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抗菌作用及药代动力学/药效学:运用AUIC提高疗效并避免耐药性。

Antimicrobial action and pharmacokinetics/pharmacodynamics: the use of AUIC to improve efficacy and avoid resistance.

作者信息

Schentag J J

机构信息

State University of New York at Buffalo School of Pharmacy, 14209, USA.

出版信息

J Chemother. 1999 Dec;11(6):426-39. doi: 10.1179/joc.1999.11.6.426.

DOI:10.1179/joc.1999.11.6.426
PMID:10678784
Abstract

In in-vitro and in animal models, antibiotics show good relationships between concentration and response, when response is quantified as the rate of bacterial eradication. The strength of these in-vitro relationships promises their utility for dosage regimen design and predictable cure of human infections. Resistance is also predictable from these parameters, fostering a rational means of using dosing adjustments to avoid or minimize the development of resistant organisms. Newly developed computerized methods for the quantitation of susceptibility allow testing of integrated kinetic-susceptibility models in patients. Our attention has focused recently on fluoroquinolones, since they are relatively non-toxic and provide the necessary range of dosage needed to elucidate correlations between concentration and response in the Intensive Care Unit patient. Studies conducted in patients with nosocomial gram-negative pneumonia reveal good correlations between bacterial eradication and integration of concentration with bacterial susceptibility. In patients, the best correlation parameters are time over MIC, and the ratio of 24-hour AUC to MIC (AUIC). Patients with serious infections like nosocomial pneumonia require bactericidal antimicrobial activity. Studies in our laboratory demonstrate that the minimum effective antimicrobial action is an area under the inhibitory titer (AUIC) of 125, where AUIC is calculated as the 24-hour serum AUC divided by the MIC of the pathogen. This target AUIC may be achieved with either a single antibiotic or it can be the sum of AUIC values of two or more antibiotics. There is considerable variability in the actual AUIC value for patients when antibiotics are given in their usually recommended dosages. Examples of this variance will be provided using aminoglycosides, fluoroquinolones, beta-lactams, macrolides and vancomycin. The achievement of minimally effective antibiotic action, consisting of an AUIC of at least 125, is associated with bacterial eradication in about 7 days for beta-lactams and quinolones. When AUIC is increased to 250, the quinolone ciprofloxacin (which displays in vivo concentration dependent bacterial killing) can eliminate the bacterial pathogen in 1-2 days. Beta lactams, even when dosed to an AUIC of 250, often require longer treatment duration to eliminate the bacterial pathogen, because the in vivo bacterial killing rate is slower with beta-lactams than with the quinolones. This remains true even at AUIC values of 250 for both compounds, which is theoretically identical dosing. Antibiotic activity indices allow clinicians to evaluate individualized patient regimens. Furthermore, antibiotic activity is a predictable clinical endpoint with predictable clinical outcome. This value is also highly predictive of the development of bacterial resistance. Antimicrobial regimens that do not achieve an AUIC of at least 125 cannot prevent the selective pressure that leads to overgrowth of resistant bacterial sub-populations. Indeed, there is considerable anxiety that conventional respiratory tract infection management strategies, which prescribe antibacterial dosages that may attain AUIC values below 125, are contributing to the pandemic rise in bacterial resistance levels.

摘要

在体外和动物模型中,当将反应量化为细菌根除率时,抗生素显示出浓度与反应之间的良好关系。这些体外关系的强度预示着它们在剂量方案设计和人类感染的可预测治愈方面的效用。从这些参数中也可以预测耐药性,这促进了一种合理的方法,即通过调整剂量来避免或最小化耐药菌的产生。新开发的用于定量药敏性的计算机化方法允许在患者中测试综合动力学-药敏性模型。我们最近的注意力集中在氟喹诺酮类药物上,因为它们相对无毒,并且提供了阐明重症监护病房患者浓度与反应之间相关性所需的必要剂量范围。对医院获得性革兰氏阴性肺炎患者进行的研究表明,细菌根除与浓度与细菌药敏性的综合之间存在良好的相关性。在患者中,最佳的相关参数是高于最低抑菌浓度(MIC)的时间,以及24小时曲线下面积(AUC)与MIC的比值(AUIC)。患有医院获得性肺炎等严重感染的患者需要杀菌抗菌活性。我们实验室的研究表明,最小有效抗菌作用是抑制效价曲线下面积(AUIC)为125,其中AUIC计算为24小时血清AUC除以病原体的MIC。这个目标AUIC可以通过单一抗生素实现,也可以是两种或更多种抗生素的AUIC值之和。当按照通常推荐的剂量给予抗生素时,患者实际的AUIC值存在相当大的变异性。将使用氨基糖苷类、氟喹诺酮类、β-内酰胺类、大环内酯类和万古霉素来提供这种变异性的例子。实现由至少125的AUIC组成的最小有效抗生素作用与β-内酰胺类和喹诺酮类药物在约7天内根除细菌有关。当AUIC增加到250时,喹诺酮类环丙沙星(其在体内显示浓度依赖性细菌杀灭作用)可以在1-2天内消除细菌病原体。β-内酰胺类药物,即使剂量达到AUIC为250,通常也需要更长的治疗时间来消除细菌病原体,因为β-内酰胺类药物在体内的细菌杀灭率比喹诺酮类药物慢。即使两种化合物的AUIC值都为250,理论上给药相同,情况仍然如此。抗生素活性指数使临床医生能够评估个体化的患者治疗方案。此外,抗生素活性是一个可预测的临床终点,具有可预测的临床结果。这个值对细菌耐药性的发展也具有高度预测性。未达到至少125的AUIC的抗菌治疗方案无法防止导致耐药细菌亚群过度生长的选择压力。事实上,人们相当担心,规定抗菌剂量可能导致AUIC值低于125的传统呼吸道感染管理策略正在导致细菌耐药水平的全球性上升。

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