Abdulla Alan, Edwina Elma E, Flint Robert B, Allegaert Karel, Wildschut Enno D, Koch Birgit C P, de Hoog Matthijs
Department of Hospital Pharmacy, Erasmus University Medical Center, Rotterdam, Netherlands.
Division of Neonatology, Department of Pediatrics, Sophia Children's Hospital, Erasmus University Medical Center, Rotterdam, Netherlands.
Front Pediatr. 2021 Feb 23;9:624639. doi: 10.3389/fped.2021.624639. eCollection 2021.
Optimal pharmacotherapy in pediatric patients with suspected infections requires understanding and integration of relevant data on the antibiotic, bacterial pathogen, and patient characteristics. Because of age-related physiological maturation and non-maturational covariates (e.g., disease state, inflammation, organ failure, co-morbidity, co-medication and extracorporeal systems), antibiotic pharmacokinetics is highly variable in pediatric patients and difficult to predict without using population pharmacokinetics models. The intra- and inter-individual variability can result in under- or overexposure in a significant proportion of patients. Therapeutic drug monitoring typically covers assessment of pharmacokinetics and pharmacodynamics, and concurrent dose adaptation after initial standard dosing and drug concentration analysis. Model-informed precision dosing (MIPD) captures drug, disease, and patient characteristics in modeling approaches and can be used to perform Bayesian forecasting and dose optimization. Incorporating MIPD in the electronic patient record system brings pharmacometrics to the bedside of the patient, with the aim of a consisted and optimal drug exposure. In this narrative review, we evaluated studies assessing optimization of antibiotic pharmacotherapy using MIPD in pediatric populations. Four eligible studies involving amikacin and vancomycin were identified from 418 records. Key articles, independent of year of publication, were also selected to highlight important attributes of MIPD. Although very little research has been conducted until this moment, the available data on vancomycin indicate that MIPD is superior compared to conventional dosing strategies with respect to target attainment. The utility of MIPD in pediatrics needs to be further confirmed in frequently used antibiotic classes, particularly aminoglycosides and beta-lactams.
对于疑似感染的儿科患者,优化药物治疗需要了解并整合有关抗生素、细菌病原体和患者特征的相关数据。由于与年龄相关的生理成熟以及非成熟协变量(如疾病状态、炎症、器官衰竭、合并症、合并用药和体外系统)的影响,抗生素在儿科患者中的药代动力学差异很大,若不使用群体药代动力学模型则很难预测。个体内和个体间的变异性可能导致相当一部分患者出现药物暴露不足或过量的情况。治疗药物监测通常包括药代动力学和药效学评估,以及在初始标准给药和药物浓度分析后进行的同步剂量调整。模型引导的精准给药(MIPD)在建模方法中纳入了药物、疾病和患者特征,可用于进行贝叶斯预测和剂量优化。将MIPD纳入电子病历系统可将药物计量学应用于患者床边,目的是实现持续且最佳的药物暴露。在这篇叙述性综述中,我们评估了在儿科人群中使用MIPD评估抗生素药物治疗优化的研究。从418条记录中确定了四项涉及阿米卡星和万古霉素的符合条件的研究。还选择了与发表年份无关的关键文章,以突出MIPD的重要属性。尽管到目前为止进行的研究很少,但关于万古霉素的现有数据表明,在目标达成方面,MIPD优于传统给药策略。MIPD在儿科中的实用性需要在常用的抗生素类别中进一步得到证实,尤其是氨基糖苷类和β-内酰胺类。