Evidence map›Paper›PMID 30768726›Full record

SynthesisBritish journal of clinical pharmacology2019

Predicting the dose of vancomycin in ICU patients receiving different types of RRT therapy: a model-based meta-analytic approach.

Guillaume Claisse, Paul J Zufferey, Jane C Trone, Nicolas Maillard, Xavier Delavenne, Silvy Laporte, Edouard Ollier

Open access · bronzeAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in British journal of clinical pharmacology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 3 pooled it
1.3field-weighted citation impact, top 22% 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

17 citing papers in PubMed, 3 syntheses or guidelines pooled it, 19 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Guillaume ClaisseService de Néphrologie, Dialyse, Transplantation Rénale, Hôpital Nord, Saint-Etienne, France.
Paul J ZuffereyUnité de Recherche Clinique, Innovation, Pharmacologie, Hôpital Nord, Saint-Etienne, France.ORCID 0000-0003-2899-1195
Jane C TroneDépartement de radiothérapie, Institut de Cancérologie Lucien Neuwirth, Saint Etienne, France.
Nicolas MaillardService de Néphrologie, Dialyse, Transplantation Rénale, Hôpital Nord, Saint-Etienne, France.
Xavier DelavenneINSERM, U1059, Dysfonction Vasculaire et Hémostase, Saint-Etienne, France.ORCID 0000-0001-7134-0713
Silvy LaporteUnité de Recherche Clinique, Innovation, Pharmacologie, Hôpital Nord, Saint-Etienne, France.
Edouard OllierUnité de Recherche Clinique, Innovation, Pharmacologie, Hôpital Nord, Saint-Etienne, France.ORCID 0000-0001-6925-2941
Inserm · FRHôpital Nord · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimPrevious pharmacokinetic (PK) studies have proposed various dosing regimens for vancomycin in intensive care unit (ICU) patients undergoing renal replacement therapy (RRT), but all are restricted to specific RRT modalities. To be useful in practice, a population PK model would need to predict vancomycin clearance during any RRT modality. Development of such a model is feasible using meta-analysis of published summarized estimates of vancomycin PK parameters. Our aims were: (i) to develop and validate a population PK model for vancomycin that takes into account any RRT modalities, and (ii) to predict vancomycin dosing for RRT patients in ICU.

methodsVancomycin pharmacokinetics were assumed to be two-compartmental, total body clearance being the sum of non-RRT clearance and RRT-induced clearance. Drug disposition and non-RRT clearance parameters were estimated by systematic review and meta-analysis of previously published parameter estimates. The relationship between RRT-induced clearance and RRT flowrate settings was assessed using a model-based meta-analysis. Prediction performances of the PK model were assessed using external data.

resultsThe meta-analyses of disposition parameters, non-RRT clearance and RRT-induced clearance included 11, 6 and 38 studies (84 RRT clearance measurements) respectively. The model performed well in predicting external individual PK data. Individual vancomycin concentrations during RRT were accurately predicted using Bayesian estimation based solely on pre-RRT measurements.

conclusionsThe PK model allowed accurate prediction of the vancomycin pharmacokinetics during RRT in ICU patients. Based on the model of RRT-induced clearance, an appropriate adjustment of the vancomycin dosing regimen could be proposed for any kind of flowrate settings.

Indexed as

Drug Dosage CalculationsIntensive Care UnitsModels, BiologicalRenal Replacement TherapyAnti-Bacterial AgentsHumansVancomycinAnti-Bacterial AgentsVancomycinClearanceIntensive CareModel Based Meta-AnalysisPharmacokineticsRenal Replacement TherapyVancomycin

Identifiers

PMID30768726
PMCPMC6533443
OpenAlexW2914543184

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.