Epidemiologic profile of obstructive sleep apnea patients attending a dental sleep medicine clinic in a University setting
Bibliographic record
Abstract
Introduction: Obstructive sleep apnea (OSA) is a common sleep breathing disorder characterized by recurrent episodes of hypopnea (reduced airflow) and apnea (breathing cessation for at least 10 seconds).OSA is a growing health concern and Canadian data reports approximately 3% of Canadian adults to be affected.Objectives: The overarching goal of this retrospective study is to contribute to national and international epidemiologic research data on OSA. Materials and Methods:A retrospective chart review was performed of all patients who were referred to the dental sleep medicine (DSM) clinic at the College of Dentistry, University of Manitoba, for the period of June 2014 to May 2016.A questionnaire was devised to obtain and filter information from both electronic and paper patient chart sources.All patient information used in this study was obtained in compliance with the Freedom of Information and Protection of Privacy Act (FIPPA) regulations.Results: A total of 201 patients were referred to DSM Clinic; the majority of the referred patients were males (61%) and the age of patients ranged from 18 to 80 years old with an average age of 49 years.Close to one third of referred patients had a diagnosis of mild OSA, followed by near even frequencies for moderate OSA and severe OSA.The epidemiological profile of patients seen in this study correlates with Canadian national statistics as reported by the Public Health Agency of Canada (2009).
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".