Department of Pharmacological and Pharmaceutical Sciences, University of Houston College of Pharmacy, Houston, TX, USA.
Department of Pharmacy Practice and Translational Research, University of Houston College of Pharmacy, Houston, TX, USA.
Clin Microbiol Infect. 2019 Sep;25(9):1154.e9-1154.e14. doi: 10.1016/j.cmi.2019.01.003. Epub 2019 Jan 18.
Extended-spectrum β-lactamases (ESBLs) present a serious challenge in the treatment of Gram-negative bacterial infections. ESBLs mediate resistance to most β-lactams, which may be reversed with the addition of an active β-lactamase inhibitor (such as tazobactam, relebactam and avibactam). However, various ESBLs may exhibit different susceptibilities to these inhibitors, which could impact efficacy. We proposed a framework for comparing the efficacy of these inhibitors when combined with the same β-lactam.
Three clinical isolates of Klebsiella pneumoniae harbouring CTX-M-15 and one Escherichia coli isolate with SHV-12 were examined. Piperacillin MICs were determined by broth dilution using escalating concentrations of tazobactam, relebactam and avibactam. The resulting MICs were characterized as response to inhibitor concentrations using an inhibitory sigmoid E model. Using the best-fit parameter values, the model was conditioned with fluctuating inhibitor concentrations to simulate instantaneous MIC profiles for each isolate-inhibitor pair. Using a simulated exposure of 4 g piperacillin every 8 h, %fT > MIC was estimated for each piperacillin/inhibitor combination. A hollowfibre infection model was subsequently used to validate the predicted effectiveness of selected combinations.
In all scenarios, piperacillin MIC reductions were well characterized with increasing inhibitor concentrations. As predicted by %fT > MIC, combining piperacillin with avibactam (61.4%-73.6%) was found to be superior to tazobactam (13.5%-44.5%) for suppressing bacterial growth over time.
We illustrated a practical approach to compare the performance of different inhibitors. This platform may be used clinically to identify the optimal pairing of various β-lactams and β-lactamase inhibitors for individual isolates producing ESBLs.
超广谱β-内酰胺酶（ESBLs）对革兰氏阴性菌感染的治疗构成严重挑战。ESBLs 介导对大多数β-内酰胺类药物的耐药性，而添加有效的β-内酰胺酶抑制剂（如他唑巴坦、雷利巴坦和阿维巴坦）可以逆转这种耐药性。然而，不同的 ESBLs 可能对这些抑制剂的敏感性不同，这可能会影响疗效。我们提出了一种比较这些抑制剂与相同β-内酰胺类药物联合使用时疗效的框架。
检测了三株携带 CTX-M-15 的肺炎克雷伯菌临床分离株和一株携带 SHV-12 的大肠埃希菌。采用肉汤稀释法，用递增浓度的他唑巴坦、雷利巴坦和阿维巴坦测定哌拉西林 MIC。用抑制型 sigmoid E 模型描述 MIC 与抑制剂浓度的关系。用最佳拟合参数值对模型进行处理，用波动的抑制剂浓度对每个分离株-抑制剂对进行瞬时 MIC 谱模拟。模拟 4 g 哌拉西林每 8 小时给药 1 次的暴露情况，计算每个哌拉西林/抑制剂组合的%fT>MIC。随后使用中空纤维感染模型验证所选组合的预测有效性。
在所有情况下，随着抑制剂浓度的增加，哌拉西林 MIC 降低均得到很好的描述。根据%fT>MIC 的预测，与他唑巴坦（13.5%-44.5%）相比，哌拉西林与阿维巴坦（61.4%-73.6%）联合使用可随着时间的推移更好地抑制细菌生长。
我们展示了一种比较不同抑制剂性能的实用方法。该平台可用于临床，为个体产生 ESBLs 的分离株确定各种β-内酰胺类药物和β-内酰胺酶抑制剂的最佳组合。
