Evidence map›Paper›PMID 35218003›Full record

ReviewClinical pharmacokinetics2022

Biomarkers Predicting Tissue Pharmacokinetics of Antimicrobials in Sepsis: A Review.

Maria Sanz Codina, Markus Zeitlinger

Open access · hybridAbstract readReview
In one paragraph

Review in Clinical pharmacokinetics, 2022. 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
4.9field-weighted citation impact, top 4% of its field
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, 30 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Review
  6. Article
  7. Host Biomarkers and Antibiotic Tissue Penetration in Sepsis: Insights from Moxifloxacin.European journal of drug metabolism and pharmacokinetics · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Review
  18. Article
  19. Effect of the human endotoxin challenge on tedizolid tissue penetration.British journal of clinical pharmacology · 2023
    Article
  20. Article
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

2 authors at 1 institution in 1 country.

Maria Sanz CodinaDepartment of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.ORCID 0000-0002-1687-5296
Markus ZeitlingerDepartment of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria. markus.zeitlinger@meduniwien.ac.at.ORCID 0000-0001-5500-5878
Medical University of Vienna · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The pathophysiology of sepsis alters drug pharmacokinetics, resulting in inadequate drug exposure and target-site concentration. Suboptimal exposure leads to treatment failure and the development of antimicrobial resistance. Therefore, we seek to optimize antimicrobial therapy in sepsis by selecting the right drug and the correct dosage. A prerequisite for achieving this goal is characterization and understanding of the mechanisms of pharmacokinetic alterations. However, most infections take place not in blood but in different body compartments. Since tissue pharmacokinetic assessment is not feasible in daily practice, we need to tailor antibiotic treatment according to the specific patient's pathophysiological processes. The complex pathophysiology of sepsis and the ineffectiveness of current targeted therapies suggest that treatments guided by biomarkers predicting target-site concentration could provide a new therapeutic strategy. Inflammation, endothelial and coagulation activation markers, and blood flow parameters might be indicators of impaired tissue distribution. Moreover, hepatic and renal dysfunction biomarkers can predict not only drug metabolism and clearance but also drug distribution. Identification of the right biomarkers can direct drug dosing and provide timely feedback on its effectiveness. Therefore, this might decrease antibiotic resistance and the mortality of critically ill patients. This article fills the literature gap by characterizing patient biomarkers that might be used to predict unbound plasma-to-tissue drug distribution in critically ill patients. Although all biomarkers must be clinically evaluated with the ultimate goal of combining them in a clinically feasible scoring system, we support the concept that the appropriate biomarkers could be used to direct targeted antibiotic dosing. ADAMTS-13 a disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13, ALAT alanine amino transferase, APACHE IV Acute Physiology and Chronic Health Evaluation-IV, aPPT activated partial thromboplastin time, ASAT aspartate amino transferase, AT antithrombin, Ca-V-O

Indexed as

Anti-Infective AgentsSepsisBiomarkersCritical IllnessHumansVascular Endothelial Growth Factor AAnti-Infective AgentsBiomarkersVascular Endothelial Growth Factor A

Identifiers

PMID35218003
PMCPMC9095522
OpenAlexW4214735255

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.