Usefulness of dynamic regression time series models for studying the relationship between antimicrobial consumption and bacterial antimicrobial resistance in hospitals: a systematic review.
Antimicrobial
Dynamic regression
Healthcare-associated infections
Resistance
Time series analysis
Journal
Antimicrobial resistance and infection control
ISSN: 2047-2994
Titre abrégé: Antimicrob Resist Infect Control
Pays: England
ID NLM: 101585411
Informations de publication
Date de publication:
12 09 2023
12 09 2023
Historique:
received:
19
07
2023
accepted:
30
08
2023
medline:
13
9
2023
pubmed:
12
9
2023
entrez:
11
9
2023
Statut:
epublish
Résumé
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). 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. 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.
Identifiants
pubmed: 37697357
doi: 10.1186/s13756-023-01302-3
pii: 10.1186/s13756-023-01302-3
pmc: PMC10496333
doi:
Substances chimiques
Anti-Bacterial Agents
0
Anti-Infective Agents
0
Carbapenems
0
Fluoroquinolones
0
Types de publication
Systematic Review
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
100Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
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