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Intensive care antibiotic consumption and resistance patterns: a cross-correlation analysis

Overview of attention for article published in Annals of Clinical Microbiology and Antimicrobials, November 2017
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Title
Intensive care antibiotic consumption and resistance patterns: a cross-correlation analysis
Published in
Annals of Clinical Microbiology and Antimicrobials, November 2017
DOI 10.1186/s12941-017-0251-8
Pubmed ID
Authors

Luminita Baditoiu, Carmen Axente, Diana Lungeanu, Delia Muntean, Florin Horhat, Roxana Moldovan, Elena Hogea, Ovidiu Bedreag, Dorel Sandesc, Monica Licker

Abstract

Over recent decades, a dramatic increase in infections caused by multidrug-resistant pathogens has been observed worldwide. The aim of the present study was to investigate the relationship between local resistance bacterial patterns and antibiotic consumption in an intensive care unit in a Romanian university hospital. A prospective study was conducted between 1st January 2012 and 31st December 2013. Data covering the consumption of antibacterial drugs and the incidence density for the main resistance phenotypes was collected on a monthly basis, and this data was aggregated quarterly. The relationship between the antibiotic consumption and resistance was investigated using cross-correlation, and four regression models were constructed, using the SPSS version 20.0 (IBM, Chicago, IL) and the R version 3.2.3 packages. During the period studied, the incidence of combined-resistant and carbapenem-resistant P. aeruginosa strains increased significantly [(gradient = 0.78, R(2) = 0.707, p = 0.009) (gradient = 0.74, R(2) = 0.666, p = 0.013) respectively], mirroring the increase in consumption of β-lactam antibiotics with β-lactamase inhibitors (piperacillin/tazobactam) and carbapenems (meropenem) [(gradient = 10.91, R(2) = 0.698, p = 0.010) and (gradient = 14.63, R(2) = 0.753, p = 0.005) respectively]. The highest cross-correlation coefficients for zero time lags were found between combined-resistant vs. penicillins consumption and carbapenem-resistant P. aeruginosa strains vs. carbapenems consumption (0.876 and 0.928, respectively). The best model describing the relation between combined-resistant P. aeruginosa strains and penicillins consumption during a given quarter incorporates both the consumption and the incidence of combined-resistant strains in the hospital department during the previous quarter (multiple R(2) = 0.953, p = 0.017). The best model for explaining the carbapenem resistance of P. aeruginosa strains based on meropenem consumption during a given quarter proved to be the adjusted model which takes into consideration both previous consumption and incidence density of strains during the previous quarter (Multiple R(2) = 0.921, p = 0.037). The cross-correlation coefficients and the fitted regression models provide additional evidence that resistance during the a given quarter depends not only on the consumption of antibacterial chemotherapeutic drugs in both that quarter and the previous one, but also on the incidence of resistant strains circulating during the previous quarter.

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The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 63 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 13%
Student > Ph. D. Student 7 11%
Student > Bachelor 7 11%
Student > Postgraduate 6 10%
Student > Doctoral Student 4 6%
Other 15 24%
Unknown 16 25%
Readers by discipline Count As %
Medicine and Dentistry 18 29%
Pharmacology, Toxicology and Pharmaceutical Science 9 14%
Biochemistry, Genetics and Molecular Biology 6 10%
Nursing and Health Professions 2 3%
Agricultural and Biological Sciences 2 3%
Other 10 16%
Unknown 16 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 November 2017.
All research outputs
#14,958,596
of 23,007,887 outputs
Outputs from Annals of Clinical Microbiology and Antimicrobials
#315
of 611 outputs
Outputs of similar age
#192,929
of 326,002 outputs
Outputs of similar age from Annals of Clinical Microbiology and Antimicrobials
#7
of 11 outputs
Altmetric has tracked 23,007,887 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 611 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,002 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 11 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.