Small Bowel Gastrointestinal Stromal Tumor as a Gateway for <i>Streptococcus anginosus</i> Causing Multiple Liver Abscesses
Bibliographic record
Abstract
Gastrointestinal stromal tumors (GISTs) are the most common type of mesenchymal neoplasm of the gastrointestinal tract but consist of only 1% of all primary gastrointestinal neoplasms. Differentiated from other spindle cell tumors, GISTs are uniquely positive for CD117 expression which allows for molecular targeting therapy with imatinib mesylate (Gleevec). Clinical presentations are variable, ranging from asymptomatic to vague symptoms of abdominal pain, early satiety, abdominal distention or gastrointestinal bleeding. Very rarely, patients can present with tumor-bowel fistula and intra-abdominal abscesses. In this article, we discuss a rare presentation of a middle-aged male with multiple liver abscesses found to have a primary small bowel GIST. This patient received prompt intravenous antibiotics; however, hepatic abscesses can be easily misinterpreted as cystic hepatic metastases which can delay appropriate therapy. Streptococcus anginosus was found to be responsible for the formation of the liver abscesses visualized on computed tomography (CT) scan. Similar to Streptococcus bovis , knowledge in the literature is arising about the association between S. anginosus and gastrointestinal malignancies. This case highlights the importance of identifying concomitant primary GISTs with intra-hepatic abscesses, as these lesions can be easily misconstrued as liver metastases and consequently mismanaged. We herein emphasize that hepatic abscesses are a potential sequela of GISTs and should thus prompt further investigation for potential malignancies, if warranted, so that there is no delay in treatment of these gastrointestinal tumors. World J Oncol. 2020;11(3):116-121 doi: https://doi.org/10.14740/wjon1270
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".