Sleep Disturbance in Infancy (Disorder)NCT04920175
Real-time State of Vigilance Monitor for the Neonatal Intensive Care Unit
An observational study of Sleep Disturbance in Infancy (Disorder) and Neonatal Disease, run by University of Michigan at 1 site in United States.
Trial summary
The goal of this observational study is to collect data to develop a complete package (hardware, user interface software and algorithms) that can monitor sleep-wake stages in neonates. Read more about this study
- Who is it for?
- Ages 1 day to 1 year
- Conditions the study is for
- Sleep Disturbance in Infancy (Disorder), Neonatal Disease
- What is being tested?
- Novel Real-time Neonatal Sleep Stage Detection Algorithm
- How many people
- 39 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Sep 2021to 19 Dec 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 1 day to 1 year
- All sexes
- No healthy volunteers
- Child
Study population: Newborns admitted to the Newborn ICU in C\&W Mott Hospital
Who may be able to join
- Admitted to the Newborn ICU in C\&W Mott Hospital
- >/= 30 weeks gestational age at the time of birth (>/= 33 weeks post-conceptional age at enrollment)
Who cannot join
- Any diagnosis, patient care, or anticipated patient care that is likely to interfere with the 12 hour recording or would make the recording dangerous to the participant
Trial locations and contacts
1 site in 1 country.
About this study
The goal of this observational study is to collect data to develop a complete package (hardware, user interface software and algorithms) that can monitor sleep-wake stages in neonates. Real-time EEG data will be used to develop and refine the prototype monitor's ability to provide direct real-time information about sleep-wake state. The study design includes multiple iterative training/testing stages to refine the prototype. The study is divided into multiple sub-aims conducted in parallel: data acquisition, algorithm development (including comparison between gold-standard polysomnogram vs. novel algorithm markings of sleep-stages), and graphical user interface software development. The data acquisition and algorithm development are iterative and linked, such that the prototype algorithm from one iteration will be deployed real-time during the next iteration of data acquisition. This allows verification that the algorithm can perform real-time and provides prospective testing data, which is later folded into the training data for the next iteration, for verification and validation of the system.
Read the detailed description
Use Case: Disruption of sleep is a common experience of hospitalized patients of all ages, especially if they are in an intensive care unit (ICU); infants in the NICU often stay weeks to months. The quality of neonatal sleep is strongly associated with later neurodevelopment. Abnormal sleep quality in neonates is associated with less attention orienting at 4 months, increased distractibility, decreased developmental function at 12-24 months, and lower emotional regulation and cognitive development at age 5. Yet disruptions to sleep are frequent: the study team has found that NICU neonates are handled by staff with a median interval of 2.3 min. Handling occurred across all sleep-wake stages and frequently resulted in arousals, awakenings, and respiratory events.
The study will employ multiple levels of noise reduction and signal quality assessment, tailored to the specific needs of the algorithm and to the NICU environment. The final algorithm will include four sleep-wake stages (awake, quiet/non-REM sleep, active/REM sleep, indeterminate/transitional sleep). The complete algorithm is intended to do what no existing algorithm does, as it uniquely combines the assessment of data quality, ability to run real-time on un-curated data, and identification of four sleep-wake stages. In this observational study, validation of the monitor "read-out" in comparison to the gold standard polysomnogram happens offline, after the completion of data collection from the subject.
Because this is an observational study to develop and validate a new physiologic monitoring modality (the bedside sleep monitor), there is no subject intervention. No change in care for these study subjects is envisioned to result from use of this prototype monitor. It is hoped that the proposed technology will create a unique solution that will one day be deployed in the NICU.
Potential Future Research Use of Monitor: The study team hypothesizes that adjusting the timing of NICU patient contact to avoid multiple sleep disruptions might improve sleep in the NICU, which could then lead to better neurodevelopmental outcomes. However, the efficacy of this approach would need to be proved in randomized controlled trials. The conduct of such a future randomized clinical trial would be facilitated by availability of a real-time, objective monitor of sleep-wake states like what the study team proposes to develop. However, the present observational study serves as an initial stage of research that would lead up to that kind of trial.
