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. 2025 Oct 14;14(10):1020.
doi: 10.3390/antibiotics14101020.

Correlation Between Antimicrobial Consumption and Resistance in Klebsiella pneumoniae During the COVID-19 Pandemic Using Dynamic Regression Models: A Quasi-Experimental Epidemiological Time-Series Study

Affiliations

Correlation Between Antimicrobial Consumption and Resistance in Klebsiella pneumoniae During the COVID-19 Pandemic Using Dynamic Regression Models: A Quasi-Experimental Epidemiological Time-Series Study

Paul Laffont-Lozes et al. Antibiotics (Basel). .

Abstract

Background/Objectives: The COVID-19 pandemic has been reported to impact antimicrobial consumption (AMC) and antimicrobial resistance (AMR) worldwide. We aimed to assess this correlation in Klebsiella pneumoniae before and during the COVID-19 pandemic and to estimate the burden of each antibiotic. Methods: We collected data on AMC of penicillins and beta-lactamase inhibitors (PBIs), anti-pseudomonal activity penicillins and beta-lactamase inhibitors (AAPBIs), cephalosporins, carbapenems, fluoroquinolones, aminoglycosides, and AMR in K. pneumoniae strains. The correlation between AMC and AMR was studied using dynamic regression models. Results: Overall, AMC of AAPBIs and fourth-generation cephalosporin increased, while fluoroquinolone consumption and AMR in the 2862 K. pneumoniae strains analyzed decreased. However, during the first year of the pandemic, we reported an increase in AMC and AMR. We found that 46% to 48% of the increase in cephalosporin, AAPBI, and fluoroquinolone resistance was explained by increased cephalosporin and fluoroquinolone consumption, 55% of the increase in PBI resistance was explained by increased PBI, cephalosporin, and fluoroquinolone consumption, and 58% of the increase in aminoglycoside resistance was explained by increased aminoglycoside consumption. Conclusions: During the COVID-19 pandemic, the increase in AMR in K. pneumoniae was correlated with the increase in AMC of several antibiotics, mainly cephalosporins and especially fluoroquinolones.

Keywords: COVID-19; Klebsiella pneumoniae; antimicrobial consumption; antimicrobial resistance; dynamic regression.

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Conflict of interest statement

P.L.-L. has received support for attending meetings and/or travel from Shionogi. P.L. 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. A.S. 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. R.L. has received consulting fees from MSD, payment or honoraria for lectures, presentations, speakers’ bureaus, or educational events from BioMérieux, MSD, Pfizer and Shionogi, and support for attending meetings and/or travel from BioMérieux, Roche Diagnostics, MSD, Pfizer, and Shionogi. All other authors declare that they have no conflict of interest.

Figures

Figure A1
Figure A1
Monthly antimicrobial resistance rates to the different classes of antibiotics in Klebsiella pneumoniae strains before (2014–2019) and during (2020–2021) the coronavirus disease 2019 (COVID-19) pandemic.
Figure 1
Figure 1
Flowchart of the study population.
Figure 2
Figure 2
Annual antimicrobial resistance rates to the different classes of antibiotics in Klebsiella pneumoniae strains before (2014–2019) and during (2020–2021) the coronavirus disease 2019 (COVID-19) pandemic (AAPBIs: anti-pseudomonal activity penicillin and beta-lactamase inhibitors. PBIs: penicillin and beta-lactamase inhibitors).
Figure 3
Figure 3
Dynamic regression modeling of (A) aminoglycosides resistance, (B) cephalosporins resistance, (C) penicillins anti-pseudomonal activity and beta-lactamase inhibitor resistance, (D) penicillins and beta-lactamase inhibitor resistance, and (E) fluoroquinolones resistance, in Klebsiella pneumoniae, during the coronavirus disease 2019 (COVID-19) pandemic (2020–2021). MA(7): moving average smoother with window size of 7 months; applied for graphical representation to highlight overall trends and reduce short-term fluctuations.

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