Sleep Disruption in Post-operative Patients in the Neurocritical Care Unit (SDPPNCU)

The role of sleep in patients admitted to the intensive care unit is an emerging field of research. There have been studies that show patients in the ICU have poor sleep including sleep fragmentation, multiple arousals, decreased stage 3 sleep and reduced REM sleep (1, 2, 3). Causes of poor sleep in the ICU include severity of illness, abnormal light exposure, and frequent arousals for medical care. Not only does poor sleep contribute to reduced cognitive function and delirium, but there are also implications for the immune system function and wound healing (4). Polysomnography is regarded as the gold standard for sleep studies, however it has limited utility in the ICU population (5) and alternative methods of sleep analysis need to be investigated to better understand the underlying physiologic mechanisms and subsequent cognitive effects.

Study Overview

• Status: Terminated
• Conditions: Sleep Fragmentation
• Intervention / Treatment: Behavioral: sleep disruption

Detailed Description

The importance of sleep for patients in the intensive care unit (ICU) has been well documented. Research has shown that the ICU has multiple risk factors for poor sleep, and that this has multiple effects on patient outcomes. Further research is needed to better define the best tool to use for measuring sleep stages in ICU patients. Furthermore, there is very limited data comparing sleep interruption in ICU patients and the effects on sleep architecture and cognition.

Hypothesis 1a: The number of episodes of rapid eye movements (REM), stage 1, stage 2, stage 3 sleep, sleep spindles, and alpha activity will increase while the total duration of activity and the duration of episodes will decline in the postoperative neurologic critical care unit (NCCU) with neurological checks every two hours over a 12 hour period of recording as compared to every 6 hours.

Hypothesis 1b: As the number of episodes of REM, stage 1, stage 2, stage 3 sleep, sleep spindles, and alpha activity increase while the total duration of activity and the duration of episodes decline in the postoperative NCCU with neurological checks every two hours over a 12 hour period of recording as compared to every 6 hours.

Hypothesis 2: The number of episodes, the total duration, and the interval durations, of REM, stage 1, stage 2, stage 3 sleep, sleep spindles, and alpha activity will be identical in the automated recordings as compared to human reading by a sleep trained Neurologist.

Hypothesis 3: The group with awakenings every two hours will report more objective sleepiness and perform psychomotor visual task (PVT) with increased time and reduced performance.

Performing this study will allow for validation of an automated EEG system for the interpretation of sleep. If this tool is a reliable method of sleep interpretation, it may be expanded to a larger population of ICU patients for further research on the effects of sleep deprivation. Additionally, it will add prospective data to the literature regarding the psychomotor effects of increased sleep interruption in ICU patients.

2. Objectives (include all primary and secondary objectives)

1. Detect the effects of disrupted sleep resulting from frequent neurological exams in the NCCU in post-surgical patients. The investigators will use an automated EEG detection system used in patients with continuous EEG (cEEG) monitoring to detect duration of sleep related EEG brain activity, number of intervals of activation, and the duration of the intervals for sleep activities including: REM, Stage 1, stage 2, and stage 3 sleep, sleep spindles, and alpha activity.

2. The investigators will study the precision, accuracy and bias of the automated algorithm by comparing it to the interpretations of two sleep trained neurologists who will read these recordings in a

   blinded manner independently of one another. The investigators will select records to validate the automatic scorer including the identification and duration of all aspects of the cEEG sleep recording during the first four hours of sleep recording for each patient. The investigators will compare the accuracy of identification and measured duration of REM, Stage one, stage two, stage 3 sleep, sleep spindles, and alpha activity.

3. Subjective measure of sleep assessment using the Richards-Campbell Sleep Questionnaire (RCSG).
4. Quantitative assessment of alertness using a psychomotor vigilance task (PVT).

• Study Type: Interventional
• Enrollment (Actual): 1
• Phase: Not Applicable

Contacts and Locations

Study Locations

• United States
  • Maryland
    • Baltimore, Maryland, United States, 21287
      • Johns Hopkins

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 100 years (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

Description

Inclusion Criteria:

• post operative back patients in the NCCU with no history of brain injury

Exclusion Criteria:

• None

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: group 2; no intervention
Other: group 1; sleep disruption	Behavioral: sleep disruption; Group two will have interrupted sleep at time periods of 2 hours post operatively. Group two will be woken every 2 hours, which is the standard NCCU protocol.; Other Names: group 2

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Detect the effects of disrupted sleep with quantitative EEG analysis	The investigators will use an automated EEG detection system used in patients with continuous EEG (cEEG) monitoring to detect duration of sleep related EEG brain activity, number of intervals of activation, and the duration of the intervals for sleep activities including: REM, Stage 1, stage 2, and stage 3 sleep, sleep spindles, and alpha activity.	Up to 12 hours

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Precision, accuracy and bias of the automated cEEG algorithm by comparing it to the interpretations of sleep trained neurologists	Two sleep trained neurologists will read these recordings in a blinded manner independently of one another. The investigators will select records to validate the automatic scorer including the identification and duration of all aspects of the cEEG sleep recording during the first four hours of sleep recording for each patient. The investigators will compare the accuracy of identification and measured duration of REM, Stage one, stage two, stage 3 sleep, sleep spindles, and alpha activity.	Up to 4 hours
Subjective measure of sleep assessment using the Richards-Campbell Sleep Questionnaire		Up to 12 hours
Quantitative assessment of alertness using a psychomotor vigilance task (PVT).		Up to 12 hours

Collaborators and Investigators

• Sponsor: Johns Hopkins University
• Investigators: Principal Investigator: Paul A Nyquist, MD, Johns Hopkins School of Medicine

Study record dates

Study Major Dates

• Study Start: December 1, 2016
• Primary Completion (Actual): March 26, 2018
• Study Completion (Actual): March 26, 2018

Study Registration Dates

• First Submitted: December 16, 2016
• First Submitted That Met QC Criteria: December 16, 2016
• First Posted (Estimate): December 20, 2016

Study Record Updates

• Last Update Posted (Actual): April 3, 2018
• Last Update Submitted That Met QC Criteria: April 2, 2018
• Last Verified: April 1, 2018

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Mental Disorders; Nervous System Diseases; Dyssomnias; Sleep Wake Disorders; Neurologic Manifestations; Sleep Deprivation
• Other Study ID Numbers: IRB00092868

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: No

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No
• product manufactured in and exported from the U.S.: No