- Being tested
- Novel Real-time Neonatal Sleep Stage Detection Algorithm
- Keywords
- NICU, Neonatal Sleep
- Medical subject headings
- Infant, Newborn, Diseases
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Novel Real-time Neonatal Sleep Stage Detection AlgorithmOther
Comparison of Novel Real-time Neonatal Sleep Stage Detection Algorithm to gold standard concurrent polysomnogram.
| Study group | Role | What they receive |
|---|---|---|
| NICU Cohort | Participants will undergo a standard polysomnogram Receives: Other: Novel Real-time Neonatal Sleep Stage Detection Algorithm |
What is being measured
The primary outcome is the main question the study is designed to answer.
Negative predictive value (NPV) for detection of sleep (any stage)
Negative predictive value of monitor compared to gold-standard polysomnogram
Measured: 12 hours
Secondary outcomes (5)
NPV for detection of REM sleep
Negative predictive value of monitor compared to gold-standard polysomnogram
Measured: 12 hours
NPV for detection of non-REM sleep
Negative predictive value of monitor compared to gold-standard polysomnogram
Measured: 12 hours
Positive predictive value (PPV) of Sleep
Positive predictive value of monitor compared to gold-standard polysomnogram
Measured: 12 hours
Positive predictive value (PPV) of REM sleep
Positive predictive value of monitor compared to gold-standard polysomnogram
Measured: 12 hours
Positive predictive value (PPV) of non-REM sleep
Positive predictive value of monitor compared to gold-standard polysomnogram
Measured: 12 hours
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jun 2021
- Study start1 Sep 2021
- Primary completion19 Dec 2024
- Study completion19 Dec 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Sleep Disturbance in Infancy (Disorder)Studies of the same condition, open and under way.
- More trials run by University of MichiganThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 39 participants (actual)
Sponsor and investigators
- Lead sponsor
- University of Michigan
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, John Barks, University of Michigan
- Investigators
- John Barks, MD, Principal investigator, University of MichiganStephen Gliske, PhD, Principal investigator, University of Nebraska
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04920175
- Sponsor's protocol ID
- HUM00187386
- Other IDs
- 1R61HL154095-01
- Status last verified
- Jan 2025
- First submitted
- 3 Jun 2021
- Last updated
- 24 Jan 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 24 Jan 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Real-time State of Vigilance Monitor for the Neonatal Intensive Care Unit
- ClinicalTrials.gov ID
- NCT04920175
- Acronym / sponsor ID
- HUM00187386
- Keywords
- NICU, Neonatal Sleep
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 39 participants (actual)
- Lead sponsor
- University of MichiganUniversity, hospital or other
- Collaborators
- University of Nebraska, National Heart, Lung, and Blood Institute (NHLBI)
- Study start
- 1 Sep 2021 (actual)
- Primary completion
- 19 Dec 2024 (actual)
- Study completion
- 19 Dec 2024 (actual)
- First posted
- 9 Jun 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this observational study is to collect data to develop a complete package (hardware, user interface software and algorithms) that can monitor sleep-wake stages in neonates. Real-time EEG data will be used to develop and refine the prototype monitor's ability to provide direct real-time information about sleep-wake state. The study design includes multiple iterative training/testing stages to refine the prototype. The study is divided into multiple sub-aims conducted in parallel: data acquisition, algorithm development (including comparison between gold-standard polysomnogram vs. novel algorithm markings of sleep-stages), and graphical user interface software development. The data acquisition and algorithm development are iterative and linked, such that the prototype algorithm from one iteration will be deployed real-time during the next iteration of data acquisition. This allows verification that the algorithm can perform real-time and provides prospective testing data, which is later folded into the training data for the next iteration, for verification and validation of the system.
