Evidence map›Paper›PMID 24663017›Full record

ArticleAntimicrobial agents and chemotherapy2014

Simplified equations using two concentrations to calculate area under the curve for antimicrobials with concentration-dependent pharmacodynamics: daptomycin as a motivating example.

Manjunath P Pai, Alessandro Russo, Andrea Novelli, Mario Venditti, Marco Falcone

Abstract read
In one paragraph

Article in Antimicrobial agents and chemotherapy, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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  5. Article
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  11. Review
  12. Clinical Pharmacokinetics of Daptomycin.Clinical pharmacokinetics · 2021
    Review
  13. Article
  14. Article
  15. Review
  16. Review
  17. Gap Analysis for the Conversion to Area Under the Curve Vancomycin Monitoring in a Small Rural Hospital.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2020
    Article
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  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Manjunath P PaiAlbany College of Pharmacy and Health Sciences, Albany, New York, USA.
Alessandro RussoDepartment of Public Health and Infectious Diseases, "Sapienza" University of Rome, Policlinico Umberto I, Rome, Italy.
Andrea NovelliClinical Pharmacology and Oncology Section, University of Florence, Florence, Italy.
Mario VendittiDepartment of Public Health and Infectious Diseases, "Sapienza" University of Rome, Policlinico Umberto I, Rome, Italy.
Marco FalconeDepartment of Public Health and Infectious Diseases, "Sapienza" University of Rome, Policlinico Umberto I, Rome, Italy marcofalc@libero.it.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The effects of several antimicrobial agents are predicted by the ratio of the area under the concentration-time curve (AUC) to the MIC (AUC/MIC). Peak (Cp) and trough (Ct) concentrations are often measured clinically as surrogates of AUC because actual computation of AUC from 1 or 2 samples requires sophisticated mathematical methods. Given that the effects of daptomycin are predicted by AUC/MIC, our objective was to compare simple equation calculated AUC based on Cp and Ct to model integrated AUC. A standard population pharmacokinetic model was used to simulate 5,000 daptomycin concentration-time profiles after 5 doses of 6 mg/kg of body weight/day (0.5-h infusions). The AUC for the 24-h period was computed by integration and by equations with 110 Cp-Ct combination pairs. The Cp time points were in 15-min increments between 0.5 h and 3 h and Ct in 15-min increments within an hour of the end of the dosing interval for each dose. The precision and bias of the calculated AUC relative to the integrated AUC were determined to identify Cp-Ct pairs associated with the lowest bias and highest precision. The equations were further validated using two daptomycin concentration-time data sets from healthy volunteers and critically ill patients. The precision and bias of calculated AUC were based primarily on Cp, and use of a daptomycin Cp 1.5 h to 3 h from the start of infusion was associated with a bias of <10% and an R(2) of >0.95. Data from the healthy volunteers and critically ill patients also demonstrated declining bias with use of Cp ≥ 1.5 h from the start of infusion with relatively good precision. Simplified equations using a daptomycin Cp approximately 2 h from the start of infusion and a Ct within an hour of the end of the dosing interval should yield precise and unbiased estimates of daptomycin AUC.

Indexed as

AlgorithmsAdultAnti-Bacterial AgentsArea Under CurveComputer SimulationCritical IllnessDaptomycinFemaleHumansInfusions, IntravenousMaleObesity, MorbidPopulationReproducibility of ResultsStaphylococcus aureusAnti-Bacterial AgentsDaptomycin

Identifiers

PMID24663017
PMCPMC4068499

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.