1.广州新华学院,广东 广州 510520
2.中山大学孙逸仙纪念医院重症医学科,广东 广州 510120
3.中山大学孙逸仙纪念医院药学部,广东 广州 510120
何志捷,主任医师,研究方向:脓毒症;E-mail:Hezhijie@mail.sysu.edu.cn
纸质出版日期:2022-11-20,
收稿日期:2022-10-10,
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何志捷,植耀炜,管宴萍等.重症监护病房脓毒症患者替考拉宁的群体药代动力学研究[J].中山大学学报(医学科学版),2022,43(06):1005-1011.
HE Zhi-jie,ZHI Yao-wei,GUAN Yan-pin,et al.Population Pharmacokinetics of Teicoplanin in Septic Patients from Intensive Care Unit[J].Journal of Sun Yat-sen University(Medical Sciences),2022,43(06):1005-1011.
何志捷,植耀炜,管宴萍等.重症监护病房脓毒症患者替考拉宁的群体药代动力学研究[J].中山大学学报(医学科学版),2022,43(06):1005-1011. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2022.0616.
HE Zhi-jie,ZHI Yao-wei,GUAN Yan-pin,et al.Population Pharmacokinetics of Teicoplanin in Septic Patients from Intensive Care Unit[J].Journal of Sun Yat-sen University(Medical Sciences),2022,43(06):1005-1011. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2022.0616.
目的
2
建立替考拉宁在重症监护病房脓毒症患者体内的群体药代动力学模型,探讨其药代动力学特征及可能的影响因素。
方法
2
纳入2017年11月至2020年2月入住中山大学孙逸仙纪念医院重症医学科的脓毒症患者66例,并采用高效液相色谱法测定替考拉宁血药谷浓度水平。应用非线性混合效应模型分析脓毒症静脉滴注替考拉宁后的血药浓度数据,计算相关药代动力学参数及其变异情况,构建替考拉宁在脓毒症患者中的群体药代动力学模型,并对最终模型进行验证。
结果
2
采用二房室模型拟合所收集的替考拉宁血药浓度数据。替考拉宁中央室清除率的群体典型值为0.45 L/min,外周室清除率的群体典型值为0.72 L/min,中央室分布容积的群体典型值为39.74 L,外周室分布容积的群体典型值为152.41 L。逐步回归法筛选协变量结果显示,血清肌酐、总蛋白及乳酸对替考拉宁的中央室清除率具有显著性影响(
P
<
0.05)。
结论
2
本研究建立的二房室群体药代动力学模型,较好预测替考拉宁在重症监护病房脓毒症患者中的药代动力学特征,可为后续优化重症脓毒症患者的给药方案提供理论依据。
Objective
2
To establish a population pharmacokinetic (PPK) model of teicoplanin in septic patients from Intensive Care Unit (ICU) and to explore its pharmacokinetic characteristics and related covariates.
Methods
2
The study included 66 septic patients hospitalized in the department of critical care medicine from November 2017 to February 2020. After intravenous dosing of teicoplanin in septic patients, the trough concentration of teicoplanin was determined by high performance liquid chromatography (HPLC) and the concentration-time data was analyzed by non-linear mixed effect model. The pharmacokinetic parameters and residual errors were evaluated. The influence of covariates on model parameters was tested by forward addition and backward elimination. The predictive performance of the final model was assessed by internal validation.
Results
2
A two-compartment model best described the teicoplanin concentration-time data. The PPK parameter estimates were central clearance of 0.45 L/min, peripheral clearance of 0.72 L/min, central volume of distribution of 39.74 L and peripheral volume of distribution of 152.41 L. Creatinine, total protein, and lactate were found to significantly affect central clearance of teicoplanin (
P
<
0.05).
Conclusion
2
The two-compartment PPK model of teicoplanin established in this study could be used for individualized treatment in septic patients from ICU due to its good stability and high predictive accuracy.
替考拉宁重症监护病房脓毒症群体药代动力学二房室模型
teicoplaninintensive care unit (ICU)sepsispopulation pharmacokineticstwo-compartment model
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