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Record W2515024541 · doi:10.14740/jocmr2698w

Neuropsychiatric Systemic Lupus Erythematosus: A Diagnostic Conundrum

2016· article· en· W2515024541 on OpenAlexvenueno aff
Vivek Joseph, Rahul Rachwani Anil, Sary Aristy

Bibliographic record

VenueJournal of Clinical Medicine Research · 2016
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDermatologySystemic lupus erythematosusPathologyDisease

Abstract

fetched live from OpenAlex

A 70-year-old man presented with complaints of rapid cognitive decline and new onset leukopenia. The patient had a 17-year history of refractory seizures. Detailed review of symptoms and investigations revealed the patient met American College of Rheumatology (ACR) diagnostic criteria for systemic lupus erythematosus (SLE). The patient had high titer ANA with a strongly positive dsDNA. Immunosuppressive therapy with hydroxychloroquine and mycophenolate mofetil led to significant improvement in cognition and seizures. Neuropsychiatric SLE should be considered a potential differential diagnosis for patients presenting with seizures or cognitive decline. Moreover, neuropsychiatric manifestations especially seizures are an early event in the disease course of SLE. Hence, we believe that early diagnosis of SLE by neuropsychiatric manifestations will not only lead to better control of CNS symptoms but early immunosuppressive therapy could control the progression of the underlying autoimmune disease.

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)0.001
metaresearch head score (Gemma)0.006
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 score0.006
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0020.002

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 head0.155
GPT teacher head0.488
Teacher spread0.333 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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