Sleep Quality in Neuromyelitis Optica Spectrum Disorder: A Systematic Review
Bibliographic record
Abstract
ABSTRACT BACKGROUND: This review summarizes the literature on sleep quality in neuromyelitis optica spectrum disorder (NMOSD) and discusses these findings in the context of current knowledge of sleep physiology. METHODS: A literature search was performed using Ovid MEDLINE, Embase, and Scopus from inception to September 3, 2020. All included studies reported at least 1 measure of sleep quality in individuals with NMOSD. Pittsburgh Sleep Quality Index (PSQI) scores of individuals from 4 studies were compared with those from a data set of controls. RESULTS: Thirteen studies (1041 individuals with NMOSD) were included in the review. Disturbed sleep was demonstrated across subjective metrics based on patient surveys and objective metrics such as polysomnography. An estimated 70% of individuals with NMOSD can be classified as poor sleepers. Standardized mean difference between PSQI scores of 183 individuals with NMOSD and those of 9284 controls was 0.72 (95% CI, 0.57–0.86; P < .001). Decreased sleep quality was significantly associated with decreased quality of life and increased anxiety, depression, and disability status. Sleep disturbances in NMOSD were similar in severity to those in multiple sclerosis. CONCLUSIONS: Sleep disturbances are a major contributor to NMOSD disease burden and may arise from the disruption of sleep circuitry, in addition to physical and psychological complications. Multiple processes involved in sleep regulation may be affected, such as, but not limited to, neural circadian circuit disruption, direct effects of inflammation, aminergic projecting system abnormalities, glymphatic system impairment, and development of sleep disorders such as restless legs syndrome/sleep apnea. A better understanding of these mechanisms is necessary for developing effective therapies for NMOSD-associated sleep disturbances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".