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Record W583416810 · doi:10.3748/wjg.v21.i19.6082

Severe Henoch-Schönlein purpura with infliximab for ulcerative colitis

2015· article· en· W583416810 on OpenAlexaff
Yang Song, Yanhong Shi, Chong He, Changqin Liu, Junshan Wang, Yujie Zhao, Yanmin Guo, Ruijin Wu, Xiaoyue Feng, Zhanju Liu

Bibliographic record

VenueWorld Journal of Gastroenterology · 2015
Typearticle
Languageen
FieldMedicine
TopicVasculitis and related conditions
Canadian institutionsCAE (Canada)
FundersNational Natural Science Foundation of China
KeywordsMedicineInfliximabUlcerative colitisDermatologyInflammatory bowel diseaseVasculitisPurpura (gastropod)Palpable purpuraColectomyHenoch-Schonlein purpuraAdverse effectGastroenterologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Infliximab (IFX) is an anti-tumor necrosis factor chimeric antibody that is effective for treatment of autoimmune disorders such as Crohn's disease and ulcerative colitis (UC). IFX is well tolerated with a low incidence of adverse effects such as infections, skin reactions, autoimmunity, and malignancy. Dermatological manifestations can appear as infusion reaction, vasculitis, cutaneous infections, psoriasis, eczema, and skin cancer. Here, we present an unusual case of extensive and sporadic subcutaneous ecchymosis in a 69-year-old woman with severe UC, partial colectomy and cecostomy, following her initial dose of IFX. The reaction occurred during infliximab infusion, and withdrawal of IFX led to gradual alleviation of her symptoms. We concluded that Henoch-Schönlein purpura, a kind of leukocytoclastic vasculitis, might have contributed to the development of the bruising. Although the precise mechanisms of the vasculitis are still controversial, such a case highlights the importance of subcutaneous adverse effects in the management of UC with IFX.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.017
GPT teacher head0.261
Teacher spread0.244 · 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 designCase report
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

Citations21
Published2015
Admission routes1
Has abstractyes

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