Renal Cell Carcinoma and Intradural Spinal Metastasis With Cauda Equina Infiltration: Case Report
Bibliographic record
Abstract
In Brief Study Design. A case report and clinical discussion. Objective. To describe the diagnosis, pathophysiology, and treatment of a papillary renal cell carcinoma that developed an intradural spinal mass with cauda equina infiltration. Summary of Background Data. Cancers that metastasize intradurally to the spinal canal are uncommon, accounting for the 6% of all spinal metastases. Those from renal cell carcinoma are especially unusual. Only 3 reports that describe the spread of metastatic renal cell carcinoma to the cauda equina have been published to our knowledge. Methods. A female patient had undergone nephrectomy for the treatment of the papillary renal cell carcinoma 2 years before, and only 1 localization (at the genital tract) was previously diagnosed. The patient presented with lower back pain irradiated to both legs, vesical incontinence, and severe paraparesis. Results. Preoperative magnetic resonance images of the lumbar spine showed an intradural spinal mass from L3–L5 with infiltration of the cauda equina; the lesion measured 62 mm craniocaudally and 16 mm anteroposteriorly, and thus occupied the majority of the intrathecal space at that level. The magnetic resonance images, surgical treatment, and related pathophysiology are reviewed. Conclusions. The majority of cauda equina tumors are primary tumors, and metastases are very rare. To our knowledge, this is the fourth case described of metastasis of renal cell carcinoma at the cauda equina and the first of papillary type. The authors present a case of a patient with a papillary renal cell carcinoma who developed an intradural spinal mass with cauda equina infiltration. To our knowledge, this is the fourth case described of metastasis of renal cell carcinoma at the cauda equina and the first of papillary type. The clinical characteristics of the disease are discussed.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".