Bibliographic record
Abstract
Earlier investigations demonstrate an increased risk for colon cancer in Crohn's disease. For other intestinal neoplasms, such as carcinoids, studies are limited. In Crohn's disease, repeated endoscopic and imaging studies along with intestinal resections may facilitate clinical recognition of neoplastic diseases, including appendiceal neoplasms. To date, however, only sporadic cases of appendiceal carcinoids have been described in Crohn's disease. In the present study, in a single clinician database of 1000 Crohn's disease patients, three of the 441 patients who had undergone intestinal resection had appendiceal carcinoids, all of which were pathologically confirmed. All were observed in female patients and were not suspected before surgical treatment. In one case, even though management was not altered, the tumour had already invaded serosal fat indicating a potential for more advanced disease. In this series, a carcinoid tumour was found in a resection specimen during a later clinical case review and another was a microcarcinoid, implying that these tumours may be overlooked in Crohn's disease. The percentage detected in the entire database (0.3%) exceeds the reported rates of detection of appendiceal carcinoids after removal of the appendix for appendicitis, as well as the rate of detection of appendiceal carcinoids in autopsy studies. This percentage would be higher if only those having an intestinal resection were considered (0.68%). Additional studies are needed to further define this risk of appendiceal carcinoids in Crohn's disease.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".