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Record W3192021686 · doi:10.21203/rs.3.rs-286513/v1

Atypical Presentations of Systemic Lupus Erythematosus by Cerebral Venous Thrombosis and Generalized Lymphadenopathy without Antiphospholipid Antibodies: Case Report

2021· preprint· en· W3192021686 on OpenAlexaff
Xinye Serena Wang, William J. Magnuson, Pearl Behl, Dmitrii Koval

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsTrillium Health CentreUniversity of Calgary
Fundersnot available
KeywordsMedicineVenous thrombosisThrombosisAntibodyAntiphospholipid syndromeSystemic lupusDermatologyImmunologyPathologyInternal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Introduction: Atypical presentations of systemic lupus erythematosus SLE) with features outside of the 2012 Systemic Lupus International Collaborating Clinics (SLICC) criteria can make the diagnosis of SLE elusive. Case Presentation: We describe a case of a healthy 31-year old female who presented with syncope preceded by progressive headache, serositis, and generalized lymphadenopathy. CT-head and MR-venogram confirmed a cerebral venous thrombosis (CVT). Subsequent workup revealed high titers of antinuclear (ANA), anti-double stranded DNA (anti-dsDNA), anti-Smith (anti-Sm) antibodies, as well as low complement levels, lymphopenia and neutropenia. Diagnosis of SLE was confirmed by SLICC classification criteria. Antiphospholipid antibodies (APLA) were negative. While in hospital, she sustained a seizure secondary to the CVT. Conclusion: We discuss considerations for atypical SLE presentations by CVT (without APLA syndrome) and generalized lymphadenopathy, and the nuances of SLE diagnosis using existing classification criteria.

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)0.004
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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0040.002

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 head0.067
GPT teacher head0.403
Teacher spread0.335 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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