Untangling sex differences in obstructive sleep apnea: a significant step toward precision medicine
Bibliographic record
Abstract
Recent data suggest that the world-wide prevalence of undiagnosed Obstructive Sleep Apnea (OSA) is close to a billion of people (Apnea Hypopnea Index: AHI ≥ 5) [1], and close to half a billion when using a stricter criterion (AHI ≥ 15). OSA is associated with hypertension, stroke, atrial fibrillation [2], certain types of cancer [3], and all-cause mortality [4]. Moreover, the relationship between OSA and cognitive decline has become more established [5]. At the same time, the daytime sleepiness associated with sleep fragmentation, partly attributed to OSA, has been shown to be related with an increased number of road-traffic accidents [6]. This evidence highlights how OSA is a global public health burden with rising healthcare costs. Estimates are up to one and half billion dollars only in the United States [7] where approximately 10 millions of individuals have been diagnosed with OSA while ~23 million remain undiagnosed. By the time OSA is diagnosed, patients often develop secondary comorbidities such as resistant hypertension, uncontrolled diabetes, or stroke.
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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 | 0.029 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".