A groundbreaking study led by Dr. Diego Z. Carvalho of Mayo Clinic, published in Neurology, has unearthed crucial links between sleep apnea, a lack of deep sleep, and an increased risk of brain health deterioration, stroke, and Alzheimer’s disease. This innovative research underscores the importance of quality sleep for improved health outcomes, positioning Neurobit’s technology at the frontline of sleep health solutions.
Sleep apnea, a disorder affecting over 936 million people worldwide, is characterized by interrupted breathing during sleep. The absence of deep sleep, or slow-wave sleep, is also concerning. This phase of sleep is crucial for memory consolidation, physical recovery, and overall brain health. Both these conditions, when left untreated, can contribute to serious health complications, including cognitive decline, stroke, and Alzheimer's disease - a progressive disorder affecting nearly 50 million people globally that disrupts memory and thinking skills and highlights the urgency of comprehensive sleep health solutions.
The study observed 140 individuals with obstructive sleep apnea and an average age of 73. Participants underwent a brain scan and a polysomnography (PSG) sleep study. PSG is a comprehensive recording of biophysiological changes that occur during sleep, often used to diagnose sleep disorders. This research identified brain biomarkers, specifically white matter hyperintensities and axonal integrity, which are crucial to white matter health. The study found that individuals with severe sleep apnea and a reduction in slow-wave sleep had more white matter hyperintensities and reduced axonal integrity, factors that contribute to brain health deterioration.
These findings illuminate the potential risk factors for cognitive decline, stroke, and Alzheimer’s disease, underscoring the importance of quality sleep and effective management of sleep disorders. Such insights could potentially inform new strategies for preventing or managing brain health deterioration. The findings highlight the critical role of Neurobit's work in delivering effective sleep health solutions.
A limitation acknowledged in the study is the split-night design of the sleep study, which may not accurately represent a full night's sleep. This highlights the need for comprehensive sleep monitoring solutions capable of capturing a complete and accurate picture of a patient's sleep cycle, a challenge Neurobit's solutions are designed to meet.
Neurobit offers innovative products to tackle and overcome these challenges:
Neurobit Score: An AI and deep learning platform that enables quick, accurate scoring of PSG data, vital for diagnosing conditions like sleep apnea. This efficiency reduces the time and cost associated with traditional manual scoring.
Z3 Pulse: A wearable ECG device that delivers comprehensive sleep reports and personalized guidance, helping individuals better understand and manage their sleep health.
Neurobit Hub: A platform that streamlines the collection and analysis of extensive datasets, promoting the discovery of novel biomarkers and sleep-centric treatment strategies.
The study's findings underscore the importance of quality sleep and effective management of sleep disorders for brain health. With Neurobit's advanced technology enabling rapid and precise PSG data analysis, comprehensive sleep reports, and extensive data analysis, we're equipping researchers with tools to better manage sleep health and reduce healthcare costs.
Discover how Neurobit’s cutting-edge technology can revolutionize your sleep health. Visit our website or contact us directly to join our mission towards better sleep and healthier brains.
Email us at Research@Neurobit.com
Citation
Carvalho, D. Z., McCarter, S. J., St Louis, E. K., Przybelski, S. A., Johnson Sparrman, K. L., Somers, V. K., Boeve, B. F., Petersen, R. C., Jack, C. R., Graff-Radford, J., & Vemuri, P. (2023). Association of Polysomnographic Sleep Parameters With Neuroimaging Biomarkers of Cerebrovascular Disease in Older Adults With Sleep Apnea. Neurology, 10.1212/WNL.0000000000207392. https://doi.org/10.1212/WNL.0000000000207392