OBJECTIVE To compare and evaluate different methods of estimating %T>MIC based on drug concentration monitoring data, and clarify the implementation plan and treatment objectives of therapeutic drug monitoring. METHODS The plasma drug concentrations of 25 patients with severe infections were collected at multiple time points after imipenem reached steady state. A population pharmacokinetic model was established by NONMEM method. The plasma drug concentrations were estimated by Bayesian feedback method at 6 and 8 h after imipenem administration. Meanwhile, the established calculation model of %T>MIC combined with the same drug concentrations was used to estimate the %T>MIC. The results of these two methods were compared with the true value of %T>MIC. RESULTS The established population pharmacokinetic model could fit the data well. The covariate serum creatinine (CR) had a significant effect on the apparent distribution volume (Vc) of central ventricle. The final model was Vc=18.8×(CR/70.9)ΘCR_VC. When MIC=2, the results of Bayesian method and %T>MIC calculation model method showed 76.9% and 84.6% deviation within±10% of the true values, respectively. CONCLUSION The two methods had good predictive accuracy when the MIC breakpoint was less than 2, but they decreased with the increase of MIC. Different therapeutic drug monitoring schemes should be considered for different levels of MIC.
陈文倩, 张竹, 张丹, 杜雯雯, 詹庆元, 张相林, 李朋梅. 重症患者中根据亚胺培南治疗药物监测结果进行%T>MIC预测方法的比较研究[J]. 中国药学杂志, 2020, 55(9): 755-759.
CHEN Wen-qian, ZHANG Zhu, ZHANG Dan, DU Wen-wen, ZHAN Qing-yuan, ZHANG Xiang-lin, LI Peng-mei. A Comparative Study on Predicting %T>MIC Imipenem based on Therapeutic Drug Monitoring Results in Critically Care Patients. Chinese Pharmaceutical Journal, 2020, 55(9): 755-759.
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2020, Vol. 55 
