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Study to Collect Data for Neonatal Abstinence Syndrome (NAS) and Evaluate the Automated Data Collection Process
Sponsor: Rekovar Inc.
Summary
Substance abuse during pregnancy is on the rise through both prescribed and illicit use of controlled substances, which has increased neonatal abstinence syndrome (NAS). The prevalence of opioid use during pregnancy has increased by 333% from 2013 to 2014 and continues to rise. Approximately 1 in 3 women were prescribed opioids during pregnancy from 2008 to 2012. In the US, NAS was diagnosed every 25 minutes in 2014. By 2019, it became every 15 minutes. Although there are medication-based interventions for the treatment of NAS, used in up to 80% of opioid-exposed infants, these treatments carry risks of toxicity and drug interactions. Despite the steep medical costs and the risks of treatment, current tools to assess the severity of NAS are subjective and suffer from examiner bias, resulting in poorer clinical outcomes, such as longer lengths of stay in the Neonatal Intensive Care Unit (NICU), for these babies. Studies have shown that continuous vital sign monitoring improves outcomes and decreases the length of stay in general practice. Preliminary machine learning models have been able to predict pharmacological treatment for Neonatal Opioid Withdrawal Syndrome (NOWS). This project will collect physiological and behavioral data of NAS patients to develop an AI algorithm and establish the advantages of continuous monitoring in NAS. The AI algorithm, processed by machine learning, will help predict NAS symptoms, automate scoring, and provide healthcare personnel with predictive analytics to guide suggested treatments.
Official title: A Multi-center Study to Collect Data for Basic Physiological Research in Neonatal Abstinence Syndrome (NAS) and Evaluate the Automated Finnegan/ESC Data Collection Process
Key Details
Gender
All
Age Range
Any - 4 Weeks
Study Type
OBSERVATIONAL
Enrollment
100
Start Date
2024-03-18
Completion Date
2026-06-30
Last Updated
2025-09-09
Healthy Volunteers
Yes
Conditions
Interventions
NeoMonki
Collection of Data for assessing the reliability of Neomonki and Realtime monitoring
Locations (1)
University of New Mexico
Albuquerque, New Mexico, United States