Obstructive sleep apnea and quality of life: comparison of the SAQLI, FOSQ, and SF-36 questionnaires
Bibliographic record
Abstract
INTRODUCTION: The impact of sleep on quality of life (QoL) has been well documented; however, there is a great need for reliable QoL measures for persons with obstructive sleep apnea (OSA). We compared the QoL scores between the 36-Item Short Form of the Medical Outcomes Survey (SF-36), Calgary Sleep Apnea Quality of Life Index (SAQLI), and Functional Outcomes Sleep Questionnaire (FOSQ) in persons with OSA. METHODS: A total of 884 participants from the Sleep Heart Health Study second examination, who completed the SF-36, FOSQ, and SAQLI, and in-home polysomnograms, were included. The apnea hypopnea index (AHI) at 4% desaturation was categorized as no OSA (<5 /hour), mild to moderate OSA (5-30 /hour) and severe OSA (>30 /hour). QoL scores for each questionnaire were determined and compared by OSA severity category and by gender. RESULTS: , p<.0001). The SF-36 PCS and Mental Component Scores (MCS) were correlated with the FOSQ and SAQLI (r=.37 PCS vs FOSQ; r=.31 MCS vs FOSQ; r=.42 PCS vs SAQLI; r=.52 MCS vs SAQLI; and r=.66 FOSQ vs SAQLI, p<.001 for all correlations). Linear regression analyses, adjusting for potential confounders, indicated that the impact of OSA severity on QoL is largely explained by the presence of daytime sleepiness. CONCLUSION: The impact of OSA on QoL differs between genders with a larger effect on females and is largely explained by the presence of daytime sleepiness. Correlations among QoL instruments are not high and various instruments may assess different aspects of QoL.
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How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".