Real-time State of Vigilance Monitor for the Neonatal Intensive Care Unit

NCT04920175 | Completed

• 2 other identifiers: HUM001873861R61HL154095-01
• Study Type: observational
• Target: 39
• Locations: 1 country
• Sites: 1

Brief 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. 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.

Conditions

Sleep Disturbance in Infancy (Disorder); Neonatal Disease

Keywords

NICU; Neonatal Sleep

Outcome Measures

Primary Outcomes (1)

• Negative predictive value (NPV) for detection of sleep (any stage)

  Negative predictive value of monitor compared to gold-standard polysomnogram

  12 hours

Secondary Outcomes (5)

• NPV for detection of REM sleep

  12 hours

• NPV for detection of non-REM sleep

  12 hours

• Positive predictive value (PPV) of Sleep

  12 hours

• Positive predictive value (PPV) of REM sleep

  12 hours

• Positive predictive value (PPV) of non-REM sleep

  12 hours

Study Arms (1)

NICU Cohort

Participants will undergo a standard polysomnogram

Other: Novel Real-time Neonatal Sleep Stage Detection Algorithm

Interventions

Novel Real-time Neonatal Sleep Stage Detection Algorithm OTHER

Comparison of Novel Real-time Neonatal Sleep Stage Detection Algorithm to gold standard concurrent polysomnogram.

NICU Cohort

Eligibility Criteria

• Age: 1 Day - 1 Year
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17)
• Sampling Method: Probability Sample

Study Population

Newborns admitted to the Newborn ICU in C\&W Mott Hospital

You may qualify if:

• 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)

You may not qualify if:

• 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

Sponsors & Collaborators

• University of Michigan: lead
• University of Nebraska: collaborator
• National Heart, Lung, and Blood Institute (NHLBI): collaborator

Study Sites (1)

University of Michigan

Ann Arbor, Michigan, 48109, United States

Location

MeSH Terms

Conditions

Infant, Newborn, Diseases

Condition Hierarchy (Ancestors)

Congenital, Hereditary, and Neonatal Diseases and Abnormalities

Study Officials

• John Barks, MD

  University of Michigan

  PRINCIPAL INVESTIGATOR

• Stephen Gliske, PhD

  University of Nebraska

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor of Pediatrics

Study Record Dates

• First Submitted: June 3, 2021
• First Posted: June 9, 2021
• Study Start: September 1, 2021
• Primary Completion: December 19, 2024
• Study Completion: December 19, 2024
• Last Updated: January 24, 2025

Record last verified: 2025-01

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)