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Record W2604225623 · doi:10.3899/jrheum.161313

Refractory Syndrome of Inappropriate Secretion of Antidiuretic Hormone in Systemic Lupus Erythematosus–associated Hypophysitis

2017· letter· en· W2604225623 on OpenAlexvenueno aff
Nicole Yang, Shamik Bhattacharyya, Michael E. Weinblatt

Bibliographic record

VenueThe Journal of Rheumatology · 2017
Typeletter
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineLeukopeniaHypophysitisAbdominal painmyalgiaRashDermatologyAnti-nuclear antibodyPrednisoneNauseaVomitingInternal medicineSore throatGastroenterologySurgeryImmunologyChemotherapyHormone

Abstract

fetched live from OpenAlex

To the Editor: The syndrome of inappropriate secretion of antidiuretic hormone (SIADH) has been reported in diseases involving the central nervous system (CNS). However, SIADH is rarely reported in patients with systemic lupus erythematosus (SLE)1,2,3,4,5,6. We present a case of a 34-year-old woman with a history of SLE who was diagnosed with SLE in 2009 with polyarthritis, leukopenia, oral ulcers, alopecia, photosensitive rash, diffuse proliferative glomerulonephritis, positive antinuclear antibody, and elevated dsDNA. Two months prior to presentation, she was transitioned from mycophenolate mofetil (MMF) 500 mg bid to azathioprine (AZA) 50 mg daily because of the desire to attempt conception. One month later, she started having daily fevers, sore throat, photosensitive rash, tender posterior cervical lymphadenopathy, abdominal pain, and leukopenia. Because of the leukopenia, she was switched from AZA back to MMF. Her worsening leukopenia and elevated inflammatory markers were suggestive of an SLE flare and she was given a higher dose of prednisone. One month later, she developed abdominal pain, nausea, and vomiting. Her medications included … Address correspondence to Dr. N. Yang, 60 Fenwood Road, Suite 3032X, Boston, Massachusetts 02115, USA. E-mail: nyang2{at}partners.org

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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 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

Citations4
Published2017
Admission routes1
Has abstractyes

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