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A general empirical model for renal drug handling in pharmacokinetic analyses

Overview of attention for article published in British Journal of Clinical Pharmacology, May 2017
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9 X users

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15 Mendeley
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Article details
Title
A general empirical model for renal drug handling in pharmacokinetic analyses
Published in
British Journal of Clinical Pharmacology, May 2017
DOI 10.1111/bcp.13306
Pubmed ID
Authors
Abstract

Dose adjustment in renal insufficiency is generally based on the assumption that renal drug clearance is related linearly to glomerular filtration rate. The theory underpinning this model is the Intact Nephron Hypothesis, where impaired renal function is said to be caused by a reduction in the number of complete (intact) nephrons. The purpose of this commentary is to propose a general empirical model for renal drug handling. We will explore models for renal function under two scenarios; one that aligns with the intact nephron hypothesis, and one that relaxes the assumptions of this hypothesis. We propose that a non-linear, non-intact nephron model will allow for differences in renal drug handling, while incorporating the intact nephron hypothesis model as a special case.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 4 27%
Student > Master 4 27%
Student > Doctoral Student 2 13%
Researcher 2 13%
Student > Bachelor 1 7%
Other 2 13%
Readers by discipline
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 4 27%
Medicine and Dentistry 4 27%
Chemical Engineering 1 7%
Mathematics 1 7%
Agricultural and Biological Sciences 1 7%
Other 1 7%
Unknown 3 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 30 April 2018.
All research outputs
#8,531,507
of 32,505,732 outputs
Outputs from British Journal of Clinical Pharmacology
#2,314
of 6,726 outputs
Outputs of similar age
#99,919
of 346,791 outputs
Outputs of similar age from British Journal of Clinical Pharmacology
#28
of 46 outputs
Altmetric has tracked 32,505,732 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 6,726 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has gotten more attention than average, scoring higher than 65% 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 346,791 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 46 others from the same source and published within six weeks on either side of this one. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.