Investigator:
Saar Anis, MD
Name of Institution:
Cleveland Clinic Foundation
Project Title:
Deep brain stimulation neural recordings analysis of varied stimulation parameters during sleep in Parkinson’s disease (The DREAMS-PD Study)
Investigator Bio:
Dr. Saar Anis is a Neurologist and Movement Disorders Specialist. He completed his Neurology Residency and Movement Disorders Fellowship at Tel Aviv Sourasky Medical Center in Tel Aviv, Israel. Following his fellowship, Dr. Anis served as staff at Sheba Medical Center and began a tenure-track position at Tel Aviv University. During his tenure, he investigated the impact of Deep brain stimulation (DBS) on non-motor features in Parkinson’s disease (PD) patients with monogenic mutations prevalent in the Ashkenazi Jewish (AJ) population.
Dr. Anis has a strong research focus on non-motor symptoms of PD and other movement disorders. His previous research includes studying the effects of medical cannabis on non-motor symptoms of PD, employing both prospective and retrospective designs. He has also led and participated in many multi-center clinical trials.
Currently, Dr. Anis is conducting a Clinical Research Fellowship at the Cleveland Clinic Foundation (CCF), focusing on the innovative use of the DBS technology BrainSenseTM in clinical and research settings.
Objective:
To investigate the impact of DBS settings on sleep efficiency and neural signatures during sleep
Background:
In recent years, there has been significant progress in refining DBS settings to effectively manage symptoms like tremor, rigidity, and bradykinesia in patients with PD. However, one aspect that has received limited attention is the impact of DBS on sleep quality – a crucial yet often overlooked component of daily life. While some evidence suggests that DBS may improve sleep efficiency and reduce daytime sleepiness, the underlying reasons remain unclear.
Recent advancements in DBS electrode sensing capabilities have shed new light on the potential to monitor and influence sleep patterns. It is now possible to differentiate between sleep and wakefulness, as well as identify specific sleep stages, using DBS sensing technology. This presents an exciting opportunity to intervene and enhance sleep quality for PD patients.
Methods/Design:
We will monitor 10 participants for six weeks in their home environment, with each participant alternating between three different device settings every two weeks. They will wear a device to track their sleep and undergo a one-night detailed sleep study to ensure accuracy.
Relevance to Diagnosis/Treatment of Parkinson’s Disease:
By correlating DBS settings with objective sleep data and patient-reported outcomes, our study aims to enhance our comprehension of how DBS impacts sleep in PD patients. Ultimately, this research may guide personalized adjustments to DBS settings to enhance sleep quality, a vital aspect of overall well-being for PD patients. Furthermore, our research has the potential to contribute to the development of closed-loop adaptive DBS systems tailored to improving sleep quality in PD patients. Lastly, our findings will serve as a foundation for further investigations into innovative approaches to DBS programming and personalized treatment strategies aimed at enhancing sleep quality and overall patient well-being in PD.