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Record W3115024787 · doi:10.15690/vsp.v19i6.2156

Wells Syndrome in Children: Case Study and Differential Diagnostics

2020· article· en· W3115024787 on OpenAlexaff
Nikolay N. Murashkin, Eduard Т. Ambarchian, Roman V. Epishev, Alexander I. Materikin, Leonid A. Opryatin, Roman A. Ivanov, Daria S. Kukoleva

Bibliographic record

VenueВопросы современной педиатрии · 2020
Typearticle
Languageen
FieldMedicine
TopicEosinophilic Disorders and Syndromes
Canadian institutionsChildren’s Health Research Institute
Fundersnot available
KeywordsMedicineDifferential diagnosisExacerbationEosinophiliaDermatologyDiseaseAbdominal painPathologyCellulitisPediatricsSurgeryImmunology

Abstract

fetched live from OpenAlex

Background . Wells syndrome (eosinophilic cellulitis) is recurrent granulomatous dermatitis with peripheral blood eosinophilia. This is extremely rare pathology, therefore, there are no reliable epidemiological data on its prevalence. Only about 200 cases were recorded worldwide and 30 of them among children according to the meta-analysis (2012). The disease is mostly sporadic, there are rare family cases, according to the results of little number of scientific publications. Clinical Case Description . The clinical case of Wells syndrome in female 4 years old patient is presented. Clinical findings included symmetrical skin lesions, nodes and large irregular edematous plaques of red-purple color with clear fluid vesicles on its surface. The disease had wavy course: rashes have recovered spontaneously over 7–10 days, new elements appeared alongside with feeling unwell, fever up to 37,8°C and abdominal pain. Similar clinical findings of rashes were observed in paternal relatives of the child. Conclusion . Differential diagnostics of Wells syndrome should be carried out with skin granulomatous diseases and hypereosinophilic syndrome that may be characterized by similar clinical findings. Verification of Wells syndrome diagnosis is complicated due to its rareness, low awareness of dermatologists and pediatricians about this pathology, as well as ignoring the need to carry out histological tests during the disease exacerbation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

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 integrity0.0000.000
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 head0.015
GPT teacher head0.252
Teacher spread0.237 · 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 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
Published2020
Admission routes1
Has abstractyes

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