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一种在急性临床环境中预测苯妥英水平的方法。

A method for prediction of phenytoin levels in the acute clinical setting.

作者信息

Scheyer R D, Mattson R H

机构信息

Department of Veterans Affairs Medical Center, Neurology Service, West Haven, Connecticut 06516.

出版信息

Comput Biomed Res. 1991 Dec;24(6):564-75. doi: 10.1016/0010-4809(91)90040-4.

Abstract

Phenytoin (PHT) administration is complicated by saturation kinetics within the therapeutic range, causing marked changes in drug concentration with small changes in dose. The "half-life" increases with concentration, varying from 8-24 hr up to weeks, making it difficult to obtain the steady state levels needed by most prediction algorithms and nomograms. A Bayesian prediction program (Epidose) is presented which explicitly models PHT absorption and elimination kinetics in the non-steady state. The algorithm accounts for the interdependency of closely spaced sequential samples. Estimates of future PHT concentration were made on 20 hospital inpatients, most of whom were acutely ill and received other medications. Future (mean = 4 day) PHT concentrations were predicted over a range from 4 to 22 micrograms/ml (mean 13.9 micrograms/ml) with a median absolute error of 1.0 microgram/ml. These data demonstrate that the program can be used for accurate PHT concentration predictions in sick patients.

摘要

苯妥英(PHT)给药因治疗范围内的饱和动力学而变得复杂,剂量的微小变化会导致药物浓度发生显著变化。“半衰期”随浓度增加,从8 - 24小时到数周不等,这使得难以获得大多数预测算法和列线图所需的稳态水平。本文介绍了一种贝叶斯预测程序(Epidose),该程序明确模拟了非稳态下PHT的吸收和消除动力学。该算法考虑了紧密间隔的连续样本之间的相互依赖性。对20名住院患者的未来PHT浓度进行了估计,其中大多数患者病情严重且正在接受其他药物治疗。预测未来(平均 = 4天)PHT浓度范围为4至22微克/毫升(平均13.9微克/毫升),中位绝对误差为1.0微克/毫升。这些数据表明,该程序可用于准确预测患病患者的PHT浓度。

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