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Record W2158332141 · doi:10.1002/pbc.20479

Cutaneous Langerhans cell histiocytosis in children under one year

2005· article· en· W2158332141 on OpenAlexaff
Loretta M. S. Lau, Bernice R. Krafchik, Monika Trebo, Sheila Weitzman

Bibliographic record

VenuePediatric Blood & Cancer · 2005
Typearticle
Languageen
FieldMedicine
TopicHistiocytic Disorders and Treatments
Canadian institutionsUniversity of TorontoHospital for Sick Children
FundersHistiocytosis Association
KeywordsMedicineLangerhans cell histiocytosisHistiocytosisIncidence (geometry)DiseaseDermatologyRetrospective cohort studyPediatricsSurgeryPathology

Abstract

fetched live from OpenAlex

BACKGROUND: To evaluate the clinical course and outcome of infants with Langerhans cell histiocytosis (LCH) involving skin and to estimate the incidence of progression to multi-system (M-S) disease in those with isolated skin involvement. METHODS: A retrospective review was conducted on 22 LCH patients who were younger than 12 months at the onset of their skin eruption. RESULTS: Twelve patients had isolated skin involvement at diagnosis and 10 were evaluable for progression. Four of the 10 (40%) evaluable patients progressed to multi-system (M-S) disease. Of the 10 patients with M-S disease at diagnosis, 5 had a history of a preceding skin eruption 2 to 13 months prior to diagnosis. Eleven of the 14 (79%) patients with M-S disease had risk organ involvement. The mortality rate of M-S disease was 50%. CONCLUSIONS: It is important for primary caregivers to recognize that isolated cutaneous LCH in infants is not always a benign disorder. The diagnosis of self-healing cutaneous LCH should only be made in retrospect. Careful, albeit non-invasive, follow-up is recommended to monitor for disease progression and development of long-term complications.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.237
Teacher spread0.229 · 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 source (direct Gemma or distilled Codex), 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

Citations98
Published2005
Admission routes1
Has abstractyes

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