New Opportunities of Dupilumab in Achieving Disease Control in Preschool Age Patients with Atopic Dermatitis: Clinical Case
Bibliographic record
Abstract
Background. Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases in children. It manifests during the first year of life in majority of cases. Early AD manifestation is a risk factor for the development of other atopic spectrum diseases in the future. Nowadays, the ability of the dupilumab, as a genetically engineered biologic drug (GEBD), to modify the disease course, to reduce the frequency of AD persistence and the possibility of multimorbid atopic phenotype development is widely discussed. Thus, dupilumab management in young children with early onset and severe course arouses specific interest. Clinical case description. This article demonstrates the experience of effective administration of GEBD dupilumab in 4-year old patient with severe AD and comorbid food allergies. Continuous therapy for 12 weeks allowed to recover disease’s skin manifestations. No adverse events were reported. Conclusion. Long-term continuous dupilumab administration in children aged from 6 months to 5 years has proven its efficacy and acceptable safety profile. The potential disease-modifying effect of dupilumab is especially significant for young and preschool children due to the high risk atopic multimorbidity developing during this period.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| 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".