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重症患者中多黏菌素早期治疗药物监测的模型指导依据

Model-Informed Rationale for Early Therapeutic Drug Monitoring of Colistin in Critically Ill Patients.

作者信息

Mathew Sumith K, Rao Shoma V, Prabha Ratna, Neely Michael N, Mathew Binu Susan, Aruldhas Blessed Winston, Veeraraghavan Balaji, Kandasamy Subramani

机构信息

Department of Pharmacology and Clinical Pharmacology, Christian Medical College, The Tamilnadu Dr.M.G.R Medical University, Vellore, Chennai, India.

Surgical Intensive Care Unit and Division of Critical Care, Christian Medical College, The Tamilnadu Dr.M.G.R Medical University, Vellore, Chennai, India.

出版信息

J Clin Pharmacol. 2023 Jan;63(1):57-65. doi: 10.1002/jcph.2130. Epub 2022 Aug 24.

Abstract

Adequate colistin exposure is important for microbiological clearance. This study was performed in critically ill patients >18 years old to develop a simplified nonparametric pharmacokinetic (PK) model of colistin for routine clinical use and to determine the role of dose optimization. The Non-Parametric Adaptive Grid algorithm within the Pmetrics software package for R was used to develop a PK model from 47 patients, and external validation of the final model was performed in 13 patients. A 1-compartment multiplicative gamma error model with 0-order input and first-order elimination of colistin was developed with creatinine clearance and serum albumin as covariates on elimination rate constant. An R for observed vs individual predicted colistin concentrations of 0.92 was obtained in the validation cohort. High interindividual variability in colistin steady-state area under the plasma concentration-time curve (AUC) from from 120 hours to 144 hours (coefficient of variation = 80.1%) and a high interoccasion variability (median coefficient of variation of AUC from time 0 to hours predicted every 8 hours for initial 96 hours after starting colistin = 23.8) was predicted in patients who received this antibiotic for a period of over 152 hours (n = 22). With the model-suggested dose regimen, only 20% of simulated profiles achieved AUC from time 0 to 24 hours in the range of 50 to 60 mg • h/L due to high variability in population PK. In this group of patients, steady-state colistin concentrations were predicted to be achieved >96 hours after initiation of colistimethate sodium. This study advocates the need for early and repeated therapeutic drug monitoring and dose optimization in critically ill patients to achieve adequate therapeutic concentration of colistin.

摘要

足够的黏菌素暴露对微生物清除很重要。本研究在18岁以上的危重症患者中进行,以建立一个简化的黏菌素非参数药代动力学(PK)模型用于常规临床应用,并确定剂量优化的作用。使用R语言的Pmetrics软件包中的非参数自适应网格算法,从47例患者中建立PK模型,并在13例患者中对最终模型进行外部验证。建立了一个具有零级输入和一级消除的单室乘性伽马误差模型,以肌酐清除率和血清白蛋白作为消除速率常数的协变量。在验证队列中,观察到的与个体预测的黏菌素浓度的R值为0.92。在接受这种抗生素超过152小时的患者(n = 22)中,预测黏菌素血浆浓度-时间曲线下稳态面积(AUC)从120小时到144小时存在较高的个体间变异性(变异系数 = 80.1%)和较高的个体间变异性(在开始使用黏菌素后的最初96小时内,每8小时预测的从时间0到小时的AUC变异系数中位数 = 23.8)。采用模型建议的给药方案,由于群体PK的高变异性,只有20%的模拟曲线在0至24小时的AUC范围为50至60mg•h/L。在这组患者中,预计在开始使用多黏菌素甲磺酸钠后>96小时达到稳态黏菌素浓度。本研究主张在危重症患者中需要早期和重复的治疗药物监测及剂量优化,以达到足够的黏菌素治疗浓度。

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