Sleep Disorders in Patients with Parkinson's Disease during COVID-19 Pandemic
Bibliographic record
Abstract
Objective: To assess the impact of coronavirus disease 2019 (COVID-19) pandemic on sleep disorders among Parkinson's disease (PD) patients using validated questionnaires. Materials and Methods: This prospective study involved 50 PD patients and 50 age, gender, and body mass index-matched controls. All participants underwent assessment of cognition using Montreal Cognitive Assessment scale, sleep quality using Parkinson's disease sleep scale-2 (PDSS-2; for PD patients) and Pittsburgh Sleep Quality Index (PSQI; for PD patients and healthy controls), excessive daytime sleepiness (EDS) using Epworth sleepiness scale (ESS), insomnia symptoms and severity using insomnia severity index (ISI), restless legs syndrome (RLS) using International RLS Study Group criteria, rapid eye movement sleep behavior disorder (RBD) using RBD Single-Question Screen (RBD1Q), and depression using Patient Health Questionnaire-9 scale. Results: Eighty-eight percent of PD patients reported one or more sleep disorders, compared to 28% controls. While 72% of PD patients reported poor sleep quality (PDSS-2 ≥15, PSQI >5), 60% had insomnia, 58% reported RBD, 50% had EDS, and 36% reported RLS. Depressive symptoms were reported by 70% patients. PD patients with and without poor sleep quality were comparable with regards to demographic and clinical variables, except for depressive symptoms ( P < 0.001). Depressive symptoms showed a significant association with EDS ( P = 0.008), RBD ( P < 0.001), and insomnia ( P = 0.001). Conclusion: Prevalence of sleep disorders increased in PD patients during the COVID-19 pandemic. Prevalence of EDS, RBD, and RLS in PD patients was higher compared to that reported in studies during the pre-COVID-19 times. Presence of depressive symptoms was a significant correlate of presence of sleep disorders in PD patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".