Prevalence of Atopic Dermatitis and Pattern of Drug Therapy in Malaysian Children
Bibliographic record
Abstract
BACKGROUND: Atopic dermatitis (AD) is a chronic relapsing, noncontagious skin inflammation characterized by dry skin and itch. Mutation in filaggrin gene leads to defective skin barrier, allowing entry of allergen and eliciting immunological response. OBJECTIVES: The aims of this study were to investigate the prevalence of AD in Malaysian children and to understand the pattern of drug therapy. Such information could be useful to establish the relationship between ethnicity and family history of atopy and the development of associated signs and symptoms. METHODS: A cross-sectional survey was conducted among children attending kindergartens and nurseries. Standardized questionnaires were filled out by parents. RESULTS: Overall prevalence of AD was 13.4%. Of 384 participants recruited, the highest prevalence was observed in males, Malays, participants younger than 2 years, and those with atopic background such as asthma, hay fever, and family history of atopic diseases. Calamine and white soft paraffin were the preferred choice of nonprescription drugs, whereas topical hydrocortisone seemed to be the preferred choice of prescription drug in the management of AD. CONCLUSIONS: The overall prevalence is comparable to that reported in the International Study of Asthma and Allergies in Childhood Phase One. There is an association between ethnicity and AD prevalence. Topical corticosteroids and emollients are the mainstay of AD management among Malaysians.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".