Outcome measurements in obstructive sleep apnea: Beyond the apnea‐hypopnea index
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: The apnea-hypopnea index (AHI) is overwhelmingly used as the main therapeutic metric in the assessment of obstructive sleep apnea (OSA) in surgical studies. However, using AHI as the sole measure is problematic. This study investigates the utility of other outcome measures for patients with OSA undergoing surgery. STUDY DESIGN: Systematic review of cohort and review studies. METHODS: A review was performed using the PubMed database. English articles focusing on outcome measures in adults with OSA were included. Studies in pediatric populations, those combining obstructing and central sleep apnea, and those without the use of outcome measures were excluded. Articles were categorized according to level of evidence. The Downs and Black scale and AMSTAR scale were used to assess quality. RESULTS: Of a total of 10,454 retrieved articles, 21 studies met inclusion and exclusion criteria. Most articles related to continuous positive airway pressure outcomes. Many categories of outcome measures were found: general quality of life, OSA-specific quality of life, measurements of sleepiness, performance, and physiological. Subjects with OSA scored differently in measurement tools in all categories compared to control populations or after treatment, and generally a poor correlation with AHI was seen. CONCLUSIONS: The literature shows a range of tools based on symptoms and physiology of OSA that can assess effects of treatment. Assessment of surgical treatment for OSA should neither be limited to AHI as an outcome, nor should this be the only outcome stressed.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 0.003 |
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; both teacher heads agree on what is shown here.
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".