More Than the Sum of the Respiratory Events: Personalized Medicine Approaches for Obstructive Sleep Apnea
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Traditionally, the presence and severity of obstructive sleep apnea (OSA) have been defined by the apnea-hypopnea index (AHI). Continuous positive airway pressure is generally first-line therapy despite low adherence, because it reliably reduces the AHI when used, and the response to other therapies is variable. However, there is growing appreciation that the underlying etiology (i.e., endotype) and clinical manifestation (i.e., phenotype) of OSA in an individual are not well described by the AHI. We define and review the important progress made in understanding and measuring physiological mechanisms (or endotypes) that help define subtypes of OSA and identify the potential use of genetics to further refine disease classification. This more detailed understanding of OSA pathogenesis should influence clinical treatment decisions as well as help inform research priorities and clinical study design. In short, treatments could be individualized on the basis of the underlying cause of OSA; patients could better understand which symptoms and outcomes will respond to OSA treatment and by how much; and researchers could select populations most likely to benefit from specific treatment approaches for OSA.
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.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.012 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it