Correlates of excessive daytime sleepiness in de novo Parkinson's disease: A case control study
Bibliographic record
Abstract
OBJECTIVE: This study was undertaken to determine the frequency and correlates of excessive daytime sleepiness in de novo, untreated Parkinson's disease (PD) patients compared with the matched healthy controls. METHODS: Data were obtained from the Parkinson's Progression Markers Initiative, an international study of de novo, untreated PD patients and healthy controls. At baseline, participants were assessed with a wide range of motor and nonmotor scales, including the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Excessive daytime sleepiness was assessed based on the Epworth Sleepiness scale (ESS), with a cutoff of 10. RESULTS: Four hundred twenty-three PD subjects and 196 healthy controls were recruited into the study. Mean ESS (min, max) score was 5.8 (0, 20) for the PD subjects and 5.6 (0, 19) for healthy controls (P = 0.54). Sixty-six (15.6%) PD subjects and 24 (12%) healthy controls had ESS of at least 10 (P = 0.28). No difference was seen in demographic characteristics, age of onset, disease duration, PD subtype, cognitive status, or utilization of sedatives between the PD sleepiness-positive versus the negative group. The sleepiness-positive group had higher MDS-UPDRS Part I and II but not III scores, and higher depression and autonomic dysfunction scores. Sleepiness was associated with a marginal reduction of A-beta (P = 0.05) but not alpha-synuclein spinal fluid levels in PD. CONCLUSIONS: This largest case control study demonstrates no difference in prevalence of excessive sleepiness in subjects with de novo untreated PD compared with healthy controls. The only clinical correlates of sleepiness were mood and autonomic dysfunction. Ongoing longitudinal analyses will be essential to further examine clinical and biological correlates of sleepiness in PD and specifically the role of dopaminergic therapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".