Co-Morbidity of Pituitary Adenoma and Frontal Convexity Meningioma: A Case Report and Review of the Literature
Bibliographic record
Abstract
Instruction: The current study reports a woman with pituitary adenoma and frontal convexity meningioma that was detected accidentally. To the best of our knowledge, this case is considered as a rare clinical scenario. Case Presentation: A 37 years old woman suffering from amenorrhea and galactorrhea had her detail investigation showed hyperprolactinemia. The patient was diagnosed with a prolactinoma, and a frontal convexity meningioma was discovered on magnetic resonance imaging (MRI). The prolactinoma controlled with Bromocriptine therapy, while the meningioma monitored through medical observation. After two months of pharmaceutical medication, her symptoms improved with the decrease in serum prolactin. Conclusion: Thanks to sophisticated MRI techniques, meningioma and prolactinoma were incidentally detected. It should be noted that co-morbidity of prolactinoma and meningioma is very rare. The mechanism of the association between these two familiar types of intracranial tumors has not yet been clarified, which indicates the need for further studies to offer possible targeted treatment for patients.
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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 | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".