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Record W4409154926 · doi:10.1097/asw.0000000000000307

Pemphigus Vulgaris: Clinical Aspects and Treatments

2025· review· en· W4409154926 on OpenAlexaff
Ryan S Q Geng, R. Gary Sibbald

Bibliographic record

VenueAdvances in Skin & Wound Care · 2025
Typereview
Languageen
FieldMedicine
TopicAutoimmune Bullous Skin Diseases
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPemphigus vulgarisMedicinePemphigusDesmoglein 3DermatologyPresentation (obstetrics)AutoantibodyDiseaseImmunologyPathologySurgeryAntibody

Abstract

fetched live from OpenAlex

ABSTRACT Pemphigus vulgaris (PV) is a rare, but potentially life-threatening (5%-30%) intraepidermal blistering disease with a mean onset age between 40 and 60 years. Disease onset typically begins in the oral mucosa prior to spreading to the skin. Classic PV is characterized by fragile flaccid blisters on normal or erythematous skin that have a tendency to break and form erosions. Diagnosis of PV can be supported by direct immunofluorescence detection of immunoglobulin G and C3 deposits on the surface of keratinocytes and immunoserology studies to detect anti-desmoglein 1/3 autoantibodies. Systemic corticosteroids are the mainstay of PV treatment and are often combined with other immunosuppressive adjuvants to improve remission rates. This review focuses on the clinical presentation, risk factors, and treatment options for PV. GENERAL PURPOSE To review the clinical presentation, diagnostic evaluation, and management approaches for pemphigus vulgaris (PV). TARGET AUDIENCE This continuing education activity is intended for physicians, physician assistants, nurse practitioners, and registered nurses with an interest in skin and wound care. LEARNING OBJECTIVES/OUTCOMES After participating in this educational activity, the learner will: 1. Summarize the clinical manifestations associated with PV. 2. Evaluate risk factors associated with PV. 3. Explain evidence-based diagnostic and treatment options for PV.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.023
GPT teacher head0.426
Teacher spread0.403 · 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 designOther design
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

Citations1
Published2025
Admission routes1
Has abstractyes

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