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个人计算机软件系统生成的血清庆大霉素浓度预测的准确性。

Accuracy of serum gentamicin concentration predictions generated by a personal-computer software system.

作者信息

Robinson J D, Hatton R C, Russell W L, Klapp D, Lopez L M

出版信息

Clin Pharm. 1984 Sep-Oct;3(5):509-16.

PMID:6548429
Abstract

Predictions of serum gentamicin concentration and half-life, using a personal-computer software system (SIMKIN [simulated kinetics]), were compared for accuracy as increasing amounts of patient-specific data were supplied to the computer. Data for a two-year period were collected for patients of a hospital's pharmacokinetic consultation service; the study group included adults who had at least one serum concentration for which time of last gentamicin dose was recorded. Input variables were age, weight, height, sex, serum creatinine concentration, concomitant drugs and diseases, gentamicin dosage, time of infusion, dosing interval, number of doses on each regimen, and time and reported value of all serum gentamicin concentrations. Individualized dosing regimens were calculated on the basis of literature estimates, and half-life and serum concentrations were then estimated for these regimens and compared with actual values. One or two measured serum concentrations were then added to the input data. The computer-estimated half-lives (obtained from single-point or two-point analysis in different dosage intervals) were compared with the half-lives determined from actual serum concentration data. Gentamicin serum concentrations were similarly compared. The computer's ability to predict subsequent serum concentrations improved in sequence for literature-averaged prediction and single-point and multipoint analysis. Accuracy of predicting whether peak concentrations were therapeutic or subtherapeutic and whether trough concentrations were toxic also improved as more patient-specific data were input. SIMKIN appropriately evaluated demographic and laboratory data and adequately predicted gentamicin half-lives and serum concentrations.

摘要

使用个人计算机软件系统(SIMKIN[模拟动力学])预测血清庆大霉素浓度和半衰期,并随着输入计算机的患者特异性数据量增加,比较预测的准确性。收集了一家医院药代动力学咨询服务部门两年期间患者的数据;研究组包括至少有一次血清浓度记录且记录了最后一剂庆大霉素给药时间的成年人。输入变量包括年龄、体重、身高、性别、血清肌酐浓度、合并用药和疾病、庆大霉素剂量、输注时间、给药间隔、每种给药方案的剂量数,以及所有血清庆大霉素浓度的时间和报告值。根据文献估计计算个体化给药方案,然后估计这些方案的半衰期和血清浓度,并与实际值进行比较。然后将一或两个测量的血清浓度添加到输入数据中。将计算机估计的半衰期(在不同给药间隔通过单点或两点分析获得)与根据实际血清浓度数据确定的半衰期进行比较。庆大霉素血清浓度也进行类似比较。计算机预测后续血清浓度的能力在文献平均预测、单点和多点分析中依次提高。随着输入更多患者特异性数据,预测峰值浓度是否具有治疗效果或低于治疗效果以及谷浓度是否有毒性的准确性也有所提高。SIMKIN适当地评估了人口统计学和实验室数据,并充分预测了庆大霉素的半衰期和血清浓度。

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