Splenic metastasis from endometrial adenocarcinoma. A case presentation
Bibliographic record
Abstract
Introduction: Splenic metastasis from endometrial carcinoma is a rare clinical event with only 13 documented cases in the literature reviewed. The evolution of a patient with this metastasis attended in our institution was the reason that motivated us to publish this work. There are other oncological diseases that are accompanied by this clinical picture during their evolution of progression where surgical treatment complemented with chemotherapy treatment is essential. A literature review was carried out in Cuban publications, but no reports on the topic were found. Objective: The aim of this work is to present an endometroid type case endometrium adenocarcinoma which metastasizes to the spleen with clear cell histology. Case presentation: Forty-five-year-old patient with diagnosis of endometrium adenocarcinoma with surgical stage pT3a Nx Mo stage IIIA Grade 2; this quantification was defined before 2009. The patient underwent surgical treatment which was complemented with radiotherapy and then followed for 21 months. In the follow-up consultation, spleen metastasis was diagnosed; so she underwent splenectomy and was treated with chemotherapy. She was treated by the multidisciplinary gynecologic oncology team; the investigations performed were based on immuhistochemistry, imaging, and supportive treatment whenever needed. Conclusions: Splenic metastasis from endometrial cancer is rare; it is the first case reported in Cuba. Immuhistochemical and imaging studies are essential.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".