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Computer-based Multitaper Spectrogram Program for Electroencephalographic Data
Published on: November 13, 2019
Cardiopulmonary Coupling Spectrogram as an Ambulatory Method for Assessing Sleep Disorders in Patients With
Jinchi Liao1, Yi Lu1, Yaxin Lu1
1From the Department of Neurology (J.L., Y.H., Y.W., L.L., X.H., Z.L., W.Q., Y.S.), The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou; Department of Neurology (Yi Lu), The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen; and Clinical Data Center (Yaxin Lu), The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Patients with autoimmune encephalitis (AE) experience significant sleep disorders, often linked to autonomic dysfunction. Cardiopulmonary coupling (CPC) monitoring shows promise in assessing and potentially predicting these sleep disturbances in AE patients.
Area of Science:
- Neurology
- Sleep Medicine
- Cardiology
Background:
- Sleep disorders are prevalent and clinically significant in autoimmune encephalitis (AE) but remain poorly understood.
- Cardiopulmonary coupling (CPC), an electrocardiogram-based portable sleep monitoring technology, has not been extensively evaluated for sleep disorder assessment in AE.
Purpose of the Study:
- To evaluate the utility of cardiopulmonary coupling (CPC) in assessing sleep disorders in patients with autoimmune encephalitis (AE).
- To compare sleep parameters between AE patients and healthy controls using CPC monitoring.
Main Methods:
- Sixty patients diagnosed with AE were age- and sex-matched with 66 healthy control subjects.
- All participants underwent CPC testing, and data on demographics, clinical information, and Pittsburgh Sleep Quality Index (PSQI) scores were collected.
- Statistical analysis was performed using R language programming software.
Main Results:
- AE patients exhibited significantly higher PSQI scores, lower sleep efficiency (SE), reduced high-frequency coupling, increased REM sleep, and higher wakefulness percentages compared to controls.
- CPC-derived metrics revealed a higher low-frequency to high-frequency (LF/HF) ratio and a greater respiratory disturbance index in AE patients.
- Follow-up in 14 AE patients indicated improvements in PSQI scores and SE, with decreased wakefulness, suggesting potential for recovery during remission.
Conclusions:
- Sleep disorders, often accompanied by autonomic dysfunction, are common in patients with AE.
- Improvements in PSQI scores and SE appear to precede the full restoration of sleep microstructural disruption during remission.
- CPC parameters show potential as valuable tools for predicting and monitoring sleep disorders in AE patients.
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