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Eczema workshops reduce severity of childhood atopic eczema

2009· article· en· W2028668859 on OpenAlexaff
Elizabeth Moore, Allison Williams, Elizabeth Manias, George Varigos, Susan Donath

Bibliographic record

VenueAustralasian Journal of Dermatology · 2009
Typearticle
Languageen
FieldMedicine
TopicDermatology and Skin Diseases
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicineSCORADAtopic dermatitisEczema Area and Severity IndexHand eczemaConfidence intervalIntervention (counseling)DermatologyPediatricsRandomized controlled trialDermatology Life Quality IndexContact dermatitisAllergySurgeryInternal medicine

Abstract

fetched live from OpenAlex

An intervention study was conducted to assess the effectiveness of a nurse-led eczema workshop in reducing the severity of atopic eczema in infants, children and adolescents. Ninety-nine new patients referred to the Dermatology Department of The Royal Children's Hospital in Melbourne, Australia, for the management of atopic eczema were randomized to receive care from an eczema workshop or a dermatologist-led clinic. Patients were followed-up 4 weeks after the intervention. The primary outcome was the severity of eczema as determined by scores obtained using the Scoring of Atopic Dermatitis (SCORAD) index at a 4-week follow-up visit. The secondary outcome was a comparison of treatments used in both clinics. At the 4-week review the mean improvement in SCORAD was significantly greater in those patients attending the eczema workshop than those attending the dermatologist-led clinic (-9.93, 95% confidence interval -14.57 to -5.29, P < 0.001). Significantly more patients from the eczema workshop improved from moderate severity eczema at baseline to mild at review. There was greater adherence to eczema management in the eczema workshop compared with the dermatologist-led clinic. In this study, patients attending the eczema workshop had a greater improvement in eczema severity thanpatients attending a dermatologist-led clinic, supporting collaborative models of service provision.

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 score0.107
Threshold uncertainty score0.756

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.284
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

Citations111
Published2009
Admission routes1
Has abstractyes

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