Translation and validation of the STOP-Bang questionnaire into Slovene
Bibliographic record
Abstract
PURPOSE: To translate, culturally adapt and evaluate the Slovene version of the STOP-Bang questionnaire (SBQ) for use in the sleep clinic. METHODS: Standard forward-backward translation and harmonisation of the Slovene translation of the SBQ were performed. Test-retest reliability was performed on a sample of healthy subjects. A cross-sectional study was performed with patients referred for a sleep study. Patients filled out the Slovene translation of the SBQ before undergoing sleep study. RESULTS: The validation group consisted of 256 patients, of which 237 (92.6%) were included. Mean age was 52.5 ± 14.6, 63.3% of patients were male. Obstructive sleep apnoea (OSA) (apnoea-hypopnea index (AHI) ≥ 5) was present in 69.6% of patients, of whom 22.4% had mild (AHI ≥ 5 and < 15), 21.9% moderate (AHI ≥ 15 and < 30), and 25.3% severe (AHI ≥ 30) OSA. A SBQ score of 3 had a sensitivity of 92.1 (86.9-95.7), specificity of 44.4 (32.7-56.6), PPV of 79.2 (75.5-82.4) and AUC of 0.757 (95% CI 0.692-0.823; p < 0.001) for all OSA (AHI ≥ 5). Each increase in the SBQ score was associated with an increase in the probability of OSA. CONCLUSION: This study shows that the Slovene version of the SBQ is a valid tool for evaluating the risk of OSA in a sleep clinic.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".