Title |
The Epidemiologic and Pharmacodynamic Cutoff Values of Tilmicosin against Haemophilus parasuis
|
---|---|
Published in |
Frontiers in Microbiology, March 2016
|
DOI | 10.3389/fmicb.2016.00385 |
Pubmed ID | |
Authors |
Peng Zhang, Haihong Hao, Jun Li, Ijaz Ahmad, Guyue Cheng, Dongmei Chen, Yanfei Tao, Lingli Huang, Yulian Wang, Menghong Dai, Zhenli Liu, Zonghui Yuan |
Abstract |
The aim of this study was to establish antimicrobial susceptibility breakpoints for tilmicosin against Haemophilus parasuis, which is an important pathogen of respiratory tract infections. The minimum inhibitory concentrations (MICs) of 103 H. parasuis isolates were determined by the agar dilution method. The wild type (WT) distribution and epidemiologic cutoff value (ECV) were evaluated by statistical analysis. The new bronchoaveolar lavage was used to establish intrapulmonary pharmacokinetic (PK) model in swine. The pharmacokinetic (PK) parameters of tilmicosin, both in pulmonary epithelial lining fluid (PELF) and in plasma, were determined using high performance liquid chromatography method and WinNonlin software. The pharmacodynamic cutoff (COPD) was calculated using Monte Carlo simulation. Our results showed that 100% of WT isolates were covered when the ECV was set at 16 μg/mL. The tilmicosin had concentration-dependent activity against H. parasuis. The PK data indicated that tilmicosin concentrations in PELF was rapidly increased to high levels at 4 h and kept stable until 48 h after drug administration, while the tilmicosin concentration in plasma reached maximum levels at 4 h and continued to decrease during 4-72 h. Using Monte Carlo simulation, COPD was defined as 1 μg/mL. Conclusively, the ECV and COPD of tilmicosin against H. parasuis were established for the first time based on the MIC distribution and PK-PD analysis in the target tissue, respectively. These values are of great importance for detection of tilmicosin-resistant H. parasuis and for effective treatment of clinical intrapulmonary infection caused by H. parasuis. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 23 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 3 | 13% |
Student > Ph. D. Student | 3 | 13% |
Student > Doctoral Student | 2 | 9% |
Student > Master | 2 | 9% |
Lecturer | 1 | 4% |
Other | 3 | 13% |
Unknown | 9 | 39% |
Readers by discipline | Count | As % |
---|---|---|
Veterinary Science and Veterinary Medicine | 6 | 26% |
Agricultural and Biological Sciences | 3 | 13% |
Medicine and Dentistry | 2 | 9% |
Social Sciences | 1 | 4% |
Biochemistry, Genetics and Molecular Biology | 1 | 4% |
Other | 0 | 0% |
Unknown | 10 | 43% |