Acute rhinosinusitis among pediatric patients with allergic rhinitis: A nationwide, population-based cohort study
Bibliographic record
Abstract
BACKGROUND: While chronic rhinosinusitis is a common complication of allergic rhinitis, the link between acute rhinosinusitis and allergic rhinitis is unclear. The aim of this study was to evaluate the risk of incident acute rhinosinusitis among pediatric patients with allergic rhinitis, using a nationwide, population-based health claims research database. METHODS: Newly diagnosed allergic rhinitis patients aged 5-18 years were identified from the health claim records of the Longitudinal Health Insurance Database 2000 of Taiwan's National Health Insurance Research Database. A comparison cohort was assembled by randomly selecting patients from the same database with frequency matching by sex, age group, and index year. All patients were followed until a diagnosis of acute rhinosinusitis or the end of the follow-up period. Cox proportional hazards model was used to assess the association between allergic rhinitis and acute rhinosinusitis. RESULTS: Of the 43,588 pediatric patients included in this study, 55.4% were male and 43.9% were between the ages of 5.0-7.9 years. The risk of acute rhinosinusitis was significantly higher in pediatric patients with allergic rhinitis compared to those without the condition (adjusted hazard ratio = 3.03, 95% confidence interval = 2.89-3.18). Similar hazard ratios were observed between male and female pediatric patients. CONCLUSIONS: This secondary cohort study using a nationwide, population-based health claim data of the Taiwan's NHIRD showed that allergic rhinitis was significantly associated with a higher risk of acute rhinosinusitis among pediatric patients.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".