A Decision Rule for Diagnostic Testing in Obstructive Sleep Apnea
Bibliographic record
Abstract
Obstructive sleep apnea (OSA) is traditionally diagnosed using overnight polysomnography. Decision rules may provide an alternative to polysomnography. A consecutive series of patients referred to a tertiary sleep center underwent prospective evaluation with the upper airway physical examination protocol, followed by determination of the respiratory disturbance index using a portable monitor. Seventy-five patients were evaluated with the upper airway physical examination protocol. Historic predictors included age, snoring, witnessed apneas, and hypertension. Physical examination-based predictors included body mass index, neck circumference, mandibular protrusion, thyro-rami distance, sterno-mental distance, sterno-mental displacement, thyro-mental displacement, cricomental space, pharyngeal grade, Sampsoon-Young classification, and over-bite. A decision rule was developed using three predictors: a cricomental space of 1.5 cm or less, a pharyngeal grade of more than II, and the presence of overbite. In patients with all three predictors (17%), the decision rule had a positive predictive value of 95% (95% confidence interval [CI], 75-100%) and a negative predictive value of 49% (95% CI, 35-63%). A cricomental space of more than 1.5 cm (27% of patients) excluded OSA (negative predictive value of 100%, 95% CI, 75-100%). Comparable performance was obtained in a validation sample of 50 patients referred for diagnostic testing. This decision rule provides a simple, reliable, and accurate method of identifying a subset patients with, and perhaps more importantly, without OSA.
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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 | 0.012 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".