4.1 Article

Wireless Electroencephalography (EEG) to Monitor Sleep Among Patients Being Withdrawn From Opioids: Evidence of Feasibility and Utility

Journal

EXPERIMENTAL AND CLINICAL PSYCHOPHARMACOLOGY
Volume 30, Issue 6, Pages 1016-1023

Publisher

AMER PSYCHOLOGICAL ASSOC
DOI: 10.1037/pha0000483

Keywords

opioid; withdrawal; sleep; EEG; buprenorphine

Funding

  1. [R01DA018125]
  2. [R01DA035246]
  3. [R01DA042751]
  4. [R01DA040644]
  5. [UG3DA048734]
  6. [U01HL150835]

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Many individuals withdrawing off of opioids experience severe sleep impairment and insomnia. The study shows that a wireless EEG sleep monitor is a feasible and useful tool for objective monitoring of sleep in this population, providing more accurate information than standard sleep diaries.
Public Health Significance Many people who are withdrawing off of opioids experience severe and clinically significant levels of sleep impairment and insomnia. In order to learn more about sleep impairment and appropriate treatment strategies, we must identify comfortable and precise ways to measure sleep in patients experiencing withdrawal. This study provides initial evidence that a commercially available, wireless, ambulatory EEG sleep monitor was accepted by patients and provided information that was more closely associated with measures of withdrawal than a standard sleep diary. Sleep impairment is a common comorbid and debilitating symptom for persons with opioid use disorder (OUD). Research into underlying mechanisms and efficacious treatment interventions for OUD-related sleep problems requires both precise and physiologic measurements of sleep-related outcomes and impairment. This pilot examined the feasibility of a wireless sleep electroencephalography (EEG) monitor (Sleep Profiler (TM)) to measure sleep outcomes and architecture among participants undergoing supervised opioid withdrawal. Sleep outcomes were compared to a self-reported sleep diary and opioid withdrawal ratings. Participants (n = 8, 100% male) wore the wireless EEG 85.6% of scheduled nights. Wireless EEG detected measures of sleep architecture including changes in total, NREM and REM sleep time during study phases, whereas the diary detected changes in wakefulness only. Direct comparisons of five overlapping outcomes revealed lower sleep efficiency and sleep onset latency and higher awakenings and time spent awake from the wireless EEG versus sleep diary. Associations were evident between wireless EEG and increased withdrawal severity, lower sleep efficiency, less time in REM and non-REM stages 1 and 2, and more hydroxyzine treatment; sleep diary was associated with total sleep time and withdrawal only. Data provide initial evidence that a wireless EEG is a feasible and useful tool for objective monitoring of sleep in persons experiencing acute opioid withdrawal. Data are limited by the small and exclusively male sample, but provide a foundation for using wireless EEG sleep monitors for objective evaluation of sleep-related impairment in persons with OUD in support of mechanistic and treatment intervention research.

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