Population Pharmacokinetics and Dosing Regimen Optimization of Linezolid in Cerebrospinal Fluid and Plasma of Post-operative Neurosurgical Patients

利奈唑啉 脑脊液 医学 药代动力学 人口 养生 加药 群体药代动力学 药理学 麻醉 外科 内科学 万古霉素 金黄色葡萄球菌 细菌 环境卫生 生物 遗传学
作者
Sichan Li,Yuefei Wang,Hui Dong,Yuan Zhu,Peng Cao,Meng Liang,Yang Wang
出处
期刊:Journal of Pharmaceutical Sciences [Elsevier]
卷期号:112 (3): 884-892 被引量:6
标识
DOI:10.1016/j.xphs.2022.12.016
摘要

Background Linezolid is a valuable therapeutic option for infections of the central nervous system caused by multi-drug resistant Gram-positive pathogens. Data regarding linezolid pharmacokinetics in cerebrospinal fluid from post-operative neurosurgical patients have revealed wide inter-individual variability. The objectives of this study were to establish a population pharmacokinetic model for linezolid in plasma and cerebrospinal fluid, as well as to optimize dosing strategies in this susceptible population. Methods This was a prospective pharmacokinetic study in post-operative neurosurgical patients receiving intravenous linezolid. Parallel blood and cerebrospinal fluid samples were collected and analyzed. The population pharmacokinetic modelling and Monte Carlo simulations were performed using the Phoenix NLME software. Results A two-compartment model (central plasma and cerebrospinal fluid compartments) fit the linezolid data well, with creatinine clearance and serum procalcitonin as significant variables. Linezolid demonstrated highly variable penetration into cerebrospinal fluid, with a mean cerebrospinal fluid/plasma ratio of 0.53. A strong correlation was found between plasma trough concentration and cerebrospinal fluid exposure of linezolid. Based on simulation results, optimal dosage regimens stratified by various renal functions and inflammatory status were proposed. Conclusion A modeling and simulating strategy was employed in dose individualization to improve the efficacy and safety of linezolid treatment.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Jasper应助感性的凉面采纳,获得10
1秒前
1秒前
2秒前
2秒前
3秒前
情怀应助顺顺采纳,获得10
3秒前
garyaa发布了新的文献求助10
3秒前
3秒前
NexusExplorer应助奔奔采纳,获得10
3秒前
Orange应助Clean采纳,获得10
4秒前
Lucas应助ww采纳,获得10
4秒前
5秒前
ttttttuu完成签到,获得积分10
5秒前
6秒前
刘涵完成签到 ,获得积分10
6秒前
小马甲应助zhui采纳,获得10
6秒前
10完成签到,获得积分10
6秒前
6秒前
6秒前
Rainielove0215完成签到,获得积分0
7秒前
zz完成签到,获得积分10
8秒前
8秒前
kyle完成签到,获得积分10
10秒前
感性的凉面完成签到,获得积分20
10秒前
10秒前
请叫我风吹麦浪应助末岛采纳,获得10
11秒前
Aprial发布了新的文献求助30
11秒前
dd发布了新的文献求助10
11秒前
传奇3应助科研小菜鸟采纳,获得10
11秒前
在水一方应助惠惠采纳,获得10
12秒前
13秒前
冷艳贵公子王少完成签到 ,获得积分10
13秒前
KatzeBaliey完成签到,获得积分10
13秒前
13秒前
13秒前
14秒前
zz发布了新的文献求助10
14秒前
14秒前
Twikky发布了新的文献求助10
15秒前
15秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527884
求助须知:如何正确求助?哪些是违规求助? 3108006
关于积分的说明 9287444
捐赠科研通 2805757
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716904
科研通“疑难数据库(出版商)”最低求助积分说明 709794