摘要
目的评估利奈唑胺群体药动学软件(NextDose-Linezolid)在中国人群的预测能力,并验证其临床应用效果。方法收集接受利奈唑胺治疗的住院患者,排除严重肾功能不全者(肌酐清除率<30 mL·min^(-1)),筛选出已测定过利奈唑胺血药浓度的患者共计38例。将患者的利奈唑胺给药剂量及相关个体化信息输入NextDose-Linezolid,并输入PK/PD靶值,使用贝叶斯反馈法估算出患者个人的药动学参数,预测出AUC/MIC达标(100 mg·L^(-1)·h-1^(-1))所需的剂量方案,并通过临床病例验证该方案的临床疗效。结果所有患者使用利奈唑胺后的平均谷浓度为(1.72±2.54)mg·L^(-1),以NextDose-Linezolid运算后预测的表观分布容积为(20.94±9.32)L,清除率为(5.52±1.88)L·h^(-1),以AUC/MIC达标所需的剂量方案为(588.27±206.86)mg,q12h。将由NextDose-Linezolid预测的剂量方案应用于患者,经临床病例验证,疗效较为满意,不良反应小。结论NextDose-Linezolid对中国人群利奈唑胺个体化给药方案具有良好的预测能力。该研究建立的个体化给药模式,有助于指导临床合理用药。
AIM To evaluate the predictive ability of the linezolid population pharmacokinetic software(NextDose-Linezolid)in Chinese population and verify its clinical application effect.METHODS Inpatients who received linezolid were collected,and those with severe renal insufficiency(creatinine clearance<30 mL·min^(-1))were excluded.The concentrations of linezolid from 38 infected patients were collected to develop pharmacokinetic parameters using the linezolid population pharmacokinetic(PPK)model of NextDose-Linezolid,and the individualized dose protocols and the predicted concentration-time curves were calculated using the patients’information,according to Bayesian evaluation.The clinical efficacy of the protocols was verified by clinical cases.RESULTS The average trough concentration from the 38 infected patients was(1.72±2.54)mg·L^(-1)while the apparent volume of distribution predicted by NextDoseLinezolid was(20.94±9.32)L,the clearance rate was(5.52±1.88)L·h^(-1),and the average dose required to achieve the AUC/MIC standard was(588.27±206.86)mg,q12h.The dosage regimen predicted by NextDose-Linezolid was applied to patients,and the clinical cases was verified.The curative effect was satisfactory,and the adverse reactions were mild.CONCLUSION The mode of clinical application based on Bayesian forecasting process of NextDose-Linezolid model has positive prediction for the Chinese population,and can help assist clinical individualized application of linezolid.
作者
何娟
毛恩强
卞晓岚
陈冰
陈尔真
HE Juan;MAO Enqiang;BIAN Xiaolan;CHEN Bing;CHEN Erzhen(Department of Pharmacy,Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200025,China;Department of Emergency,Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine,Shanghai 200025,China)
出处
《中国临床药学杂志》
CAS
2022年第5期334-339,共6页
Chinese Journal of Clinical Pharmacy
关键词
利奈唑胺
群体药动学
贝叶斯算法
个体化给药
linezolid
population pharmacokinetic
Bayesian algorithm
individualized administration
