Association of Childhood Atopic Dermatitis with a Higher Risk of Health Care Utilization and Drug Use for Asthma: A Nationwide Cohort Study
Bibliographic record
Abstract
BACKGROUND: Overwhelming evidence supports a causal relationship between occurrence of asthma and atopic dermatitis (AD). OBJECTIVE: The aims of the study were to determine the incidence of asthma in children with AD and to examine the health care utilization and drug use for asthma in children with AD. METHODS: Children with hospital-diagnosed AD (cases) were matched with individuals from the background population (controls) in a 1:4 ratio. RESULTS: In the final cohort (18,625 cases and 74,500 controls), the incident cases of asthma were 4203 among AD cases and 5298 in controls, corresponding to incidence rates of 34 and 9 in cases and controls per 1000 person-years, respectively (hazard ratio [HR] = 3.82, 95% confidence interval [CI] = 3.65-4.00). During the 1-year follow-up period from asthma diagnosis, children with concomitant AD had a significantly higher risk of hospital admission (HR = 1.97, 95% CI = 1.63-2.37), emergency department visits (HR = 1.62, 95% CI = 1.22-2.14), outpatient visits (HR = 1.97, 95% CI = 1.74-2.23), asthma medication (HR = 1.31, 95% CI = 1.27-1.35), and rescue course corticosteroids (HR = 1.74, 95% CI = 1.13-2.69) compared with children with asthma only. CONCLUSIONS: The risk of being diagnosed with asthma was higher in children with AD. Risk of health care utilization and drug use for asthma was higher in children with both AD and asthma compared with asthma only.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".