Evidence map›Paper›PMID 30506225›Full record

ArticleEuropean journal of drug metabolism and pharmacokinetics2019

Development of a Population Pharmacokinetic Model of Vancomycin and its Application in Chinese Geriatric Patients with Pulmonary Infections.

Ying Zhou, Feifei Gao, Chaoyang Chen, Lingyun Ma, Ting Yang, Xiao Liu, Yaou Liu, Xiaoqing Wang, Xia Zhao, Chengli Que and 4 more

Open access · hybridAbstract read
In one paragraph

Article in European journal of drug metabolism and pharmacokinetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 20% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  16. Vancomycin Pharmacokinetics in Patients with Advanced Cancer Near End of Life.European journal of drug metabolism and pharmacokinetics · 2019
    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

14 authors at 1 institution in 1 country.

Ying ZhouCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Feifei GaoCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Chaoyang ChenCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Lingyun MaCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Ting YangCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Xiao LiuCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Yaou LiuCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Xiaoqing WangCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Xia ZhaoCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China.
Chengli QueDepartment of Respiratory Medicine, Peking University First Hospital, No.1 Dahongluochang Street, Xicheng District, Beijing, China.
Shuangling LiIntensive-Care Unit, Peking University First Hospital, No.1 Dahongluochang Street, Xicheng District, Beijing, China.
JiCheng LvDepartment of Nephrology, Peking University First Hospital, No.1 Dahongluochang Street, Xicheng District, Beijing, China.
Yimin CuiCollege of Pharmacy, Peking University Health Science Center, No.38 Xueyuan Road, Haidian District, Beijing, China. cui.pharm@pkufh.com.ORCID http://orcid.org/0000-0002-4186-1005
Li YangDepartment of Nephrology, Peking University First Hospital, No.1 Dahongluochang Street, Xicheng District, Beijing, China. li.yang@bjmu.edu.cn.
Peking University · CN

Funding

the Interdisciplinary clinical research project of Peking University First Hospital 2017CR25
6 · The paper itself

Abstract

backgroundThe optimal use of vancomycin in the elderly requires information about the drug's pharmacokinetics and the influence of various factors on the drug's disposition. However, because of sampling restrictions, it is often difficult to perform traditional pharmacokinetic studies in elderly patients.

objectiveThis study was conducted to estimate the population pharmacokinetics of vancomycin in Chinese geriatric patients (age ≥ 65 years) with pulmonary infections and to explore the clinical application of this information for vancomycin dose individualization.

methodsThe steady-state trough concentrations were retrospectively collected from January 2011 to December 2016 and were analyzed using the nonlinear mixed-effect model software. The final model was evaluated using the bootstrap method, goodness-of-fit plots and the normalized prediction distribution error method.

main outcome measureModel parameters and prediction error.

resultsA total of 125 steady-state trough concentrations from 70 patients were retrospectively collected. A one-compartment model was established. The final model was depicted as clearance (CL) [L/h] = 2.45 × (CL

conclusionA population pharmacokinetic model was established to estimate the pharmacokinetics characteristics of Chinese geriatric patients with pulmonary infections, and this model can be used to develop an initial vancomycin dosing regimen for geriatric patients.

Indexed as

Models, BiologicalAgedAnti-Bacterial AgentsChinaDose-Response Relationship, DrugFemaleHumansMaleRespiratory Tract InfectionsRetrospective StudiesVancomycinAnti-Bacterial AgentsVancomycin

Identifiers

PMID30506225
PMCPMC6520475
OpenAlexW2902667296

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.