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Record W2121065385 · doi:10.2340/00015555-1941

Factors That Predict Remission of Infant Atopic Dermatitis: A Systematic Review

2015· review· en· W2121065385 on OpenAlexaboutno aff
Laura von Kobyletzki, Åke Svensson, Christian Apfelbacher, Jochen Schmitt

Bibliographic record

VenueActa Dermato Venereologica · 2015
Typereview
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsAtopic dermatitisMedicineFilaggrinConfidence intervalOdds ratioPediatricsAtopySensitizationAllergyInternal medicineDermatologyImmunology

Abstract

fetched live from OpenAlex

The individual prognosis of infants with atopic dermatitis (AD) is important for parents, healthcare professionals, and society. The aim of this study was to investigate predictors for remission of infant AD until school age. A systematic review was carried out of clinical and epidemiological studies investigating the effect of filaggrin gene (FLG) loss-of-function mutations, sex, exposure to pets, topical anti-inflammatory treatment, disease severity, and atopic sensitization during infancy on complete remission of infant-onset AD until 6-7 years of age. Systematic electronic searches until September 2013, data abstraction, and study quality assessment (Newcastle-Ottawa Scale) were performed. From 3,316 abstracts identified, 2 studies of good study quality were included. Parental allergies and sex did not significantly affect remission. For non-remission of AD, the included articles reported an association with any atopic sensitization at 2 years old (adjusted odds ratio [aOR] 2.76; 95% confidence interval (CI) 1.29-5.91), frequent scratching with early AD (aOR 5.86; 95% CI 3.04-11.29), objective severity score at 2 years old (aOR 1.10; 95% CI 1.07-1.14), and exposure to pets (cat OR 2.33; 95% CI 0.85-6.38). It is largely unknown which factors predict remission of infant AD. This is a highly relevant research gap that hinders patient information on the prognosis of infant-onset AD.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.350
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.087
GPT teacher head0.344
Teacher spread0.257 · 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 designSystematic review
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

Citations22
Published2015
Admission routes1
Has abstractyes

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