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Record W4309659994 · doi:10.1136/bcr-2022-251451

Plurihormonal pituitary adenoma cosecreting ACTH and GH: a rare cause of Cushing’s disease

2022· article· en· W4309659994 on OpenAlexaff
Jumana Amir, Marie Christine Guiot, Natasha Garfield

Bibliographic record

VenueBMJ Case Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineCushing's diseasePituitary adenomaInternal medicinePituitary disorderAcromegalyEndocrinologyAdenomaProlactinRare diseasePolycystic ovarian diseaseCushing DiseaseCushing syndromeTranssphenoidal surgerySomatotropic cellGrowth hormoneDiseaseHormonePolycystic ovaryDiabetes mellitusInsulin resistance

Abstract

fetched live from OpenAlex

Plurihormonal pituitary adenomas are rare forms of pituitary adenomas that express more than one hormone. The most common association is with growth hormone (GH) and prolactin. Cosecretion of GH and adrenocorticotrophic hormone (ACTH) is rare with only 25 reported cases in literature. Most presented with features of GH excess, and only four presented with Cushing's disease. We report a case of a woman in her 30s with recurrent plurihormonal pituitary macroadenoma cosecreting GH and ACTH, diagnosed during workup for polycystic ovarian syndrome, and both times presenting uniquely with Cushing's disease. Biochemical testing showed GH excess and hypercortisolism. She underwent transsphenoidal surgery twice and immunohistochemistry showed positive staining for GH and ACTH on both occasions. We aim to raise more awareness of this rare type of pituitary adenoma, shed light on the importance of recognising rare presentations and highlight the necessity of rigorous follow-up given morbidity and potentially higher mortality risk.

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)0.002
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.022
GPT teacher head0.290
Teacher spread0.268 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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