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Record W2524163516 · doi:10.14740/jocmr2717w

Generalized Lymphadenopathy as Presenting Feature of Systemic Lupus Erythematosus: Case Report and Review of the Literature

2016· article· en· W2524163516 on OpenAlexvenueno aff
Wais Afzal, T.M. Arab, Tofura Ullah, Katerina Teller, Kaushik Doshi

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typearticle
Languageen
FieldMedicine
TopicLymphadenopathy Diagnosis and Analysis
Canadian institutionsnot available
FundersNational Institute of Arthritis and Musculoskeletal and Skin Diseases
KeywordsMedicineConstitutional symptomsEtiologyGeneralized lymphadenopathyDermatologyDifferential diagnosisMedical historyPhysical examinationMalaiseNauseaPathologySurgeryLymphomaDisease

Abstract

fetched live from OpenAlex

Lymphadenopathy could represent a vast spectrum of etiologies including infectious and non-infectious diseases. Besides proper history taking, physical examination, and laboratory investigations, a tissue diagnosis is often necessary to unmask the cause of generalized lymphadenopathy. Here we present a 23-year-old woman who was admitted for diffuse generalized lymphadenopathy, fatigue, malaise, weight loss, nausea, and bilateral lower extremity edema. She reported a history of seizures as well as stroke 2 years prior with no other medical conditions present. Although malignant and infectious etiologies were initially the primary targets for workup, her history of seizures and stroke remained a dilemma. Extensive workup for malignant and infectious diseases was unrevealing; however, rheumatologic workup was eventually positive for systemic lupus erythematosus (SLE). This case illustrates that extensive generalized diffuse lymphadenopathy may be a presenting feature of SLE and should be considered in the differential diagnosis of patients presenting with diffuse lymphadenopathy and constitutional symptoms.

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: none
Teacher disagreement score0.004
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.087
GPT teacher head0.471
Teacher spread0.384 · 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

Citations26
Published2016
Admission routes1
Has abstractyes

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