Individualised antibiotic dosing for patients who are critically ill: challenges and potential solutions.
Individualised antibiotic dosing for patients who are critically ill: challenges and potential solutions.
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DOI：
10.1016/s1473-3099(14)70036-2
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发表时间：
2014-06
影响因子：
56.3
通讯作者：
Kuti, Joseph L.
中科院分区：
文献类型：
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作者：
Roberts, Jason A.;Abdul-Aziz, Mohd H.;Lipman, Jeffrey;Mouton, Johan W.;Vinks, Alexander A.;Felton, Timothy W.;Hope, William W.;Farkas, Andras;Neely, Michael N.;Schentag, Jerome J.;Drusano, George;Frey, Otto R.;Theuretzbacher, Ursula;Kuti, Joseph L.
重症患者的感染与持续不良的临床结局相关。这些患者具有严重改变和可变的抗生素药代动力学，并且被较不敏感的病原体感染。不考虑这些特征的抗生素剂量可能导致次优结果。在本文中，我们回顾了导致抗生素剂量不足的患者和病原体相关挑战，并讨论了如何实施个性化抗生素治疗过程，以提高剂量的准确性，以进一步优化危重患者的护理。优化抗生素给药的过程首先需要确定患者中可能改变抗生素浓度的生理紊乱，包括液体状态改变、微血管衰竭、血清白蛋白浓度以及肾功能和肝功能改变。其次，应通过与微生物实验室联系确定感染病原体的敏感性知识。然后可以通过将敏感性数据与测量的抗生素浓度数据（在可能的情况下）结合到临床给药软件中来解决患者和病原体挑战。该软件使用来自重症患者的药代动力学-药效学（PK/PD）模型来准确预测个体患者的给药需求，目的是优化抗生素暴露并最大化有效性。
Infections in critically ill patients are associated with persistently poor clinical outcomes. These patients have severely altered and variable antibiotic pharmacokinetics and are infected by less susceptible pathogens. Antibiotic dosing that does not account for these features is likely to result in sub-optimal outcomes. In this paper, we review the patient- and pathogen-related challenges that contribute to inadequate antibiotic dosing and discuss how a process for individualised antibiotic therapy, that increases the accuracy of dosing, can be implemented to further optimise care for the critically ill patient. The process for optimised antibiotic dosing firstly requires determination of the physiological derangements in the patient that can alter antibiotic concentrations including altered fluid status, microvascular failure, serum albumin concentrations as well as altered renal and hepatic function. Secondly, knowledge of the susceptibility of the infecting pathogen should be determined through liaison with the microbiology laboratory. The patient and pathogen challenges can then be solved by combining susceptibility data with measured antibiotic concentration data (where possible) into a clinical dosing software. Such software uses pharmacokinetic-pharmacodynamic (PK/PD) models from critically ill patients to accurately predict the dosing requirements for the individual patient with the aim of optimising antibiotic exposure and maximising effectiveness.