Assessing STOP-Bang Questionnaire Sensitivity and Specificity for Sleep Apnea Detection in Iraqi Adults
Bibliographic record
Abstract
Introduction: Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that can lead to severe health complications if left untreated. The STOP-Bang questionnaire, developed in Canada, is a widely used screening tool for OSA. However, the applicability of this tool in different populations, including the Iraqi population, requires further examination due to ethnic and physiological variations, particularly regarding body mass index (BMI). Aim: This study aimed to evaluate the effectiveness of the STOP-Bang questionnaire in detecting OSA among the Iraqi population and to determine whether adjusting the BMI cut-off value could improve its accuracy. Methods: A prospective cross-sectional study was conducted at Khanzad Teaching Hospital in Erbil, Iraq, between January 2022 and December 2023. A total of 500 adult patients (aged 18-60 years) who reported sleep-related
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".