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PK–PD Compass: bringing infectious diseases pharmacometrics to the patient’s bedside

Overview of attention for article published in Journal of Pharmacokinetics and Pharmacodynamics, March 2017
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Title
PK–PD Compass: bringing infectious diseases pharmacometrics to the patient’s bedside
Published in
Journal of Pharmacokinetics and Pharmacodynamics, March 2017
DOI 10.1007/s10928-017-9518-0
Pubmed ID
Authors

Catharine C. Bulik, Justin C. Bader, Li Zhang, Scott A. Van Wart, Christopher M. Rubino, Sujata M. Bhavnani, Kim L. Sweeney, Paul G. Ambrose

Abstract

Antimicrobial stewardship programs face many challenges, one of which is a lack of guidance regarding antimicrobial dose, interval, and duration. There is no tool that considers patient demographic, pathogen susceptibility, and pharmacokinetic-pharmacodynamic (PK-PD) targets for efficacy in order to evaluate appropriate antimicrobial dosing regimens. The PK-PD Compass, an educational mobile application, was developed to address this unmet need. The application consists of a Monte Carlo simulation algorithm which integrates pharmacokinetic (PK) and PK-PD data, patient-specific characteristics, and pathogen susceptibility data. Through the integration of these data, the application allows practitioners to assess the percent probability of PK-PD target attainment for 35 intravenous antimicrobial agents across 29 infection categories. Population PK models for each drug were identified, evaluated, and refined as needed. Susceptibility breakpoints were based upon FDA and CLSI criteria. By incorporating these data into one interface, clinicians can select the infection, pathogen, and antimicrobial agents of interest and obtain the percent probability of PK-PD target attainment for each regimen based upon patient-specific characteristics. The antimicrobial dosing regimens provided include those recommended by standard guidelines and reference texts. However, unlike these references, potential choices are prioritized based on percent probabilities of PK-PD target attainment. Such data will educate clinicians on selecting optimized antibiotic regimens through the lens of PK-PD.

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The data shown below were collected from the profiles of 2 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 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Netherlands 1 3%
Unknown 35 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 16%
Researcher 6 16%
Student > Postgraduate 4 11%
Student > Master 3 8%
Student > Doctoral Student 2 5%
Other 6 16%
Unknown 10 27%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 10 27%
Medicine and Dentistry 6 16%
Veterinary Science and Veterinary Medicine 3 8%
Agricultural and Biological Sciences 2 5%
Mathematics 1 3%
Other 6 16%
Unknown 9 24%
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 06 April 2017.
All research outputs
#15,173,117
of 25,382,440 outputs
Outputs from Journal of Pharmacokinetics and Pharmacodynamics
#292
of 477 outputs
Outputs of similar age
#170,101
of 322,922 outputs
Outputs of similar age from Journal of Pharmacokinetics and Pharmacodynamics
#4
of 7 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 477 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 37th percentile – i.e., 37% 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 322,922 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.