The effects of intranasal esketamine (84 mg) and oral mirtazapine (30 mg) on on-road driving performance: a double-blind, placebo-controlled study

Psychopharmacology(2017)

引用 23|浏览14
暂无评分
摘要
Rationale The purpose of this study is to evaluate the single dose effect of intranasal esketamine (84 mg) compared to placebo on on-road driving performance. Mirtazapine (oral, 30 mg) was used as a positive control, as this antidepressant drug is known to negatively affect driving performance. Methods Twenty-six healthy volunteers aged 21 to 60 years were enrolled in this study. In the evening, 8 h after treatment administration, participants conducted the standardized 100-km on-road driving test. Primary outcome measure was the standard deviation of lateral position (SDLP), i.e., the weaving of the car. Mean lateral position, mean speed, and standard deviation of speed were secondary outcome measures. For SDLP, non-inferiority analyses were conducted, using +2.4 cm (relative to placebo) as a predefined non-inferiority margin for clinical relevant impairment. Results Twenty-four participants completed the study. No significant SDLP difference was found between esketamine and placebo ( p = 0.7638), whereas the SDLP after mirtazapine was significantly higher when compared to placebo ( p = 0.0001). The upper limit of the two-sided 95% confidence interval (CI) of the mean difference between esketamine and placebo was +0.86 cm, i.e., <+2.4 cm, thus demonstrating that esketamine was non-inferior to placebo. Non-inferiority could not be concluded for mirtazapine (+3.15 cm SDLP relative to placebo). No significant differences in mean speed, standard deviation of speed, and mean lateral position were observed between the active treatments and placebo. Conclusions No significant difference in driving performance was observed 8 h after administering intranasal esketamine (84 mg) or placebo. In contrast, oral mirtazapine (30 mg) significantly impaired on road driving performance.
更多
查看译文
关键词
Driving,SDLP,Esketamine,Mirtazapine,Depression
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要