictive capacity and usefulness for ASPs.

Keywords: Antimicrobial; Dynamic regression; Healthcare-associated infections; Resistance; Time series analysis.

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Conflict of interest statement

PLL has received support for attending meetings and/or travel from Shionogi. PL has received payment or honoraria for lectures, presentations, speakers’ bureaus, or educational events from AstraZeneca, GSK, Janssen, MSD, Moderna, Pfizer, Sanofi Pasteur, and support for attending meetings and/or travel from AstraZeneca, Pfizer, and Sanofi Pasteur. AS has received consulting fees from Besins Healthcare and Karo Pharma, support for attending meetings and/or travel from Pfizer and MSD and participates free of charge on advisory boards of Biofilm Control and CTX Laboratory. RL has received consulting fees from MSD, payment or honoraria for lectures, presentations, speakers’ bureaus, or educational events from BioM?rieux, MSD, Pfizer and Shionogi, and support for attending meetings and/or travel from BioM?rieux, Roche Diagnostics, MSD, Pfizer and Shionogi. All other authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Study selection flow chart
Fig. 2
Fig. 2
Risk of bias assessment in the overall studies
Fig. 3
Fig. 3
Risk of bias per study
See this image and copyright information in PMC

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