Unusual Features of Clear Cell Adenocarcinoma of the Female Urethra: A Case Report and Literature Review
Bibliographic record
Abstract
BACKGROUND: There has been scarce information about clear cell adenocarcinoma of the urethra (CCAU), an extremely rare type of cancer. A few case reports show that CCAU tends to have similar clinical manifestation to the other urethral carcinomas, urethrocystoscopy can easily identify tumoral lesions in the urethra, and bloody drainage from the urethral meatus is often seen during physical exams. METHODS: A 52-year-old woman presented with dysuria for 6 months. Urethrocystoscopy did not reveal abnormality, and there was no bloody vaginal drainage or bloody drainage from the urethral meatus during physical exams. Ultrasonography demonstrated a solid mass with well-defined margins located between the anterior vaginal wall and the posterior urethral wall. Computed tomography showed the mass with smooth margins at the level of vaginal fornix, and magnetic resonance imaging showed the same location of the tumor as ultrasonography. RESULTS: Surgical removal of the tumor was successfully performed and histological and immunohistochemical analysis confirmed the final diagnosis of CCAU. CONCLUSION: Abnormality in urethrocystoscopy and bloody drainage during the physical exam were not found in this case, which is in contrast to the findings reported in literature. These unusual features add new knowledge about CCAU that deserves dissemination for improved CCAU diagnosis and management.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 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".