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OBJECTIVE: To explore the application of therapy drug monitoring of imipenem in ICU, and to provide evidence for the use of imipenem in critically ill patients. METHODS: A cross-sectional survey was conducted to collect clinical data of 67 patients receiving therapeutic drug monitoring of imipenem in ICU from January 1, 2016 to December 31, 2018. Using SPSS21.0 statistical software, 71 cases of therapeutic drug monitoring data (blood drug concentration, f%T>MIC) and related clinical data were analyzed. RESULTS: Of all 71 cases of therapeutic drug monitoring, there are 37 cases (52.11%) f%TMIC≥40%,26 cases(36.62%)f%TMIC70%,and 10 cases(14.08%) f%TMIC=100%. f%TMIC of all cases with 0.25 g q6h were 70%. Among other dosage regimens, the highest proportion of f%T>MIC>40% was 1 g q12h (66.67%) and the highest proportion of f%T>MIC>70% was 0.5 g q8h(43.59%). According to different f%T>MIC, those patients were divided into ≤40% group, >40%-70% group and>70%group. Only group>70% showed a downward trend in the infection index of patients before and after medication. The body temperature decreased significantly (P=0.004), while the average PCT level of group MIC>70% group showed a downward trend in serum creatinine after treatment, but there was no significant difference (P=0.285). The serum drug concentration in CRRT group was slightly higher than that in non-CRRT group, and there was no significant difference in f%T>MIC (P=0.376, P=0.209, P=0.988). CONCLUSION: The level of f%T>MIC of imipenem in ICU is unsatisfactory. For critically ill patients, when imipenem f%T>MIC>70%, the antimicrobial effect is better.
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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.
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Objective To simplify the calculation of T>MIC and evaluate meropenem regimens based on the simple mathematical model of T>MIC reported in literature for two-compartment model.Methods Six meropenem regimens were designed according to the recommended dose with the infusion duration of 0.5 h and 3 h.Four different MIC susceptibility breakpoint of meropenem against clinical microbiologic flora were used to formulate different T>MIC.Each T>MIC was calculated by both the simple and two-compartment model of T>MIC.Meropenem regimens were evaluated for different bacterial infections based on the simple model of T>MIC with 40%~100% of the T>MIC% as the target.The t-test suggested no significant difference between the pairs of T>MIC calculated by the two models.Results and Conclusion Simple model of T>MIC can replace the two-compartment model.Meropenem regimens can be optimized based on this simple model of T>MIC conveniently and quickly.