Gastric Schwannoma as an Important and Infrequent Differential Diagnosis of Gastric Mesenchymal Tumours: A Case Report and Review of Literature
Bibliographic record
Abstract
The spectrum for gastrointestinal tract mesenchymal tumours includes leiomyomas, leiomyosarcomas, gastrointestinal stromal tumours (GISTs) and schwannomas. Schwannomas (also known as neuroma, neurilemmomas or neurinomas of Verocay) are well-known slow-growing, benign neoplasms that originate from nerve plexuses within a Schwann cell sheath. They can arise anywhere along the course of the peripheral nerve and are frequently reported around the head and neck, brachial plexus and along the gastrointestinal tract. Usually, these tumours are detected as solitary; however, they can occur at multiple sites around the body. Schwannomatosis (multiple schwannomas) is usually associated with neurofibromatosis type 2; the pathogenesis is triggered by mutations of the neurofibromatosis 2 tumour suppressor gene resulting in a loss of its function. Solitary gastric schwannomas are rare lesions that arise from the nerve plexus of the gastric wall. Frequently they are detected incidentally or may present with nonspecific abdominal pain or bleeding. This paper reports the case of a 79-year-old patient diagnosed with gastric schwannoma after presenting with abdominal pain. Gastric schwannomas should be taken into consideration while making a differential diagnosis of lesions that are gastric mesenchymal tumours, which span a broad spectrum. Gastric schwannomas are typically benign, considerably less common than gastric GISTs, and have an excellent prognosis following excision.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| 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".