Leptomeningeal Carcinomatosis Secondary to Gastroesophageal Adenocarcinoma: A Case Report and Review of the Literature
Bibliographic record
Abstract
BACKGROUND: Leptomeningeal carcinomatosis (LC) is a rare metastatic complication of solid tumours. It has been mainly described in association with breast cancer, lung cancer and melanoma. CASE PRESENTATION: A patient presenting with progressive solid food dysphagia with documented adenocarcinoma of the lower esophagus and gastroesophageal junction is reported. One month after the initial diagnosis, the patient developed gradual onset of increasing headache and progressive decrease in the level of consciousness. Computed tomography of the head showed evidence of meningeal enhancement, and cerebrospinal fluid examination showed the presence of adenocarcinoma cells, making the diagnosis of LC. The patient died one month after LC was diagnosed. DISCUSSION: LC is a poor prognostic sign in solid organ malignancies. It usually presents with headache, altered level of consciousness and focal neurological deficits. Diagnosis is established by finding malignant cells in the cerebrospinal fluid and supported by marked meningeal enhancement on computed tomography of the brain. A review of the English literature found only three reported cases of LC secondary to esophageal malignancy. CONCLUSION: A case of LC complicating esophageal and gastroesophageal junction malignancy is described. A high index of suspicion and early diagnosis may influence the poor outcome of these patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".