Atopic Dermatitis as a Risk Factor for Herpes Zoster Infection Independent of Treatment: A Nationwide Population-Based Cohort Study
Bibliographic record
Abstract
Background: In the wake of the emerging development of biologics in atopic dermatitis (AD), herpes zoster (HZ) infection has been reported as a treatment-related adverse event. Objectives: This study aims at investigating the association between AD and HZ, and the risk factors within. Methods: 28,677 participants with AD from the Taiwan National Health Insurance Research Database 2000–2015 were enrolled. Risk of HZ infection was compared in the study cohort (with AD) and the control cohort (without AD). Further analyses were conducted in gender-, age-, and treatment strategy-stratified subgroups. Results: Significantly higher adjusted hazard ratios (aHRs) of HZ infection were revealed in AD patients (aHR = 2.303, P < 0.001), and remained this trend in gender- and age-stratified models. All AD groups, irrespective of the treatment type, had higher aHRs (AD without systemic treatment: aHR = 2.356, P < 0.001; AD with systemic treatment: aHR = 2.182, P < 0.001) compared with those without AD. However, no differences in HZ risk were shown between each treatment type. Conclusions: Risk of HZ infection in AD is higher irrespective of treatment type. Considering that AD per se increases susceptibility to HZ infection, the administration of biologics requires careful considerations.
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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 | 0.000 |
| 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".