Detailed description
Use Case: Disruption of sleep is a common experience of hospitalized patients of all ages, especially if they are in an intensive care unit (ICU); infants in the NICU often stay weeks to months. The quality of neonatal sleep is strongly associated with later neurodevelopment. Abnormal sleep quality in neonates is associated with less attention orienting at 4 months, increased distractibility, decreased developmental function at 12-24 months, and lower emotional regulation and cognitive development at age 5. Yet disruptions to sleep are frequent: the study team has found that NICU neonates are handled by staff with a median interval of 2.3 min. Handling occurred across all sleep-wake stages and frequently resulted in arousals, awakenings, and respiratory events.
The study will employ multiple levels of noise reduction and signal quality assessment, tailored to the specific needs of the algorithm and to the NICU environment. The final algorithm will include four sleep-wake stages (awake, quiet/non-REM sleep, active/REM sleep, indeterminate/transitional sleep). The complete algorithm is intended to do what no existing algorithm does, as it uniquely combines the assessment of data quality, ability to run real-time on un-curated data, and identification of four sleep-wake stages. In this observational study, validation of the monitor "read-out" in comparison to the gold standard polysomnogram happens offline, after the completion of data collection from the subject.
Because this is an observational study to develop and validate a new physiologic monitoring modality (the bedside sleep monitor), there is no subject intervention. No change in care for these study subjects is envisioned to result from use of this prototype monitor. It is hoped that the proposed technology will create a unique solution that will one day be deployed in the NICU.
Potential Future Research Use of Monitor: The study team hypothesizes that adjusting the timing of NICU patient contact to avoid multiple sleep disruptions might improve sleep in the NICU, which could then lead to better neurodevelopmental outcomes. However, the efficacy of this approach would need to be proved in randomized controlled trials. The conduct of such a future randomized clinical trial would be facilitated by availability of a real-time, objective monitor of sleep-wake states like what the study team proposes to develop. However, the present observational study serves as an initial stage of research that would lead up to that kind of trial.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| NICU Cohort | – | Other: Novel Real-time Neonatal Sleep Stage Detection AlgorithmParticipants will undergo a standard polysomnogram |
Who may qualify
- Ages
- 1 day to 1 year
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
- Study population
- Newborns admitted to the Newborn ICU in C\&W Mott Hospital
Key inclusion criteria (2 listed)
- Admitted to the Newborn ICU in C\&W Mott Hospital
- >/= 30 weeks gestational age at the time of birth (>/= 33 weeks post-conceptional age at enrollment)
Key exclusion criteria (1 listed)
- Any diagnosis, patient care, or anticipated patient care that is likely to interfere with the 12 hour recording or would make the recording dangerous to the participant
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Novel Real-time Neonatal Sleep Stage Detection AlgorithmComparison of Novel Real-time Neonatal Sleep Stage Detection Algorithm to gold standard concurrent polysomnogram. | Other | NICU Cohort |
Primary outcome
Negative predictive value (NPV) for detection of sleep (any stage)
Time frame: 12 hours
Negative predictive value of monitor compared to gold-standard polysomnogram
5 secondary outcomes
NPV for detection of REM sleep
Time frame: 12 hours
NPV for detection of non-REM sleep
Time frame: 12 hours
Positive predictive value (PPV) of Sleep
Time frame: 12 hours
Positive predictive value (PPV) of REM sleep
Time frame: 12 hours
Positive predictive value (PPV) of non-REM sleep
Time frame: 12 hours
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Jan 2025.
- Individual participant dataSharing planned: No
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
John Barks, MD principal investigator
University of Michigan
Stephen Gliske, PhD principal investigator
University of Nebraska
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Sleep Disturbance in Infancy (Disorder) and Neonatal Disease, run by University of Michigan at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 24 Jan 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Negative predictive value (NPV) for detection of sleep (any stage) (time frame: 12 hours). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Jan 2025.