Atopic Dermatitis in Asians: A Review on Genetics, Clinical Presentation, and Therapeutic Implications
Bibliographic record
Abstract
Atopic dermatitis (AD) is a common, multifactorial, and pruritic inflammatory skin condition with a chronic relapsing course. It typically manifests in infancy or early childhood and is often associated with other atopic conditions, such as asthma and allergic rhinoconjunctivitis. As the most prevalent chronic inflammatory skin disease worldwide, AD affects individuals across a wide range of racial and ethnic backgrounds. Recent studies suggest that Central Asia has the highest pediatric prevalence of AD in 2021, with a rate of 10.5%, surpassing the 5.4% prevalence observed in high‑income North America. According to the 2021 Census, individuals of Asian descent constitute the third-largest population group in Canada, following those of European and North American descent, with nearly half originating from East or Southeast Asia. Furthermore, Asians represent Canada’s fastest-growing demographic. This review highlights the genetic factors, clinical presentations, and therapeutic considerations for AD in Asian populations, aiming to improve understanding and inform tailored treatment approaches.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".