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Record W3142056325 · doi:10.4021/jem31w

Myelofibrosis and Antiphospholipid Syndrome Presenting With Adrenal Insufficiency Due to Bilateral Adrenal Hemorrhage: A Case Series

2011· article· en· W3142056325 on OpenAlexvenueno aff
Robbins

Bibliographic record

VenueJournal of Endocrinology and Metabolism · 2011
Typearticle
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineAdrenal HemorrhageAdrenal insufficiencySplenectomyAbdominal painAntiphospholipid syndromeNauseaVomitingMyelofibrosisAdrenal disorderWarfarinSurgeryThrombosisInternal medicineInsulinAtrial fibrillationGlucose homeostasisSpleen

Abstract

fetched live from OpenAlex

Adrenal hemorrhage is rare but appears to occur more frequently in patients with underlying hematological conditions. We report two recent patients with underlying hematological disorders who presented with adrenal insufficiency due to bilateral adrenal hemorrhage. The first case is a 59-year-old woman known to have myelofibrosis. This patient was being treated with warfarin for left leg deep vein thrombosis which developed after splenectomy. She was admitted to hospital with vomiting and abdominal pain. The second case is an 84-year-old male patient with antiphospholipid syndrome and diabetes mellitus who was treated with warfarin and insulin. He was admitted with sudden onset of nausea, hypotension and recurrent hypoglycemia despite cessation of insulin therapy. In both cases, bilateral enlarged adrenal glands consistent with hemorrhage were detected resulting in adrenal insufficiency. It is important that Hematologists and Endocrinologists alike should recognise symptoms of adrenal insufficiency in patients with hematological disorders, particularly those being treated with antiplatelet medications or anticoagulants. J Endocrinol Metab. 2011;1(3):142-145 doi: https://doi.org/10.4021/jem31w

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.019
GPT teacher head0.248
Teacher spread0.229 · 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
Published2011
Admission routes1
Has abstractyes

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