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Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models

Overview of attention for article published in Critical Care, December 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Title
Can physicochemical properties of antimicrobials be used to predict their pharmacokinetics during extracorporeal membrane oxygenation? Illustrative data from ovine models
Published in
Critical Care, December 2015
DOI 10.1186/s13054-015-1151-y
Pubmed ID
Authors

Kiran Shekar, Jason A. Roberts, Adrian G. Barnett, Sara Diab, Steven C. Wallis, Yoke L. Fung, John F. Fraser

Abstract

Ex vivo experiments in extracorporeal membrane oxygenation (ECMO) circuits have identified octanol-water partition coefficient (logP, a marker of lipophilicity) and protein binding (PB) as key drug factors affecting pharmacokinetics (PK) during ECMO. Using ovine models, in this study we investigated whether these drug properties can be used to predict PK alterations of antimicrobial drugs during ECMO. Single-dose PK sampling was performed in healthy sheep (HS, n = 7), healthy sheep on ECMO (E24H, n = 7) and sheep with smoke inhalation acute lung injury on ECMO (SE24H, n = 6). The sheep received eight study antimicrobials (ceftriaxone, gentamicin, meropenem, vancomycin, doripenem, ciprofloxacin, fluconazole, caspofungin) that exhibit varying degrees of logP and PB. Plasma drug concentrations were determined using validated chromatographic techniques. PK data obtained from a non-compartmental analysis were used in a linear regression model to predict PK parameters based on logP and PB. We found statistically significant differences in pH, haemodynamics, fluid balance and plasma proteins between the E24H and SE24H groups (p < 0.001). logP had a strong positive linear relationship with steady-state volume of distribution (Vss) in both the E24H and SE24H groups (p < 0.001) but not in the HS group (p = 0.9) and no relationship with clearance (CL) in all study groups. Although we observed an increase in CL for highly PB drugs in ECMO sheep, PB exhibited a weaker negative linear relationship with both CL (HS, p = 0.01; E24H, p < 0.001; SE24H, p < 0.001) and Vss (HS, p = 0.01; E24H, p = 0.004; SE24H, p =0.05) in the final model. Lipophilic antimicrobials are likely to have an increased Vss and decreased CL during ECMO. Protein-bound antimicrobial agents are likely to have reductions both in CL and Vss during ECMO. The strong relationship between lipophilicity and Vss seen in both the E24H and SE24H groups indicates circuit sequestration of lipophilic drugs. These findings highlight the importance of drug factors in predicting antimicrobial drug PK during ECMO and should be a consideration when performing and interpreting population PK studies.

X Demographics

X Demographics

The data shown below were collected from the profiles of 40 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Chile 1 2%
Unknown 64 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 12%
Other 7 11%
Student > Ph. D. Student 7 11%
Student > Doctoral Student 5 8%
Student > Master 5 8%
Other 15 23%
Unknown 19 29%
Readers by discipline Count As %
Medicine and Dentistry 25 38%
Pharmacology, Toxicology and Pharmaceutical Science 11 17%
Agricultural and Biological Sciences 2 3%
Biochemistry, Genetics and Molecular Biology 2 3%
Linguistics 1 2%
Other 8 12%
Unknown 17 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. 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 09 July 2016.
All research outputs
#1,636,515
of 25,587,485 outputs
Outputs from Critical Care
#1,437
of 6,587 outputs
Outputs of similar age
#26,707
of 396,618 outputs
Outputs of similar age from Critical Care
#100
of 466 outputs
Altmetric has tracked 25,587,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,587 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one has done well, scoring higher than 78% of its peers.
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 396,618 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 466 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.