Case report of a serous endometrial carcinoma metastasizing to the brain
Bibliographic record
Abstract
Background: Endometrial carcinoma (EC) is a rare cause of central nervous system metastases, with only 115 cases reported in the literature. There have only been 4 cases reported in the literature for the serous carcinoma subtype. This case study describes a new case of serous carcinoma metastasizing to the brain and demonstrates some of the potential characteristics of this subset. Case: A 77 year old female presented to the emergency department with a 2 week history of progressive left sided weakness and speech difficulties, and a known history of EC diagnosed approximately 3 years earlier. Imaging showed a right temporoparietal tumour. She underwent debulking of this tumour and was found to have a metastasis from her previously known serous carcinoma. Results: In comparing the serous subtype to the 115 known cases, many characteristics show similar patterns to EC as a whole; there could be a predominance to infratentorial lesions with the serous subtype, as 2/4 known metastases were cerebellar compared to only 25% of all endometrial carcinomas. Conclusions: There are possibly different characteristics of metastasizing of various EC subtypes. Before any conclusions can be drawn about the characteristics of any subtype, more data needs to be available for accurate interpretation.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| 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".