1190 Engaging Patients And Family Members To Understand What Matters Most Living With Obstructive Sleep Apnea
Bibliographic record
Abstract
Abstract Introduction As a common but modifiable chronic condition, obstructive sleep apnea (OSA) has been identified as the top secondary cause of many other diseases including cardiovascular diseases and type 2 diabetes. Diagnosing and managing OSA provides neurological, cardiovascular and metabolic benefits, however real-world studies indicate disconnections between evidence and outcomes. Using an engagement approach and qualitative design, this project aims to better understand care and research gaps in OSA in a community healthcare setting. Methods: Methods Patient and family representatives were identified and recruited through OSA support meetings hosted by MultiCare Sleep Medicine Centers, to form a board of 12, with three key patient advocates. Six meetings, each facilitated by one or two members of the board, were held to encourage focus group discussion and accommodate interactive conversations on the topic. Discussions were audio recorded and edited to exclude patients’ identifiable information, then transcribed. Manual open coding was completed by two coders for each transcription to develop a codebook, followed by auto-coding and inductive content analysis using Nvivo 11. Results All enrolled patients had diagnosed moderate-to-severe OSA and were prescribed with continuous positive airway pressure (CPAP) therapy. Two participants were African American and one was multiethnic. Patients’ age ranged from early 30s to 80s. Seven main themes were identified: OSA diagnostic issues; treatment experiences and options; comorbidities; patient community and support needs; long-term management challenges beyond “compliance”; knowledge of OSA, CPAP and care; and patient-driven research. The first few weeks after CPAP initiation appeared to be a critical time window that impacted patients’ adaptation and use. Conclusion Our study revealed barriers and facilitators in OSA diagnosis and treatment. Results showed highly prevalent chronic co-morbidities and the needs to care for patients in the comorbid scenario. It was highlighted that a paradigm of patient-centered care and research is lacking and warranted. Participants also called for better coordination between sleep medicine, primary care, other specialists, durable device suppliers and insurance. Key research efforts are expected to focus on the first 30-day post CPAP dispense to improve compliance. Support Patient Centered Outcomes Research Institute (PCORI) (Contract #: 7717241)
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".