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Record W4410517619 · doi:10.15690/vsp.v24i2.2867

Results of Emollient Therapy in a Child with Severe Atopic Dermatitis Treated with Genetically Engineered Biological Drug: Clinical Case

2025· article· en· W4410517619 on OpenAlexaff
Eduard Т. Ambarchian, Anastasia D. Kuzminova, Vladislav V. Ivanchikov

Bibliographic record

VenueВопросы современной педиатрии · 2025
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsChildren’s Health Research Institute
Fundersnot available
KeywordsAtopic dermatitisMedicineGenetically engineeredDermatologyDrugImmunologyPharmacologyBiologyGenetics

Abstract

fetched live from OpenAlex

Background. Baseline therapy for children with severe atopic dermatitis (AD) is crucial for achieving required clinical effect, regardless the systemic treatment variants. Clinical case description. The boy, 9 years old, had complaints on widespread rashes on the body and limbs accompanied by dry skin and itching and was diagnosed with AD. Topical glucocorticoids, course of local medium wave narrowband phototherapy of 311 nm, topical calcineurin inhibitors were used in the treatment but with weak positive dynamics. Genetically engineered biological therapy was initiated due to frequent relapses and lack of disease control. No persistent improvement was noted after 10 weeks of therapy. The child was hospitalized, cyclic biological therapy was continued, topical therapy was corrected, and skin care was modified, the emollient-plus drug was prescribed. Clinically significant decrease in EASI and CDLQI indices, as well as a decrease in SCORAD and NRS scores was noted 4 weeks after treatment correction and emollients implementation. Conclusion. Emollients are mandatory in the management of children with AD (despite the disease severity) according to clinical guidelines. This clinical case confirms the feasibility of therapy with emollient-plus agents, as it was possible to achieve the correction of epidermal barrier dysfunction and significant clinical effect.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.824

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.288
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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