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Comparison of Dreem to Clinical PSG for Sleep Monitoring in Apnea Patients

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ClinicalTrials.gov Identifier: NCT03657329
Recruitment Status : Completed
First Posted : September 5, 2018
Last Update Posted : November 28, 2018
Sponsor:
Collaborator:
Stanford University
Information provided by (Responsible Party):
Dreem

Brief Summary:
This study aims to evaluate the accuracy of apnea detection and automated sleep analysis by the Dreem dry-EEG headband and deep learning algorithm in comparison to the consensus of 5 sleep technologists' manual scoring of a gold-standard clinical polysomnogram (PSG) record in adults during a physician-referred overnight sleep study due to suspicion of sleep-disordered breathing.

Condition or disease Intervention/treatment Phase
Sleep Sleep Apnea Diagnostic Test: Dreem Not Applicable

Detailed Description:

The study will enroll up to 70 adults who are referred to the Stanford Sleep Medicine Center by their physician for an overnight polysomnographic sleep study due to suspicion of sleep-disordered breathing, with the aim of collecting 60 usable data sets (i.e., eligible subjects with high-quality PSG and Dreem recordings). Upon arrival to the clinic, patients provide informed consent, are interviewed to determine eligibility, and complete a detailed demographic, medical, health, sleep, and lifestyle questionnaire (Alliance Sleep Questionnaire; ASQ). After the ASQ, participants are fitted with the PSG and the Dreem headband by the sleep technologist. During the PSG sleep study, the Dreem headband records EEG, pulse, oxygen saturation (SO2), movement, and respiratory rate. Many participants may undergo a split-night study with a continuous positive airway pressure (CPAP) device during their participation, as deemed necessary by the clinical staff pursuant to the sleep study.

The PSG data from the first 30 eligible participants will be manually scored by 5 sleep technologists. These manually-scored PSG data files (referred to as the training dataset) will be synchronized with Dreem data files from the same night and the synchronized files will be used to train Dreem's deep learning algorithms. Following training, the algorithms will be deployed to automatically score the final 30 participants' Dreem datasets (testing dataset). Finally, PSG records for the second 30 participants will be provided to the sponsor and manually scored by 5 sleep technologists. The manual scoring results will be compared to the Dreem automatic analysis to determine the accuracy of Dreem's apnea-hypopnea index (AHI) severity detection and sleep staging algorithms.


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Study Type : Interventional  (Clinical Trial)
Actual Enrollment : 67 participants
Intervention Model: Single Group Assignment
Intervention Model Description: Dreem
Masking: None (Open Label)
Primary Purpose: Diagnostic
Official Title: Performance of a Wireless Dry-EEG Device for Sleep Monitoring Compared to a Gold Standard Polysomnography in Patients With Suspected Sleep-Disordered Breathing
Actual Study Start Date : May 7, 2018
Actual Primary Completion Date : November 2, 2018
Actual Study Completion Date : November 2, 2018

Arm Intervention/treatment
Experimental: Suspicion of sleep-disordered breathing
Dreem
Diagnostic Test: Dreem
Dreem Band to be worn by each participant while undergoing in-lab sleep study with PSG. Pursuant to the physician-ordered diagnostic study, clinical staff may determine a split-night study with CPAP to be appropriate for any participant, simultaneous with the PSG and Dreem.




Primary Outcome Measures :
  1. Apnea-Hypopnea Index (AHI) severity agreement [ Time Frame: Day 1 ]
    AHI severity (normal [<5], mild [5-14], moderate [15-29], severe [>29]) as automatically determined by the Dreem headband compared to the AHI severity determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.


Secondary Outcome Measures :
  1. Total Sleep Time (TST) agreement [ Time Frame: Day 1 ]
    Total time (in minutes) the subject spends asleep as automatically determined by the Dreem headband compared to the TST determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.

  2. EEG Virtual Channel signal quality agreement [ Time Frame: Day 1 ]
    Comparison of a proprietary signal quality metric between Dreem and PSG virtual channel, calculated as a ratio of supra-threshold quality signal time over total time in bed trying to sleep (lights off to lights on).

  3. Wake After Sleep Onset (WASO) time agreement [ Time Frame: Day 1 ]
    Total time (in minutes) the subject spends awake from sleep onset to sleep end as automatically determined by the Dreem headband compared to the WASO determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.

  4. Time in N1 sleep stage agreement [ Time Frame: Day 1 ]
    Total time (in minutes) the subject spends in AASM N1 sleep stage as automatically determined by the Dreem headband compared to the N1 time determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.

  5. Time in N2 sleep stage agreement [ Time Frame: Day 1 ]
    Total time (in minutes) the subject spends in AASM N2 sleep stage as automatically determined by the Dreem headband compared to the N2 time determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.

  6. Time in N3 sleep stage agreement [ Time Frame: Day 1 ]
    Total time (in minutes) the subject spends in AASM N3 sleep stage as automatically determined by the Dreem headband compared to the N3 time determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.

  7. Time in REM sleep stage agreement [ Time Frame: Day 1 ]
    Total time (in minutes) the subject spends in AASM REM sleep stage as automatically determined by the Dreem headband compared to the REM time determined by the consensus of 5 sleep technologists' scoring of the subject's PSG record from the same night.



Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years to 70 Years   (Adult, Older Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Criteria

Inclusion Criteria:

  • 18-70 years of age
  • Capable of providing informed consent
  • Suspicion of sleep breathing disorder (both diagnostic and split-night studies)

Exclusion Criteria:

  • Concomitant diagnosis of a sleep disorder other than sleep apnea syndrome or insomnia
  • Morbid obesity (BMI > 39)
  • Use of benzodiazepines, nonbenzodiazepine (Z-drugs), or Gammahydroxybutyrate (GHB) the day/night of the study
  • Concomitant diagnosis of cardiopulmonary or neurological comorbidities (such as heart failure, COPD, neurodegenerative conditions)

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03657329


Locations
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United States, California
Stanford Sleep Medicine Center
Redwood City, California, United States, 94063
Sponsors and Collaborators
Dreem
Stanford University
Investigators
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Principal Investigator: Emmanuel H During, MD Stanford University

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Responsible Party: Dreem
ClinicalTrials.gov Identifier: NCT03657329     History of Changes
Other Study ID Numbers: OCTAVE Stanford
First Posted: September 5, 2018    Key Record Dates
Last Update Posted: November 28, 2018
Last Verified: November 2018
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Undecided
Plan Description: We plan to share de-identified physiological data in an open-source format to the public. However, this will only occur if the data files are of sufficient quality and likely to be of use to the scientific community. This decision may also depend on certain legal or business constraints.

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Studies a U.S. FDA-regulated Drug Product: No
Studies a U.S. FDA-regulated Device Product: No

Keywords provided by Dreem:
Automated Sleep Staging
Automated Apnea Detection

Additional relevant MeSH terms:
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Apnea
Respiration Disorders
Respiratory Tract Diseases
Signs and Symptoms, Respiratory
Signs and Symptoms