Boothe Dawn Merton
Department of Anatomy, Physiology, Pharmacology, Auburn University, Auburn, AL 36849, USA.
J Vet Emerg Crit Care (San Antonio). 2010 Feb;20(1):110-31. doi: 10.1111/j.1476-4431.2009.00509.x.
The need for immediate, effective antimicrobial therapy in the critical care patient must be tempered by approaches which simultaneously minimize emergence of antimicrobial resistance. Ideally, therapy will successfully resolve clinical signs of infection, while eradicating infecting pathogens such that the risk of resistance is avoided. Increasing limitations associated with empirical antimicrobial choices direct the need for culture and susceptibility data as a basis of therapy. Even so, such in vitro data should be utilized within its limitations.
To demonstrate the attributes and limitations of patient and population culture and susceptibility (pharmacodynamic) data in the selection of antimicrobial drugs and to demonstrate the design of individualized dosing regimens based on integration of pharmacodynamic (PD) and pharmacokinetic (PK) data.
Limitations in culture and susceptibility testing begin with sample collection and continue through drug selection and dose design. Among the challenges in interpretation is discrimination between pathogens and commensals. Properly collected samples are critical for generation of data relevant to the patient's infection. Data are presented as minimum inhibitory concentrations (MICs). The MIC facilitate selection of the most appropriate drug, particularly when considered in the context of antimicrobial concentrations achieved in the patient at a chosen dose. Integration of MIC data with key PK data yields the C(max):MIC important to efficacy of concentration-dependent drugs and T>MIC, which guides use of time-dependent drugs. These indices are then used to design dosing regimens that are more likely to kill all infecting pathogens. In the absence of patient MIC data, population data (eg, MIC(90)) may serve as a reasonable surrogate.
Properly collected, performed, and interpreted culture and susceptibility data are increasingly important in the selection of and design of dosing regimens for antimicrobial drugs. Integration of PK and PD data as modified by host and microbial factors supports a hit hard, exit fast approach to therapy that will facilitate efficacy while minimizing resistance.
在重症监护患者中，立即进行有效抗菌治疗的需求必须通过同时尽量减少抗菌药物耐药性出现的方法来加以权衡。理想情况下，治疗应能成功消除感染的临床症状，同时根除感染病原体，从而避免耐药风险。与经验性抗菌药物选择相关的限制日益增加，这就需要将培养和药敏数据作为治疗的基础。即便如此，此类体外数据也应在其局限性范围内使用。
阐述患者及群体培养和药敏（药效学）数据在抗菌药物选择中的特性和局限性，并展示基于药效学（PD）和药代动力学（PK）数据整合的个体化给药方案设计。
培养和药敏试验的局限性始于样本采集，并贯穿药物选择和剂量设计过程。解释过程中的挑战之一是区分病原体和共生菌。正确采集的样本对于生成与患者感染相关的数据至关重要。数据以最低抑菌浓度（MIC）表示。MIC有助于选择最合适的药物，尤其是在考虑特定剂量下患者体内达到的抗菌药物浓度时。将MIC数据与关键PK数据整合可得出对浓度依赖性药物疗效重要的C(max):MIC以及指导时间依赖性药物使用的T>MIC。然后利用这些指标设计更有可能杀灭所有感染病原体的给药方案。在缺乏患者MIC数据时，群体数据（如MIC(90)）可作为合理替代。
正确采集、执行和解释的培养和药敏数据在抗菌药物选择和给药方案设计中越来越重要。整合受宿主和微生物因素影响的PK和PD数据支持一种“重拳出击、快速撤离”的治疗方法，这将有助于提高疗效同时尽量减少耐药性。
