Recommendations for clinical management of excessive daytime sleepiness in obstructive sleep apnoea – A Delphi consensus study
Bibliographic record
Abstract
STUDY OBJECTIVE: Excessive daytime sleepiness is common with obstructive sleep apnoea and can persist despite efforts to optimise primary airway therapy. The literature lacks recommendations regarding differential diagnosis and management of excessive daytime sleepiness in obstructive sleep apnoea. This study sought to develop expert consensus statements to bridge the gap between existing literature/guidelines and clinical practice. METHODS: A panel of 10 international experts was convened to undertake a modified Delphi process. Statements were developed based on available evidence identified through a scoping literature review, and expert opinion. Consensus was achieved through 3 rounds of iterative, blinded survey voting and revision to statements until a predetermined level of agreement was met (≥80 % voting "strongly agree" or "agree with reservation"). RESULTS: Consensus was achieved for 32 final statements. The panel agreed excessive daytime sleepiness is a patient-reported symptom. The importance of subjective/objective evaluation of excessive daytime sleepiness in the initial evaluation and serial management of obstructive sleep apnoea was recognised. The differential diagnosis of residual excessive daytime sleepiness in obstructive sleep apnoea was discussed. Optimizing airway therapy (eg, troubleshooting issues affecting effectiveness) was addressed. The panel recognised occurrence of residual excessive daytime sleepiness in obstructive sleep apnoea despite optimal airway therapy and the need to evaluate patients for underlying causes. CONCLUSIONS: Excessive daytime sleepiness in patients with obstructive sleep apnoea is a public health issue requiring increased awareness, recognition, and attention. Implementation of these statements may improve patient care, long-term management, and clinical outcomes in patients with obstructive sleep apnoea.
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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 | 0.299 | 0.280 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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; 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".