Department of Clinical Pharmacology, Medical University of Vienna, Vienna, Austria.
Clin Pharmacokinet. 2022 May;61(5):593-617. doi: 10.1007/s40262-021-01102-1. Epub 2022 Feb 25.
The pathophysiology of sepsis alters drug pharmacokinetics, resulting in inadequate drug exposure and target-site concentration. Suboptimal exposure leads to treatment failure and the development of antimicrobial resistance. Therefore, we seek to optimize antimicrobial therapy in sepsis by selecting the right drug and the correct dosage. A prerequisite for achieving this goal is characterization and understanding of the mechanisms of pharmacokinetic alterations. However, most infections take place not in blood but in different body compartments. Since tissue pharmacokinetic assessment is not feasible in daily practice, we need to tailor antibiotic treatment according to the specific patient's pathophysiological processes. The complex pathophysiology of sepsis and the ineffectiveness of current targeted therapies suggest that treatments guided by biomarkers predicting target-site concentration could provide a new therapeutic strategy. Inflammation, endothelial and coagulation activation markers, and blood flow parameters might be indicators of impaired tissue distribution. Moreover, hepatic and renal dysfunction biomarkers can predict not only drug metabolism and clearance but also drug distribution. Identification of the right biomarkers can direct drug dosing and provide timely feedback on its effectiveness. Therefore, this might decrease antibiotic resistance and the mortality of critically ill patients. This article fills the literature gap by characterizing patient biomarkers that might be used to predict unbound plasma-to-tissue drug distribution in critically ill patients. Although all biomarkers must be clinically evaluated with the ultimate goal of combining them in a clinically feasible scoring system, we support the concept that the appropriate biomarkers could be used to direct targeted antibiotic dosing. ADAMTS-13 a disintegrin-like and metalloprotease with thrombospondin type 1 motif no. 13, ALAT alanine amino transferase, APACHE IV Acute Physiology and Chronic Health Evaluation-IV, aPPT activated partial thromboplastin time, ASAT aspartate amino transferase, AT antithrombin, Ca-V-O oxygen content difference, arterial-venous, CRP C-reactive protein, ELAM endothelial leukocyte adhesion molecule, ICAM intercellular adhesion molecule, IL interleukin, INR international normalized ratio, LBP lipopolysaccharide-binding protein, MCP monocyte chemoattractant protein, mHLA monocytic human leukocyte antigen, MIF migration inhibitory factor, MIP macrophage inflammatory protein, PAI plasminogen activator inhibitor, PCO partial pressure of carbon dioxide, PT prothrombin time, RRT renal replacement therapy, SAPSS III Simplified Acute Physiology Score-III, sO oxygen saturation, SOFA Sequential [Sepsis-related] Organ Failure Assessment, sTREM soluble triggering receptor expressed on myeloid cells 1, TLR toll-like receptor, TNF tumor necrosis factor, VCAM vascular cell adhesion molecule, VEGF vascular endothelial growth factor, vWf von Willebrand factor.
脓毒症的病理生理学改变了药物的药代动力学,导致药物暴露不足和靶位浓度降低。药物暴露不足会导致治疗失败和抗菌药物耐药性的产生。因此,我们试图通过选择合适的药物和正确的剂量来优化脓毒症的抗菌治疗。实现这一目标的前提是对药代动力学改变机制进行描述和理解。然而,大多数感染不是发生在血液中,而是发生在不同的身体部位。由于组织药代动力学评估在日常实践中不可行,因此我们需要根据特定患者的病理生理过程来调整抗生素治疗。脓毒症的复杂病理生理学和当前靶向治疗的无效性表明,基于预测靶位浓度的生物标志物指导的治疗可能提供一种新的治疗策略。炎症、内皮和凝血激活标志物以及血流参数可能是组织分布受损的指标。此外,肝肾功能生物标志物不仅可以预测药物代谢和清除,还可以预测药物分布。识别合适的生物标志物可以指导药物剂量,并及时反馈其疗效。因此,这可能会降低危重病患者的抗生素耐药性和死亡率。本文通过描述可能用于预测危重病患者游离血浆与组织药物分布的患者生物标志物,填补了文献空白。虽然所有的生物标志物都必须经过临床评估,最终目标是将它们结合到一个临床可行的评分系统中,但我们支持这样一种概念,即合适的生物标志物可以用于指导靶向抗生素剂量。ADAMTS-13 a 型血小板反应蛋白 13,ALAT 丙氨酸氨基转移酶,APACHE IV 急性生理学和慢性健康评估-IV,aPPT 活化部分凝血活酶时间,ASAT 天冬氨酸氨基转移酶,AT 抗凝血酶,Ca-V-O 氧含量差,动静脉,CRP C 反应蛋白,ELAM 内皮白细胞黏附分子,ICAM 细胞间黏附分子,IL 白细胞介素,INR 国际标准化比值,LBP 脂多糖结合蛋白,MCP 单核细胞趋化蛋白,mHLA 单核细胞人白细胞抗原,MIF 迁移抑制因子,MIP 巨噬细胞炎症蛋白,PAI 纤溶酶原激活物抑制剂,PCO 二氧化碳分压,PT 凝血酶原时间,RRT 肾脏替代治疗,SAPSS III 简化急性生理学评分-III,sO 氧饱和度,SOFA 序贯器官衰竭评估,sTREM 可溶性髓系细胞触发受体 1,TLR toll 样受体,TNF 肿瘤坏死因子,VCAM 血管细胞黏附分子,VEGF 血管内皮生长因子,vWf 血管性血友病因子。