Bibliographic record
Abstract
Obstructive sleep apnea (OSA) is a treatable disorder with a multifaceted pathophysiology. There has been increasing concern in the effects of OSA on brain, particularly in the elderly and in patients with neurodegenerative diseases such has Parkinson’s disease (PD), Alzheimer’s disease (AD) and stroke. OSA has the potential to exacerbate PD-related symptoms and the underlying neuropathology. While increasing data on OSA supports its role in higher risk of cognitive decline and Alzheimer-type dementia, a knowledge gap continues to exist regarding relationships between OSA and PD, particularly from prospective cohort studies. Questionnaires that identify OSA, in lieu of polysomnography (PSG), could be helpful in studying larger groups. Despite the validation of several questionnaires for OSA screening in the general population, there is a scarcity of studies evaluating the diagnostic precision of these tools in PD populations. My first objective of this thesis was to validate self-reported sleep questionnaires for OSA detection in PD individuals. My second objective was to evaluate the prevalence of questionnaire-based OSA risk in individuals with PD, and with other frequent neurological conditions in a population-based cohort. My last objective was to determine whether OSA is associated with greater dysfunction in specific cognitive domains in individuals with PD from a population cohort. These aims have led to three research articles. My first article allowed to assess the diagnostic precision of four OSA screening tools to identify OSA in PD patients selected from the McGill Movement Disorder Clinic. Both STOP-B28 and STOP questionnaires exhibited the most favorable qualities for detecting PSG-defined OSA in patients with PD and showed the strongest association with clinical outcomes related to OSA. The second article examined the prevalence of high risk of OSA, as determined by commonly used questionnaires, and self-reported OSA diagnosis among individuals with stroke, Alzheimer's disease, PD, and the general population (GP) in the Canadian Longitudinal Study on Aging (CLSA). This is a national, long-term population-based study on healthy aging that recruited individuals between the ages of 45 and 85 without any major cognitive impairment. There were extensive variations in the prevalence of high-risk of OSA depending on which of the screening questionnaires were used, emphasizing the need to validate these tools in older adults with neurological conditions. Self-reported OSA rates were notably low across all groups, hinting at a potential underdiagnosis or patient underreporting. The third article assessed the association between high risk of OSA and cognitive function in patients with PD from the CLSA . A strong association emerged between high risk of OSA and reduced executive function in individuals with PD, especially in females. The impact of OSA on cognitive health can vary depending on the sex of the individuals. The work presented in this thesis enhances our understanding of the relationship between OSA and neurological diseases of aging, particularly PD. It shows that different OSA screening tools show highly variable prevalence of OSA in neurological diseases of aging. This emphasizes the need to validate OSA diagnostic tools specifically in these populations. My work has defined the accuracy of OSA screening tools in PD, which will help with further work in this field. Furthermore, I have found that OSA is associated with reduced cognitive function in PD in a population cohort. Results support wider screening for OSA in PD patients and additional research on OSA therapies. Amelioration of OSA could not only improve PD patient symptoms and well-being but also slow the progression of the neurodegenerative process. OSA treatment trials will be required to evaluate whether OSA-related effects are indeed modifiable.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| 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 | 0.001 |
| 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".