Increased Incidence of Obstructive Sleep Apnea in Hospitalized Children After Enterovirus Infection: A Nationwide Population-based Cohort Study
Bibliographic record
Abstract
BACKGROUND: We report the first nationwide population-based cohort study using Taiwan's National Health Insurance Research Database on the association between enterovirus (EV) infection and the incidence of sleep disorders in a pediatric population. METHODS: Two matched groups of children under 18 years of age were included in the analyses for nonapneic sleep disorder and obstructive sleep apnea (OSA). Among them, 316 subjects were diagnosed with OSA during the surveillance period, including 182 in the EV infection group and 134 in the non-EV infection group. RESULTS: Hospitalization because of EV infection was associated with OSA after adjusting for age, sex, urbanization atopic disease and perinatal complications (adjusted hazard ratio: 1.62, 95% confidence interval: 1.18-2.21; P = 0.003). An additional factor significantly associated with sleep apnea was allergic rhinitis (hazard ratio: 4.82, 95% confidence interval: 3.45-6.72). CONCLUSIONS: Children with severe EV infection (ie, requiring hospitalization) carry a significantly higher risk of developing OSA, particularly in those with allergic rhinitis. As pediatric obstructive sleep apnea is a treatable sleep disorder, we emphasize regular follow-up and early detection in children with EV infection.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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 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".