Pituitary Macroadenoma With Partial Transient Hypopituitarism
Bibliographic record
Abstract
Pituitary tumors are lesions of the central nervous system that are usually benign and most often develop sporadically. Non-functioning pituitary adenomas range from being clinically asymptomatic to causing significant hypothalamic/pituitary dysfunction, including hypopituitarism, and visual field loss due to their large size. Pituitary macroadenomas (size over 10 mm) may cause elevated prolactin levels (“pseudoprolactinoma”) as a result of the lost dopaminergic inhibition on pituitary lactotrophs. Spontaneous recovery of the pituitary function in patients with hypopituitarism after surgical removal of a macroadenoma is rare. We present a clinical case of a 40-year-old man, referred for diagnostic clarification in a specialized endocrine clinic, due to easy fatigue and swelling of the lower limbs and outpatient-acquired data on secondary hypothyroidism. From the conducted complex hormonal evaluation, the patient presented with partial hypopituitarism (secondary hypogonadism and hypothyroidism) and hyperprolactinemia. The performed magnetic resonance imaging (MRI) of the brain revealed a pituitary macroadenoma, measuring 24 × 23 × 22 mm, without involvement of the optic nerves. After the execution of transsphenoidal adenomectomy, the patient underwent recovery of the pituitary function and did not require permanent hormone replacement therapy. The described clinical case provides evidence of the unique high reparative and regenerative potential of the pituitary gland that should be kept in mind during the follow-up period of patients with postoperative hypopituitarism.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".