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Record W4410027819 · doi:10.1186/s13223-025-00963-6

Dermatologic presentations of hyper IgE syndrome in pediatric patients

2025· review· en· W4410027819 on OpenAlexvenueno aff
Mohammad Mahjoubi, Ronak Rashedi, Noosha Samieefar, Fahimeh Abdollahimajd, Nima Rezaei

Bibliographic record

VenueAllergy Asthma and Clinical Immunology · 2025
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmunodeficiency and Autoimmune Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImmunoglobulin EDermatologyRashPsychological interventionDiseaseImmunologyIntensive care medicinePediatricsAntibodyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Hyper-IgE Syndrome, also known as Job's syndrome, is a rare primary immunodeficiency disorder characterized by recurrent infections and elevated levels of immunoglobulin E. While respiratory and systemic manifestations have been more emphasized, dermatological manifestations in Hyper-IgE Syndrome also play a significant role in disease presentation. METHODS: This narrative review explores the dermatologic presentations of Hyper-IgE Syndrome in pediatric populations, including descriptions, associated symptoms/findings, and available treatment options. RESULTS AND CONCLUSION: Neonatal rash, mucocutaneous candidiasis, noma neonatorum, psoriasis, cold staphylococcal abscesses, and candida onychomycosis are among the dermatological manifestations of Hyper-IgE Syndrome. Each manifestation has unique characteristics and treatment considerations, necessitating accurate recognition and diagnosis for effective management. Optimal treatment strategies involve a combination of supportive care, topical/systemic therapies, antifungal medications, and surgical interventions when necessary. Further research is needed to enhance our understanding of these manifestations and evaluate treatment modalities for individuals affected by Hyper-IgE Syndrome.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.984
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0020.001
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 head0.021
GPT teacher head0.324
Teacher spread0.302 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations2
Published2025
Admission routes1
Has abstractyes

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