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Record W4239287570 · doi:10.1177/120347540400800607

Kikuchi—Fujimoto's Necrotizing Lymphadenitis in Association with Discoid Lupus Erthematosus: A Case Report

2004· article· en· W4239287570 on OpenAlexaff
Shane Silver, Hwanhee Hong, Patricia T. Ting, Nigel J. Ball

Bibliographic record

VenueJournal of Cutaneous Medicine and Surgery · 2004
Typearticle
Languageen
FieldMedicine
TopicLymphadenopathy Diagnosis and Analysis
Canadian institutionsUniversity of CalgaryUniversity of ManitobaUniversity of British Columbia
Fundersnot available
KeywordsMedicineDiscoid lupus erythematosusPathologyScalpDermisFollicular hyperplasiaHistopathologyLymphDermatologyReticular DermisBiopsyLupus erythematosusImmunology

Abstract

fetched live from OpenAlex

Background: Kikuchi–Fujimoto's necrotizing lymphadenitis (KFNL) is a rare, benign, self-limited condition characterized by constitutional symptoms, lymphadenopathy, and skin lesions. Objective: We report a case of KFNL in a 43-year-old East Indian woman with a ten-year history of discoid lupus erythematosus (DLE) of the scalp and a three-month history of a erythematous plaque on the left nasal bridge, cervical lymphadenopathy, and fever. Skin biopsy samples were taken from the face and lymph node. Results: Histopathological examination of the skin revealed a mixed infiltrate of inflammatory cells, nuclear dust, and histiocytes phagocytosing nuclear debris in the reticular dermis. The lymph node showed interfollicular liquefactive necrosis, immunoblasts, and a similar cellular infiltrate as the skin. The non-necrotic areas demonstrated follicular hyperplasia. These pathological changes are associated with a diagnosis of KFNL. Conclusions: KFNL is reported in association with systemic lupus erythematosus, but only two other cases of systemic KFNL in association with DLE exist in the literature. This case is unique in that the patient presented with cutaneous and systemic KFNL in the setting of longstanding DLE.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.344
Threshold uncertainty score0.562

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.257
Teacher spread0.243 · 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.

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

Citations0
Published2004
Admission routes1
Has abstractyes

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