Evidence map›Paper›PMID 42440663›Full record

ArticleFrontiers in medicine2026

Vancomycin population pharmacokinetics in patients with burns.

Yan Shi, Yijin Yao, Xiaoshuang He, Xiaolan Bian, Xunben Yu, Jie Fang, Huan Wang, Yi Dou

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Yan Shi *Department of Burn, Shanghai Burn Institute, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yijin Yao *Department of Respiratory and Critical Care Medicine, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai, China.
Xiaoshuang He *Department of Pharmacy, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai, China.
Xiaolan BianDepartment of Pharmacy, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai, China.
Xunben YuDepartment of Pharmacy, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
Jie FangDepartment of Pharmacy, School of Medicine, Ruijin Hospital, Shanghai Jiao Tong University, Shanghai, China.
Huan WangDepartment of Pharmacy, The Fifth Affiliated Hospital, Xinjiang Medical University, Ürümqi, China.
Yi DouDepartment of Burn, Shanghai Burn Institute, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Vancomycin is used to treat severe infections caused by methicillin-resistant gram-positive bacteria such as methicillin-resistant Methods: Serum vancomycin concentrations from 93 burn patients were analyzed using non-linear mixed-effects modeling. Covariates including age, gender, creatinine clearance (CrCL), BMI, burn cause, and burn area were evaluated using stepwise forward selection and backward elimination. Model stability was assessed by bootstrap. Predictive performance was compared with Clincalc in 9 external burn patients. Results: A one-compartment model best described vancomycin PK in burn patients. The final model identified CrCL as a significant covariate on clearance: CL (L/h) = 6.73 × (CrCL/111.67) Conclusion: Vancomycin clearance is increased in burn patients and significantly correlated with CrCL. The developed PopPK model provides a reliable basis for individualized vancomycin dosing in this specific population.

Indexed as

burncreatinine clearanceindividualized medicationPPK modelvancomycin

Identifiers

PMID42440663
PMCPMC13333703

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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.