Evidence map›Paper›PMID 28039606›Full record

ArticleClinical pharmacokinetics2017

Development of a Physiologically Based Pharmacokinetic Modelling Approach to Predict the Pharmacokinetics of Vancomycin in Critically Ill Septic Patients.

Christian Radke, Dagmar Horn, Christian Lanckohr, Björn Ellger, Michaela Meyer, Thomas Eissing, Georg Hempel

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Article in Clinical pharmacokinetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  17. Biomarker-Guided Individualization of Antibiotic Therapy.Clinical pharmacology and therapeutics · 2021
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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

7 authors.

Christian RadkeDepartment of Clinical Pharmacy, Institute of Pharmaceutical and Medical Chemistry, University of Muenster, Corrensstrasse 48, 48149, Muenster, Germany.
Dagmar HornDepartment of Pharmacy, University Hospital of Muenster, Muenster, Germany.
Christian LanckohrDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital of Muenster, Muenster, Germany.
Björn EllgerDepartment of Anesthesiology, Intensive Care Medicine and Pain Therapy, University Hospital of Muenster, Muenster, Germany.
Michaela MeyerSystems Pharmacology CV, Bayer Technology Services GmbH, Leverkusen, Germany.
Thomas EissingSystems Pharmacology CV, Bayer Technology Services GmbH, Leverkusen, Germany.
Georg HempelDepartment of Clinical Pharmacy, Institute of Pharmaceutical and Medical Chemistry, University of Muenster, Corrensstrasse 48, 48149, Muenster, Germany. georg.hempel@uni-muenster.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivesSepsis is characterised by an excessive release of inflammatory mediators substantially affecting body composition and physiology, which can be further affected by intensive care management. Consequently, drug pharmacokinetics can be substantially altered. This study aimed to extend a whole-body physiologically based pharmacokinetic (PBPK) model for healthy adults based on disease-related physiological changes of critically ill septic patients and to evaluate the accuracy of this PBPK model using vancomycin as a clinically relevant drug.

methodsThe literature was searched for relevant information on physiological changes in critically ill patients with sepsis, severe sepsis and septic shock. Consolidated information was incorporated into a validated PBPK vancomycin model for healthy adults. In addition, the model was further individualised based on patient data from a study including ten septic patients treated with intravenous vancomycin. Models were evaluated comparing predicted concentrations with observed patient concentration-time data.

resultsThe literature-based PBPK model correctly predicted pharmacokinetic changes and observed plasma concentrations especially for the distribution phase as a result of a consideration of interstitial water accumulation. Incorporation of disease-related changes improved the model prediction from 55 to 88% within a threshold of 30% variability of predicted vs. observed concentrations. In particular, the consideration of individualised creatinine clearance data, which were highly variable in this patient population, had an influence on model performance.

conclusionPBPK modelling incorporating literature data and individual patient data is able to correctly predict vancomycin pharmacokinetics in septic patients. This study therefore provides essential key parameters for further development of PBPK models and dose optimisation strategies in critically ill patients with sepsis.

Indexed as

Models, BiologicalAdultAgedAnti-Bacterial AgentsBlood ProteinsCritical IllnessCytochrome P-450 Enzyme SystemFemaleHematocritHumansKidneyLiverMaleMiddle AgedSepsisVancomycinAnti-Bacterial AgentsBlood ProteinsCytochrome P-450 Enzyme SystemVancomycin

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Registered trials

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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.