Hydropic leiomyoma presenting as a rare condition of pseudo-Meigs syndrome: literature review and a case of a pseudo-Meigs syndrome mimicking ovarian carcinoma with elevated CA125
Bibliographic record
Abstract
The clinical scenario of a female patient with a pelvic mass, elevated CA125 tumour marker, pleural effusion and ascites is often associated with malignancy. However, not all cases are malignant. Non-malignant diseases, such as Meigs syndrome and pseudo-Meigs syndrome, must be part of your differential. We present a 56-year-old woman with dyspnoea secondary to a right pleural effusion. After further investigations, a serum cancer antigen-125 was found to be elevated at 437.3 U/mL. CT of her abdomen and pelvis showed a large heterogeneous mass in the pelvis measuring 13.2×9.7×15.1 cm with mild ascites. She was initially thought to have ovarian carcinoma and underwent total abdominal hysterectomy and bilateral salpingo-oophorectomy with omental biopsy. Pathology from the surgical specimen revealed a hydropic leiomyoma and after removal of pelvic mass her pleural effusion and ascites completely resolved. She was ultimately diagnosed with the rare pseudo-Meigs syndrome.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".