An evaluation of rural–urban disparities in treatment outcomes for obstructive sleep apnoea: study protocol for a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Obstructive sleep apnoea (OSA) is a common and treatable chronic condition that is associated with significant morbidity and economic cost. Geography is increasingly being recognised as a barrier to diagnosis and treatment of many chronic diseases; however, no study to date has investigated the impact of place of residence on health outcomes in OSA. OBJECTIVE: rural settings. METHODS: A prospective cohort design will be used. Participants will be recruited through community-based CPAP providers and assigned to either the rural or urban cohort based on residential postal code. The primary outcome will be the difference in nightly hours of CPAP use between the two groups, measured 3 months after initiation of therapy. Secondary outcomes will include symptoms, quality of life, patient satisfaction and patient-borne costs. ANTICIPATED RESULTS: This study will determine whether there are differences in CPAP adherence or patient-reported outcomes between rural and urban patients with OSA. These results will highlight potential challenges with providing OSA care in rural populations and may inform health interventions to reduce urban-rural inequities.
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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 | 0.048 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.006 |
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".