Effect of antimicrobial consumption on Escherichia coli resistance: assessment and forecasting using Dynamic Regression models in a French university hospital (2014-2019)

Laffont-Lozes, Paul; Salipante, Florian; Leguelinel-Blache, Géraldine; Dunyach-Rémy, Catherine; Lavigne, Jean‐Philippe; Sotto, Albert; Larcher, Romaric

doi:10.1016/j.ijantimicag.2023.106768

Cited by 1 publication

(17 citation statements)

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“…A further 17 articles were excluded after analysis for statistical issues (including 11 studies using ARIMA model and cross-correlation analysis without DR, and one study in which DR use was not confirmed despite attempts to contact the authors). Finally, 28 studies [ 8 , 13 – 15 , 21 – 44 ] met the inclusion criteria (Table 1 ; Fig. 1 ).…”

Section: Resultsmentioning

confidence: 99%

“…The 28 included articles [ 8 , 13 – 15 , 21 – 44 ] were published from 2000 to 2023. The studies were mainly conducted in hospitals in the United Kingdom (5/28) [ 21 , 23 , 25 , 34 , 35 ], France (5/28) [ 13 , 15 , 22 , 26 , 42 ], Germany (4/28) [ 14 , 28 , 29 , 33 ], China (3/28) [ 38 , 43 , 44 ] and Greece (3/28) [ 30 , 31 , 39 ]. Most articles studied the correlation between AMC and AMR month by month, with a median follow-up ranging from 15 to 174 months [ 24 , 29 ].…”

Section: Resultsmentioning

confidence: 99%

“…Twenty-six studies [ 8 , 14 , 15 , 21 – 38 , 40 – 44 ] included all the bacteriological samples available, while one [ 13 ] focused on urine analyses and one [ 39 ] on blood cultures. When different samples from the same patient were positive for the same microorganism, samples were deduplicated in most studies (23/28) [ 8 , 13 – 15 , 21 – 23 , 26 – 32 , 34 , 36 – 38 , 40 – 44 ].…”

Section: Resultsmentioning

confidence: 99%

“…Finally, DR models could be used to evaluate existing ASPs and to develop new ones, targeting the consumption of antibiotics that are more closely linked to the emergence of AMR [ 14 ]. However, their predictive capacity is the subject of debate and could limit their use to retrospective analyses only [ 15 ]. Indeed, external validation of DR models has been performed in few studies [ 15 ], in which they seems to be much better at describing the link between prior AMC and AMR, rather than predicting the emergence of resistance on the basis of presumed AMC.…”

Section: Introductionmentioning

confidence: 99%

“…However, their predictive capacity is the subject of debate and could limit their use to retrospective analyses only [ 15 ]. Indeed, external validation of DR models has been performed in few studies [ 15 ], in which they seems to be much better at describing the link between prior AMC and AMR, rather than predicting the emergence of resistance on the basis of presumed AMC.…”

Section: Introductionmentioning

confidence: 99%

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

Laffont-Lozes,

Larcher,

Salipante

et al. 2023

Antimicrob Resist Infect Control

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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.

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