Staatz Christine E, Byrne Colette, Thomson Alison H
Pharmacy Department, Western Infirmary, North Glasgow University Hospitals, NHS, Glasgow G11 6NT, UK.
Br J Clin Pharmacol. 2006 Feb;61(2):164-76. doi: 10.1111/j.1365-2125.2005.02547.x.
To describe the population pharmacokinetics of gentamicin and vancomycin in cardiothoracic surgery patients with unstable renal function.
Data collected during routine care were analyzed using NONMEM. Linear relationships between creatinine clearance (CL(Cr)) and drug clearance (CL) were identified, and two approaches to modelling changing CL(Cr) were examined. The first included baseline (BCOV) and difference from baseline (DCOV) effects and the second allowed the influence of CL(Cr) to vary between individuals. Final model predictive performance was evaluated using independent data. The data sets were then combined and parameters re-estimated.
Model building was performed using data from 96 (gentamicin) and 102 (vancomycin) patients, aged 17-87 years. CL(Cr) ranged from 9 to 172 ml min(-1) and changes varied from -76 to 58 ml min(-1) (gentamicin) and -86 to 93 ml min(-1) (vancomycin). Inclusion of BCOV and DCOV improved the fit of the gentamicin data but had little effect on that for vancomycin. Inclusion of interindividual variability (IIV) in the influence of CL(cr) resulted in a poorly characterized model for gentamicin and had no effect on vancomycin modelling. No bias was seen in population compared with individual CL estimates in independent data from 39 (gentamicin) and 37 (vancomycin) patients. Mean (95% CI) differences were 4% (-3, 11%) and 2% (-2, 6%), respectively. Final estimates were: CL(Gent) (l h(-1)) = 2.81 x (1 + 0.015 x (BCOV(CLCr)-BCOV(CLCr Median)) + 0.0174 x DCOV(CLCr)); CL(Vanc) (l h(-1)) = 2.97 x (1 + 0.0205 x (CL(Cr)-CL(Cr Median))). IIV in CL was 27% for both drugs.
A parameter describing individual changes in CL(cr) with time improves population pharmacokinetic modelling of gentamicin but not vancomycin in clinically unstable patients.
描述庆大霉素和万古霉素在肾功能不稳定的心胸外科手术患者中的群体药代动力学特征。
使用NONMEM软件分析常规护理期间收集的数据。确定肌酐清除率(CL(Cr))与药物清除率(CL)之间的线性关系,并研究两种模拟CL(Cr)变化的方法。第一种方法包括基线(BCOV)和与基线的差异(DCOV)效应,第二种方法允许CL(Cr)的影响在个体之间变化。使用独立数据评估最终模型的预测性能。然后将数据集合并并重新估计参数。
使用来自96例(庆大霉素)和102例(万古霉素)年龄在17 - 87岁患者的数据进行模型构建。CL(Cr)范围为9至172 ml min(-1),变化范围为 - 76至58 ml min(-1)(庆大霉素)和 - 86至93 ml min(-1)(万古霉素)。纳入BCOV和DCOV改善了庆大霉素数据的拟合,但对万古霉素数据的拟合影响不大。在CL(cr)的影响中纳入个体间变异性(IIV)导致庆大霉素模型特征不佳,对万古霉素建模没有影响。在来自39例(庆大霉素)和37例(万古霉素)患者的独立数据中,群体CL估计与个体CL估计相比未见偏差。平均(95% CI)差异分别为4%(-3, 11%)和2%(-2, 6%)。最终估计值为:CL(庆大霉素)(l h(-1))= 2.81 x (1 + 0.015 x (BCOV(CLCr) - BCOV(CLCr中位数)) + 0.0174 x DCOV(CLCr));CL(万古霉素)(l h(-1))= 2.97 x (1 + 0.0205 x (CL(Cr) - CL(Cr中位数)))。两种药物CL的IIV均为27%。
一个描述CL(cr)随时间个体变化的参数改善了临床不稳定患者中庆大霉素的群体药代动力学建模,但对万古霉素无效。