A Feasibility Study to Test the REST Tracker System for Use in Maternal Care to Improve Outcomes by Early Detection of Obstructive Sleep Apnea

AbstractObstructive sleep apnea (OSA) during pregnancy is associated with increased risk of developing gestational diabetes, hypertension, preeclampsia, and eclampsia, contributing to maternal and neonatal morbidity and mortality. Furthermore, OSA increases risk of chronic cardiovascular disease, well beyond pregnancy, raising the stakes for detection and management during pregnancy. Research studies suggest that the prevalence of OSA increases during pregnancy, as the maternal body mass index (BMI) rises. Continuous evaluation is necessary as the risk of developing OSA increases throughout the course of the pregnancy however this is not currently a standard practice in prenatal care. Serial screenings for OSA with polysomnograms or home sleep apnea tests are impractical and financially prohibitive. Thus, the need arises for improved tools that provides simple and accurate detection of OSA during pregnancy to prevent potential consequences. Sleep specialists have not provided a specific approach to assist obstetricians addressing OSA concern, leaving a gap in our maternal health management. Our proposal seeks to address this gap.REST Technologies has been involved with providing services to support clinical sleep medicine for the past twenty years. Now, using remote patient monitoring, state-of-the-art signal processing, and data reduction techniques REST Technologies REST Tracker system can improve maternal health. Additionally, beyond the detection of OSA during pregnancy, OSA treatment management itself can be optimized using this same monitoring approach. The progressive physiologic changes in pregnancy make it an ideal population for the REST Tracker system development, as the approach is generalizable to other at-risk populations. This grant focuses on demonstrating feasibility to perform Remote Patient Monitoring to track pregnant patients throughout their pregnancy is a fashion that is simple for the patient yet yielding critical data that relates to sleep and sleep physiology. The team assembled for this project have vast clinical experience and plan to bring innovative approaches to the practice of sleep medicine beyond maternal monitoring to enhance Telemedicine clinical pathways.