Lactotroph <scp>PitNET</scp>/adenoma associated to granulomatous hypophysitis in a patient with Crohn's disease: A case report
Bibliographic record
Abstract
Granulomatous hypophysitis is a rare and poorly understood condition. Although certain cases are treated as primary pituitary autoimmune disorders, rare cases may be associated with pituitary neuroendocrine tumours (PitNETs) and systemic inflammatory diseases. Here, we report a case of a 47-year-old man that underwent endoscopic trans-sphenoidal excision of a pituitary mass diagnosed as PitNET. On histologic evaluation, the neoplasm showed an admixture of granulomas with extensive inflammatory infiltrate and lactotroph PitNET/adenoma. Careful anamnestic examination revealed a diagnosis of Crohn's disease 20 years prior. Although rarely done, both PitNET and Crohn's disease may be associated with granulomatous hypophysitis, and our patient had both conditions. During the 6-year follow-up, PitNETs and hypophysitis did not recur, while Crohn's disease was only partially controlled by medical therapy. To our knowledge, this is the first description of association of granulomatous hypophysitis, PitNET and Crohn's disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".