Evidence map›Paper›PMID 32468340›Full record

ArticlePharmaceutical research2020

Development of Vancomycin Dose Individualization Strategy by Bayesian Prediction in Patients Receiving Continuous Renal Replacement Therapy.

Kazutaka Oda, Hirofumi Jono, Hidenobu Kamohara, Kazuhiko Nishi, Naomi Tanoue, Hideyuki Saito

Abstract readEvaluation Study
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In one paragraph

Article in Pharmaceutical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

6 authors.

Kazutaka OdaDepartment of Pharmacy, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan. kazutakaoda@kuh.kumamoto-u.ac.jp.
Hirofumi JonoDepartment of Pharmacy, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan.
Hidenobu KamoharaDepartment of Intensive Care Medicine, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan.
Kazuhiko NishiDepartment of Hemodialysis and Apheresis, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan.
Naomi TanoueDepartment of Pharmacy, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan.
Hideyuki SaitoDepartment of Pharmacy, Kumamoto University Hospital, 1-1-1, Honjo, Chuo-ku, Kumamoto city, Kumamoto, Japan.

Funding

Ministry of Education, Culture, Sports, Science and Technology 16K19615
6 · The paper itself

Abstract

purposeVancomycin (VCM) concentration is often out of therapeutic range (10-20 μg/ml) in patients receiving continuous renal replacement therapy (CRRT). The purposes of this study were to develop a practical VCM population pharmacokinetic (PPK) model and to evaluate the potential of Bayesian prediction-based therapeutic drug monitoring (Bayes-TDM) in VCM dose individualization for patients receiving CRRT.

methodsWe developed a VCM PPK model using 80 therapeutic concentrations in 17 patients receiving CRRT. Bayes-TDM with the VCM PPK model was evaluated in 23 patients after PPK modeling.

resultsWe identified the covariates reduced urine output (RUO, <0.5 ml/kg/h) and effluent flow rate of CRRT for the VCM PPK model. The mean VCM non CRRT clearance (CL

conclusionsBayes-TDM could be a useful tool for VCM dose individualization in patients receiving CRRT.

Indexed as

Models, BiologicalAcute Kidney InjuryAdultAgedAged, 80 and overAnti-Bacterial AgentsBayes TheoremContinuous Renal Replacement TherapyDose-Response Relationship, DrugDrug MonitoringFemaleHumansKidneyMaleMiddle AgedRenal EliminationAnti-Bacterial AgentsVancomycinBayesiancontinuous renal replacement therapypopulation pharmacokineticstherapeutic drug monitoringVancomycin

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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.