Cutaneous Deciduosis: A Rare Cutaneous Lesion Mimicking Malignancy
Bibliographic record
Abstract
ABSTRACT: Cutaneous deciduosis is an extremely rare condition that clinically presents as a nodular lesion in the skin as a scar or neoplasm. Histologically, this may pose a diagnostic challenge simulating malignant epithelioid neoplasms including sarcoma. Histologically, a nodular growth pattern of large monomorphic epithelioid cells is observed. The epithelioid cells in deciduosis can appear atypical with considerable nuclear pleomorphism, mimicking a malignancy. These features can be misinterpreted as a primary cutaneous or metastatic malignancy by dermatopathologists who are not familiar with gynecologic pathology. Failure to correctly diagnose this condition may result in unnecessary diagnostic studies for the patient. In this article, we report a case of cutaneous deciduosis in a 35-year-old woman with a cesarean scar. Histological examination revealed nodular proliferation of large epithelioid cells with pale eosinophilic cytoplasm and large nuclei with prominent nucleoli. Compressed atrophic slit-like glands resembling endometrial glands were present in some areas. Histopathological features of decidual cells, along with appropriate immunohistochemical studies, help establish the diagnosis and rule out other neoplastic mimics of deciduosis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".