Bibliographic record
Abstract
Excessive daytime sleepiness is prevalent and clinically significant in OSA. Other symptoms are less well-understood, especially in mild OSA population. Objective: Explore symptom phenotypes in adults with mild OSA. Observational study of 22 adults employed convenience sampling at diagnostic polysomnography. Symptom measures: Stanford Sleepiness Scale (SSS) and Lee Fatigue and Energy Scale (LFES) measured before sleep (8:00pm-10:00pm, E) and after sleep (6:00am-7:00am, M). Epworth Sleepiness Scale, Profile of Mood States, Quebec Sleep Questionnaire, Perceived Stress Scale, and Beck Depression Inventory were measured before sleep. Descriptive statistics and cluster analysis for symptom phenotype exploration using cosine similarity to measure distances between symptom vectors and clusters were visualized with network graphs (yED Graph Editor). Middle-age (49.0±17.2 yrs), overweight (34.1±8.7 kg/m2), men (50.0%) and women with OSA (AHI 12.85[IQR 7.8-15.8] events/hr) had morning sleepiness (SSS), high fatigue and low energy (LFES). Two distinct symptom clusters were identified: momentary and lasting symptom clusters. Cluster 1, momentary symptom cluster, included sleepiness (E and M) and fatigue (E and M); cluster 2, lasting symptom cluster, included sleep-related quality of life and energy levels (E and M). In cluster 1, fatigue (E) and sleepiness (E) had the strongest connection, and perceived stress was connected to four different momentary symptoms, including sleepiness (E), sleepiness (M), fatigue (M), and diurnal symptoms, a sleep-related quality of life construct. In cluster 2, symptom vectors shared at least three connections with each other, excepting energy (E). The nocturnal symptom (i.e., nocturia, choking/gasping at night, and snoring), a sleep-related quality of life construct, was the dominant variable, showing six connections with other variables of which four symptoms had strong similarity. Sleepiness over the past month, mood disturbance, and depression were not grouped in any cluster and remained independent of other symptoms. The identified two symptom clusters, momentary and lasting symptoms, in mild OSA may guide symptom management approaches. Future larger studies of mild OSA symptom clusters may suggest reference points for evaluation of mild OSA, including treatment responses. American Nurses Foundation and Sigma Theta Tau International (Hyunju Yang, PI).
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".