Antimicrobial resistance, a major threat to human health, is mainly driven by the overuse of antimicrobials. The purpose of this study was to further investigate the relationship between antimicrobial use and resistance with a 15-year record in Southwest hospital, one of the largest hospitals in Southwest China and a university affiliated hospital, thus to further predict the antimicrobial resistance in an autoregressive integrated moving average (ARIMA) manner. Kirby-Bauer tests were carried out to figure out the drug sensitivity of Gram-negative bacterial. Antimicrobials (β-lactamase inhibitor complex, aminoglycosides, quinolones, third and fourth-generation cephalosporins, carbapenems, cephamycins, oxacephems, and sulfonamides) consumption were calculated according to World Health Organization (WHO) anatomical therapeutic chemical classification index and expressed as annual defined daily dose (DDD) or DDD per 1000 out patients. Resistance rates of levofloxacin-resistant Escherichia coli, ceftazidime-resistant Klebsiella pneumoniae, amikacin-resistant Bacterium levans, imipenem-resistant Pseudomonas aeruginosa is positively correlated with the usage of aminoglycosides and quinolones; resistance rates of imipenem-resistant Acinetobacter baumanii is positively correlated with the usage of carbapenemes (P-value between the drug resistance of levofloxacin-resistant E. coli, ceftazidime-resistant K. pneumoniae and the usage of aminoglycosides is under .05, the other P-value are under .01); resistance rates of the drug resistance of levofloxacin-resistant E. coli is positively correlated with the usage of oxacephems (P < .01); resistance rates of imipenem-resistant P. aeruginosa is positively correlated with the usage of oxacephems and sulfonamides (P < .01). The present study presents one of the largest and longest retrospective analyses in China between antimicrobial consumption and antimicrobial resistance. Change of the usage of several antibacterial drugs has great influence on the drug resistance of Gram-negative bacterial. Of particular, ARIMA forecasting revealed that carbapenem related bacterial resistance should be closely watched.

To develop a population-based pharmacokinetic model for the oral antiepileptic drug zonisamide using a cohort of healthy (nonepileptic) subjects and evaluate the effect of individual factors on the pharmacokinetics of zonisamide. 30 young adults (21-39 years) in good health were randomly assigned to 3 equal groups (1:1 sex ratio) for single-dose administration of zonisamide at 200 mg, 300 mg, or 400 mg. An additional 9 subjects (22-24 years) were administered once daily zonisamide at 300 mg for 14 days, and comprised the multiple dosing group. Venous blood samples were collected for analysis prior to (baseline, 0 hours) and after (1-300 hours) drug administration, providing 607 total samples used to build the pharmacokinetic model. The population pharmacokinetic analysis was performed by ICON's nonlinear mixed-effect modeling (NONMEM) software. Validation of the final model was carried out by nonparametric bootstrapping and visual predictive check. The zonisamide pharmacokinetics was best described by a two-compartment model with first-order elimination. In the final model, the estimated value of clearance (CL) was 23.25 L/h, the volume of distribution of the central compartment (Vc) was 34.50 L, the intercompartmental clearance (Q) was 20.22 L/h, and the Ka was 0.026 h(-1). The peripheral volume of distribution (Vp) was 1,429 L for single dose and 1,003 L for multiple doses. Body weight was the significant covariate affecting CL, Vc, Vp, and Q. Otherwise, female subjects had a lower Q than male subjects. The pharmacokinetics of zonisamide after oral administration could be described using a linear first-order elimination two-compartment model, which may provide a reference for clinical use of zonisamide in Chinese adults.