Elevated Risk of Sleepiness-Related Motor Vehicle Accidents in Patients With Obstructive Sleep Apnea Syndrome: A Case-Control Study
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Bibliographic record
Abstract
OBJECTIVES: The present case-control study aimed to determine whether obstructive sleep apnea syndrome (OSAS) patients are at an increased risk for sleepiness-related motor vehicle accidents (MVAs) than controls and to identify disease-related factors associated with accident risk. METHODS: Demographic, anthropometric, clinical, and polysomnographic parameters of 312 OSAS patients were compared with 156 age- and sex-matched primary snoring subjects. RESULTS: The rate of OSAS patients reporting accident was higher than snoring subjects (21.2% vs. 11.5%, P = .011), and OSAS was associated with an increase in accident risk (odds ratio = 2.06, 95% confidence interval [CI], 1.17 to 3.61, P = .012). Younger OSAS patients (P = .001) and those who were male (P = .001), had greater neck circumference (P = .002), had a higher Epworth sleepiness score (ESS; P < .0001), and had a higher apnea-hypopnea index (AHI; p = .039) had more MVAs than OSAS patients. Daytime sleepiness was associated with a 2.74-fold increase (95% CI, 1.54 to 4.87, P = .001) in accident risk. In multiple logistic regression analysis, accident risk was associated with neck circumference (P < .031) and ESS (P < .0001). In addition, accident risk could be excluded in OSAS patients with neck circumference < 43 cm and ESS < 11 (sensitivity 33.3%, specificity 85.8%). CONCLUSIONS: The present results show that OSAS patients have a twofold higher risk of traffic accidents than control subjects, and increased neck circumference and excessive daytime sleepiness are useful in predicting OSAS patients at higher risk of having accidents.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it