Rodvold K A, Gentry C A, Plank G S, Kraus D M, Nickel E, Gross J R
Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago 60612.
Dev Pharmacol Ther. 1993;20(3-4):211-9. doi: 10.1159/000457565.
This study retrospectively characterized population-based pharmacokinetic parameters for gentamicin in neonates and young infants, and evaluated the predictive performance of these parameters in a Bayesian forecasting program. Population parameter estimates were determined from the serum concentration-time data of 19 neonates and infants using a one-compartment open infusion model and nonlinear least-squares regression analysis. Univariate and multiple stepwise linear regression analyses were used to determine significant relationships between demographic characteristics and gentamicin pharmacokinetic parameters. Creatinine clearance and postnatal age were the most significant predictors of weight-standardized gentamicin clearance (model r2 = 0.86). The relationships between patient characteristics and population-based parameters were incorporated into the one-compartment Bayesian forecasting model. A second group of 17 neonates and infants receiving 35 courses of gentamicin therapy were used to evaluate the predictive performance of the population-based parameters and a Bayesian forecasting model. The population parameters provided accurate prediction of steady state gentamicin concentrations throughout multiple courses of therapy within the same patient. Bayesian forecasting further minimized the mean prediction error (bias) once a set of steady state peak and trough serum gentamicin concentrations became available (peak concentrations: -0.062 vs. -0.273 mg/l; trough concentrations: -0.006 vs. -0.161 mg/l). The mean absolute error (accuracy) was similar for the two sets of parameters. The observed accuracy of both the population parameters and Bayesian forecasting suggests that monitoring of serum gentamicin concentrations can be kept to minimum in neonates and infants.
本研究回顾性地描述了新生儿和婴幼儿群体中庆大霉素的药代动力学参数，并评估了这些参数在贝叶斯预测程序中的预测性能。使用一室开放输注模型和非线性最小二乘回归分析，根据19例新生儿和婴儿的血清浓度-时间数据确定群体参数估计值。采用单变量和多步线性回归分析来确定人口统计学特征与庆大霉素药代动力学参数之间的显著关系。肌酐清除率和出生后年龄是体重标准化庆大霉素清除率的最显著预测因子（模型r2 = 0.86）。患者特征与群体参数之间的关系被纳入一室贝叶斯预测模型。另一组接受35个疗程庆大霉素治疗的17例新生儿和婴儿用于评估群体参数和贝叶斯预测模型的预测性能。群体参数在同一患者的多个疗程治疗中准确预测了稳态庆大霉素浓度。一旦获得一组稳态峰谷血清庆大霉素浓度，贝叶斯预测进一步将平均预测误差（偏差）降至最低（峰浓度：-0.062 vs. -0.273 mg/l；谷浓度：-0.006 vs. -0.161 mg/l）。两组参数的平均绝对误差（准确性）相似。群体参数和贝叶斯预测观察到的准确性表明，新生儿和婴幼儿血清庆大霉素浓度的监测可以降至最低。
