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利用体内结合参数预测游离血清丙戊酸浓度

Prediction of unbound serum valproic acid concentration by using in vivo binding parameters.

作者信息

Kodama Y, Kuranari M, Tsutsumi K, Kimoto H, Fujii I, Takeyama M

机构信息

Department of Clinical Pharmacy, Oita Medical University, Japan.

出版信息

Ther Drug Monit. 1992 Oct;14(5):349-53. doi: 10.1097/00007691-199210000-00001.

DOI:10.1097/00007691-199210000-00001
PMID:1448839
Abstract

In a previous study, we determined the in vivo binding parameters of valproic acid (VPA) to serum proteins in seven healthy young adults at steady state by using the Scatchard equation. To evaluate the ability of the Scatchard binding equation to predict steady-state unbound serum VPA concentrations (Cf), 39 adult patients receiving VPA monotherapy and ranging in age from 16 to 68 years were studied. The correlation between predicted and observed Cf was high (r = 0.865). Mean prediction error, mean absolute error (MAE), and root mean squared error (RMSE) were calculated, and served as a measure of prediction bias and precision. The MAE and RMSE were low (MAE = 12.9 mumol/L, RMSE = 17.7 mumol/L). It is feasible to use the Scatchard binding equation to predict Cf in patients receiving VPA monotherapy.

摘要

在之前的一项研究中,我们通过使用Scatchard方程,测定了7名处于稳态的健康年轻成年人中丙戊酸(VPA)与血清蛋白的体内结合参数。为了评估Scatchard结合方程预测稳态下未结合血清VPA浓度(Cf)的能力,我们研究了39名接受VPA单药治疗、年龄在16至68岁之间的成年患者。预测的Cf与观察到的Cf之间的相关性很高(r = 0.865)。计算了平均预测误差、平均绝对误差(MAE)和均方根误差(RMSE),并将其作为预测偏差和精度的度量。MAE和RMSE较低(MAE = 12.9 μmol/L,RMSE = 17.7 μmol/L)。使用Scatchard结合方程预测接受VPA单药治疗患者的Cf是可行的。

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