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Epilepsy, a prevalent neurological disorder, affects 40% of patients with uncontrolled seizures despite medications. Sleep disturbance exacerbates epilepsy, and vice versa, but existing literature suffers from limitations. Studies conducted in hospital settings provide only brief observation periods and fail to capture the natural sleep environment. Wearable technology offers a promising solution, providing a nuanced understanding of the relationship between seizures and sleep. The Dreem headband, an EEG-based wearable, is well-suited for such studies, offering ease of use and validated accuracy. This technology enables extended observation periods under stable medication conditions, essential for assessing the complex interplay between sleep and epilepsy. By elucidating the impact of sleep on seizures, the researchers seek to identify patient populations where sleep significantly influences seizure susceptibility, ultimately informing personalized epilepsy treatments.
The first aim of this study is to investigate how variations in sleep timing, duration, and structure influence seizure risk, particularly in individuals with sleep-sensitive seizures. The investigators will conduct longitudinal EEG assessments to analyze how changes in sleep features correlate with interictal epileptiform discharge rates and seizure occurrences over time.
The second aim is to develop a sleep quality index that predicts individual risk for sleep-sensitive seizures, the Sleep-Sensitive Epilepsy Risk Index (SERI). This index aims to predict an individual's seizure risk associated with disrupted sleep, facilitating personalized and preventative patient care.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Dreem headband | Experimental | Participants will wear a Fitbit daily and a Dreem headband exclusively at night in their homes over a 21-day period as part of the data collection protocol. Additionally, they will maintain daily sleep and seizure diaries. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Dreem headband | Device | The Dreem headband is an EEG-based wearable tool that can be used to reliably assess the relationship between sleep and epilepsy over extended observation periods. |
| Measure | Description | Time Frame |
|---|---|---|
| Total sleep time (sleep macrostructure) | Total sleep time as measured by the Dreem headband | 21 days |
| Spike rates per hour (epilepsy marker) | Spikes will be detected by the Dreem headband | 21 days |
| Seizure frequency per night (epilepsy marker) | Seizures will be detected by the Dreem headband | 21 days |
| Measure | Description | Time Frame |
|---|---|---|
| Sleep latency (sleep macrostructure) | Sleep latency as measured by the Dreem headband | 21 days |
| Wake after sleep onset (sleep macrostructure) | Wake after sleep onset as measured by the Dreem headband |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Birgit Frauscher, MD PD | Contact | 9196139386 | birgit.frauscher@duke.edu |
| Name | Affiliation | Role |
|---|---|---|
| Birgit Frauscher, MD PD | Duke University | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Duke University Health System | Recruiting | Durham | North Carolina | 27710 | United States |
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| ID | Term |
|---|---|
| D000069279 | Drug Resistant Epilepsy |
| D004827 | Epilepsy |
| ID | Term |
|---|---|
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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All participants will initially undergo a screening night at a sleep lab before being equipped with a Dreem EEG headband and a Fitbit for continuous monitoring of sleep patterns and epileptic activity at home. Over 21 days, participants will wear the Fitbit daily and the Dreem headband exclusively at night as part of the data collection protocol. Additionally, participants will maintain daily sleep and seizure diaries.
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| 21 days |
| Sleep efficiency (sleep macrostructure) | Sleep efficiency as measured by the Dreem headband | 21 days |
| Sleep stage distribution (sleep macrostructure) | Sleep stage distribution as measured by the Dreem headband | 21 days |
| Sleep spindle events (sleep microstructure) | Sleep spindles (10-16 Hz; duration 0.5-3 sec) as measured by the Dreem headband | 21 days |
| Sleep slow wave events (sleep microstructure) | Slow waves (0.5-4 Hz) as measured by the Dreem headband | 21 days |
| Performance the SERI model, as measured by the area under the receiver operating characteristic curve | The Sleep-Sensitive Epilepsy Risk Index (SERI) aims to predict an individual's seizure risk associated with disrupted sleep. A high SERI will indicate a high risk for sleep-sensitive seizures, while a low value will indicate a low risk. | Up to 2 years after study commencement |
| Sensitivity of the SERI model | The Sleep-Sensitive Epilepsy Risk Index (SERI) aims to predict an individual's seizure risk associated with disrupted sleep. A high SERI will indicate a high risk for sleep-sensitive seizures, while a low value will indicate a low risk. | Up to 2 years after study commencement |
| Specificity of the SERI model | The Sleep-Sensitive Epilepsy Risk Index (SERI) aims to predict an individual's seizure risk associated with disrupted sleep. A high SERI will indicate a high risk for sleep-sensitive seizures, while a low value will indicate a low risk. | Up to 2 years after study commencement |
| Performance the SERI model, as measured by F1-score | The Sleep-Sensitive Epilepsy Risk Index (SERI) aims to predict an individual's seizure risk associated with disrupted sleep. A high SERI will indicate a high risk for sleep-sensitive seizures, while a low value will indicate a low risk. The F1 score ranges from 0 to 1. A value of 0 indicates poor performance, and a value of 1 represents perfect performance. | Up to 2 years after study commencement |