OFF-Times Before, During, and After Nighttime Sleep Periods in Parkinson’s Disease Patients with Motor Fluctuations and the Effects of Opicapone: A Post Hoc Analysis of Diary Data from BIPARK-1 and -2

Parkinsonism & Related Disorders(2024)

引用 0|浏览1
暂无评分
摘要
Introduction In BIPARK-1 and BIPARK-2, addition of once-daily opicapone to levodopa/carbidopa significantly reduced daily “OFF”-time relative to placebo in adults with Parkinson’s disease (PD) and motor fluctuations. Diary data from these studies were pooled and analyzed post hoc to characterize “OFF”-times around nighttime sleep and to explore the effects of opicapone 50 mg. Methods “OFF” before sleep (OBS), “OFF during the nighttime sleep period” (ODNSP), early morning “OFF” (EMO), and duration of nighttime sleep and awake periods were analyzed descriptively at baseline. Mean changes from baseline to Week 14/15 (end of double-blind treatment) were analyzed using two-sided t-tests in participants with data for both visits. Results At baseline, 88.3% (454/514) of participants reported having OBS (34.0%), ODNSP (17.1%), or EMO (79.6%). Those with ODNSP had substantially shorter mean duration of uninterrupted sleep (4.4 hours) than the overall pooled population (7.1 hours). At Week 14/15, mean decrease from baseline in ODNSP duration was significantly greater with opicapone than with placebo (-0.9 vs. -0.4 hours, P<0.05). In participants with ODNSP at baseline, the decrease in total time spent awake during the night-time sleep period was significantly greater with opicapone than with placebo (-1.0 vs -0.4 hours, P<0.05), as was the reduction in percent time spent awake during the night-time sleep period (-12.8% vs. -4.5%, P<0.05). Conclusion “OFF”-times around nighttime sleep were common in BIPARK-1 and BIPARK-2. Opicapone may improve sleep by decreasing the amount of time spent awake during the night in patients with PD who have night-time sleep period “OFF” episodes.
更多
查看译文
关键词
motor fluctuations,nighttime sleep,OFF time,opicapone,Parkinson’s disease,treatment
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