Sleep Disorders and Future Diagnosis of Parkinsonism: A Prospective Study Using the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
BACKGROUND: Earlier detection of parkinsonism, specifically during its prodromal stage, may be key to preventing its progression. Previous studies have produced contradictory results on the association between sleep symptoms and prodromal parkinsonism. OBJECTIVE: We conducted a prospective study within the Canadian Longitudinal Study on Aging (CLSA) to determine whether self-reported symptoms of insomnia, somnolence, apnea, and restless legs syndrome predate the diagnosis of parkinsonism after three years of follow-up. METHODS: At baseline, amongst other information, participants completed a questionnaire for difficulty initiating or maintaining sleep, daytime somnolence, snoring or stopping breathing during sleep, and symptoms of restless legs syndrome. After 3 years of follow-up, baseline responses from participants who self-reported a new diagnosis of parkinsonism (cases) were compared to those who did not (controls). For each case, 10 controls were individually matched by age, sex, education, BMI, caffeine, smoking, and alcohol. Binary unconditional logistic regression models were used to estimate the association between sleep symptoms and new-onset parkinsonism, adjusting for age, sex, education, BMI, smoking, alcohol, and caffeine. RESULTS: We identified 58 incident-parkinsonism cases and 580 matched controls (65.5%male, mean age = 69.60, SD = 8.0). Baseline symptoms of sleep-onset insomnia (12.1%vs. 13.0%, Adjusted OR[95%CI] = 0.87[0.32,2.33]), sleep-maintenance insomnia (24.1%vs. 20.2%, AOR = 1.01[0.46,2.20]), daytime somnolence (8.6%vs. 7.4%, AOR = 1.11[0.37,3.39]), obstructive sleep apnea (27.3%vs. 26.2%, AOR = 0.84[0.40,1.79]), and restless leg syndrome (20.6%vs. 9.9%, AOR = 1.34[0.42,4.25]) were similar among those who developed parkinsonism and those who did not. CONCLUSION: Symptoms of insomnia, somnolence, apnea, and restless legs did not predate a new diagnosis of parkinsonism over 3 years.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".