Predisposição da apneia e seus impactos na sonolência diurna e qualidade de vida na obesidade
Bibliographic record
Abstract
This research evaluated the risk of obstructive sleep apnea through apnea questionnaires and scales in obese patients and examined their impact on quality of life. For this, 51 obese patients of both sexes had their anthropometric and biochemical parameters measured. The presence of respiratory disorders was assessed using the NoSAS score (Neck, Obesity, Snoring, Age, Sex). The risk of apnea was verified using the STOP-BANG questionnaire (Snore, Tiredness, Observed, Blood Pressure, Body mass index, Age, Neck, Gender). We measured daytime sleepiness using the Epworth scale. The impact of apnea on quality of life was assessed using the Quebec Sleep Questionnaire. STOP-BANG results showed that 88.24% of women and 100% of men were at high risk for apnea. In addition, 70.45% of women and 42.85% of men had hypersomnolence on the Epworth with a score above 10. The groups classified as <10, 10-16, and >16 on the Epworth were evaluated through the sleep questionnaire, and the results showed significant differences in all domains between the <10 and >16 groups (p < 0.01). We concluded that obese patients have a high risk for apnea, with consequences on daytime sleepiness that impact the quality of life of these individuals.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".