Schentag J J, Strenkoski-Nix L C, Nix D E, Forrest A
Clinical Pharmacokinetics Laboratory, Millard Fillmore Health System and School of Pharmacy, State University of New York at Buffalo, New York, USA.
Clin Infect Dis. 1998 Jul;27(1):40-6. doi: 10.1086/514621.
Clinical trials show that the area under the inhibitory curve (AUIC) is predictive of antibacterial killing rates in patients with nosocomial pneumonia and is useful for predicting clinical or microbiological outcomes and making dosage adjustments with beta-lactams, quinolones, aminoglycosides, and vancomycin. The AUIC values of two antibiotics are additive, and since antibiotics are often given in combination, determining the AUIC for antibiotic combinations could potentially predict the microbiological outcomes for patients given these combinations. To further address this question, mathematical modeling was used to study in vitro pharmacokinetic and pharmacodynamic interactions of the antimicrobials piperacillin and ciprofloxacin. These agents were also studied in vivo in healthy volunteers. Blood samples were obtained for analysis of serum drug concentrations, and serum inhibitory titers were determined against eight common bacterial pathogens, chosen to reflect the range of MIC values to ciprofloxacin and piperacillin. Additive AUIC relationships predictive of bacterial killing rates were typical in patients given these antibiotics in combination.
临床试验表明，抑制曲线下面积（AUIC）可预测医院获得性肺炎患者的抗菌杀菌率，有助于预测临床或微生物学结局，并用于调整β-内酰胺类、喹诺酮类、氨基糖苷类和万古霉素的剂量。两种抗生素的AUIC值具有相加性，由于抗生素常联合使用，因此确定抗生素联合使用时的AUIC可能有助于预测接受这些联合治疗患者的微生物学结局。为进一步探讨这一问题，采用数学模型研究了抗菌药物哌拉西林和环丙沙星的体外药代动力学和药效学相互作用。还在健康志愿者体内对这些药物进行了研究。采集血样分析血清药物浓度，并针对8种常见细菌病原体测定血清抑制效价，这些病原体的选择反映了环丙沙星和哌拉西林的MIC值范围。联合使用这些抗生素的患者中，预测细菌杀灭率的相加性AUIC关系较为典型。
