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Onset of Pyoderma Gangrenosum in Patients on Biologic Therapies: A Systematic Review

2022· article· en· W4220851488 on OpenAlexaff

Bibliographic record

VenueAdvances in Skin & Wound Care · 2022
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders
Canadian institutionsWomen's College Hospital
Fundersnot available
KeywordsPyoderma gangrenosumRituximabAdverse effectMEDLINEBiologic Agents

Abstract

fetched live from OpenAlex

OBJECTIVE: To summarize clinical outcomes of paradoxical pyoderma gangrenosum (PG) onset in patients on biologic therapy. METHODS: The authors conducted MEDLINE and EMBASE searches using PRISMA guidelines to include 57 patients (23 reports). RESULTS: Of the included patients, 71.9% (n = 41/57) noted PG onset after initiating rituximab, 21.1% (n = 12/57) noted tumor necrosis factor α (TNF-α) inhibitors, 5.3% (n = 3/57) reported interleukin 17A inhibitors, and 1.8% (n = 1/57) reported cytotoxic T-lymphocyte-associated protein 4 antibodies. The majority of patients (94.3%) discontinued biologic use. The most common medications used to resolve rituximab-associated PG were intravenous immunoglobulins, oral corticosteroids, and antibiotics, with an average resolution time of 3.3 months. Complete resolution of PG in TNF-α-associated cases occurred within an average of 2.2 months after switching to another TNF-α inhibitor (n = 1), an interleukin 12/23 inhibitor (n = 2), or treatment with systemic corticosteroids and cyclosporine (n = 3), systemic corticosteroids alone (n = 1), or cyclosporine alone (n = 1). CONCLUSIONS: Further investigations are warranted to determine whether PG onset is associated with underlying comorbidities, the use of biologic agents, or a synergistic effect. Nevertheless, PG may develop in patients on rituximab or TNF-α inhibitors, suggesting the need to monitor and treat such adverse effects.

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.011
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.005
Bibliometrics0.0110.013
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.261
Teacher spread0.256 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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