A140 ECTOPIC SPLEEN PRESENTING AS A GASTRIC SUBMUCOSAL LESION
Bibliographic record
Abstract
Abstract Background Accessory spleen is ectopic splenic tissue which can be either congenital or acquired. It is usually an asymptomatic incidental finding. In the context of known malignancy, accessory spleen can be mistaken for metastasis. Purpose Here, we share a case of ectopic spleen presenting as a gastric subepithelial lesion post splenectomy. Rare cases have been reported in the literature. Method Case Report and Literature Review Result(s) Case: A middle age male with history of splenic rupture secondary to a motor vehicle accident and metastatic renal cancer was found to have a gastric subepithelial lesion on endoscopy. Endoscopic ultrasound (EUS) revealed a subepithelial mass coming off the submucosa or muscularis mucosa of the gastric wall with intact muscularis propria. EUS-guided core biopsy was performed and demonstrated splenic tissue Conclusion(s) Splenic tissue should be considered in the differential diagnosis when assessing gastric subepithelial tumors even in the context of previous trauma to the spleen. In addition, EUS-guided core biopsy may be required to rule out metastatic disease. Please acknowledge all funding agencies by checking the applicable boxes below None Disclosure of Interest None Declared ESOPHAGEAL, GASTRIC & DUODENAL DISORDERS
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".