Leptomeningeal metastasis of poorly differentiated uterine cervical adenosquamous carcinoma following reirradiation to metastatic vertebrae
Bibliographic record
Abstract
RATIONALE: Leptomeningeal metastasis from cervical adenosquamous carcinoma is extremely rare especially after radiotherapy for vertebral metastasis. PATIENT CONCERNS: A 52-year-old woman with International Federation of Gynecology and Obstetrics (FIGO) stage IIB adenosquamous carcinoma of cervix presented with bilateral lower limbs weakening after 2 courses radiotherapy to thoracic vertebral metastases. DIAGNOSES: Initial spine magnetic resonance imaging (MRI) showed no obvious nerve compression, and radiation myelopathy was suspected by the clinician. Progressive multifocal neurological signs developed one month after completion of spine re-irradiation. She was diagnosed with leptomeningeal metastasis by MRI and cerebrospinal fluid (CSF) study. INTERVENTIONS: She received whole brain irradiation with a dose of 30 Gy in 10 fractions. Systemic chemotherapy with cisplatin (50 mg/m) and topotecan (0.75 mg/m) was administered sequentially. OUTCOMES: She died with progressive disease two months after the diagnosis of leptomeningeal metastases. LESSONS: Poorly differentiated advanced-stage cervical adenosquamous carcinoma is an aggressive neoplasm with a worse outcome. Leptomeningeal metastasis should be included in the differential diagnosis for patients with multifocal craniospinal neurological signs. A combination of detailed neurological examinations, MRI and CSF study allowed us to establish a correct diagnosis of leptomeningeal metastasis and initiate treatment in a timely manner.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".