Sleep-related symptoms in multiple system atrophy: determinants and impact on disease severity
Bibliographic record
Abstract
BACKGROUND: Sleep disorders are common but under-researched symptoms in patients with multiple system atrophy (MSA). We investigated the frequency and factors associated with sleep-related symptoms in patients with MSA and the impact of sleep disturbances on disease severity. METHODS: This cross-sectional study involved 165 patients with MSA. Three sleep-related symptoms, namely Parkinson's disease (PD)-related sleep problems (PD-SP), excessive daytime sleepiness (EDS), and rapid eye movement sleep behavior disorder (RBD), were evaluated using the PD Sleep Scale-2 (PDSS-2), Epworth Sleepiness Scale (ESS), and RBD Screening Questionnaire (RBDSQ), respectively. Disease severity was evaluated using the Unified MSA Rating Scale (UMSARS). RESULTS: The frequency of PD-SP (PDSS-2 score of ≥18), EDS (ESS score of ≥10), and RBD (RBDSQ score of ≥5) in patients with MSA was 18.8%, 27.3%, and 49.7%, respectively. The frequency of coexistence of all three sleep-related symptoms was 7.3%. Compared with the cerebellar subtype of MSA (MSA-C), the parkinsonism subtype of MSA (MSA-P) was associated with a higher frequency of PD-SP and EDS, but not of RBD. Binary logistic regression revealed that the MSA-P subtype, a higher total UMSARS score, and anxiety were associated with PD-SP; that male sex, a higher total UMSARS score, the MSA-P subtype, and fatigue were associated with EDS; and that male sex, a higher total UMSARS score, and autonomic onset were associated with RBD in patients with MSA. Stepwise linear regression showed that the number of sleep-related symptoms (PD-SP, EDS, and RBD), disease duration, depression, fatigue, and total Montreal Cognitive Assessment score were predictors of disease severity in patients with MSA. CONCLUSIONS: Sleep-related disorders were associated with both MSA subtypes and the severity of disease in patients with MSA, indicating that sleep disorders may reflect the distribution and degree of dopaminergic/non-dopaminergic neuron degeneration in MSA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".