Insomnia, Sleep Quality, and Quality of Life in Mild to Moderate Parkinson’s Disease
Bibliographic record
Abstract
RATIONALE: Sleep disorders are prevalent in Parkinson's disease but underreported in clinical settings. The contribution of sleep disorders to health-related quality of life (HRQOL) for patients with this degenerative neurological disease are not well known. OBJECTIVES: To evaluate the impact of insomnia symptoms, obstructive sleep apnea (OSA), and poor sleep quality on HRQOL in a cohort of patients with idiopathic Parkinson's disease. METHODS: We enrolled a convenience sample of 66 adults seen in the University of Miami Movement Disorders Clinic between July 2011 and June 2013. Participants completed validated questionnaires to determine insomnia symptoms, OSA risk, depression, anxiety, and HRQOL. All patients underwent unattended polysomnography to confirm OSA. Results were compared for those with and without insomnia symptoms. Principal component and regression analyses were performed to evaluate determinants of HRQOL. MEASUREMENTS AND MAIN RESULTS: Participants were predominately Hispanic males with mild to moderate Parkinson's disease. Insomnia symptoms were reported for 46% of the study subjects. OSA (apnea-hypopnea index, ≥5) was noted in 47%, with a mean apnea-hypopnea index of 8.3 ± 11.0. Fairly bad to very bad sleep quality was reported by 21% of the participants. Insomnia (r = 0.71; P < 0.001), daytime sleepiness (r = 0.36; P = 0.003), depression symptoms (r = 0.44; P < 0.001), and anxiety symptoms (r = 0.33; P = 0.006) were significant correlates of poor sleep quality. OSA, severity of Parkinson's disease, and dopaminergic therapy were not. In the principal component analysis, sleep quality was a significant component of the "psychological factor" that in turn was a significant determinant of overall HRQOL. CONCLUSIONS: Insomnia symptoms, OSA, and subsequent poor sleep quality are prevalent in Parkinson's disease. In this single-center, exploratory study, we found that insomnia and poor sleep quality, but not OSA, play important roles in determining overall quality of life for patients with this disease. Clinical trial registered with www.clinicaltrials.gov (NCT02034357).
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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 | 0.001 |
| 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".