Evidence map›Paper›PMID 23554417›Full record

ReviewClinical microbiology reviews2013

Importance of relating efficacy measures to unbound drug concentrations for anti-infective agents.

Daniel Gonzalez, Stephan Schmidt, Hartmut Derendorf

Abstract readReview
In one paragraph

Review in Clinical microbiology reviews, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 2 pooled it
–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

74 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  13. Wearable bioelectronics for cancer theranostics.Microsystems & nanoengineering · 2025
    Review
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  18. Assessment of antibiotic release and antibacterial efficacy from pendant glutathione hydrogels using ex vivo porcine skin.Journal of controlled release : official journal of the Controlled Release Society · 2024
    Article
  19. Review
  20. Article

14 more citing papers are in PubMed but not listed here.

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

3 authors.

Daniel GonzalezDepartment of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL, USA.
Stephan Schmidt
Hartmut Derendorf

Funding

UNC-Duke Collaborative Clinical Pharmacology Postdoctoral Training Program-Evaluation SupplementT32GM086330 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KIM L.R. BROUWER, Daniel Gonzalez · 2011 to 2026
$8.5M
NIGMS NIH HHS T32 GM086330
6 · The paper itself

Abstract

For the optimization of dosing regimens of anti-infective agents, it is imperative to have a good understanding of pharmacokinetics (PK) and pharmacodynamics (PD). Whenever possible, drug efficacy needs to be related to unbound concentrations at the site of action. For anti-infective drugs, the infection site is typically located outside plasma, and a drug must diffuse through capillary membranes to reach its target. Disease- and drug-related factors can contribute to differential tissue distribution. As a result, the assumption that the plasma concentration of drugs represents a suitable surrogate of tissue concentrations may lead to erroneous conclusions. Quantifying drug exposure in tissues represents an opportunity to relate the pharmacologically active concentrations to an observed pharmacodynamic parameter, such as the MIC. Selection of an appropriate specimen to sample and the advantages and limitations of the available sampling techniques require careful consideration. Ultimately, the goal will be to assess the appropriateness of a drug and dosing regimen for a specific pathogen and infection.

Indexed as

Anti-Infective AgentsCommunicable DiseasesHumansTissue DistributionTreatment OutcomeAnti-Infective Agents

Identifiers

PMID23554417
PMCPMC3623378

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.