Unsuspected Small-Bowel Crohn’s Disease in Elderly Patients Diagnosed by Video Capsule Endoscopy
Bibliographic record
Abstract
Background. Video capsule endoscopy (VCE) is increasingly performed among the elderly for obscure bleeding. Our aim was to report on the utility of VCE to uncover unsuspected Crohn’s disease (CD) in elderly patients. Methods. Retrospective review of VCE performed in elderly patients (≥70 y) at a tertiary hospital (2010–2015). All underwent prior negative bidirectional endoscopies. CD diagnosis was based on consistent endoscopic findings, exclusion of other causes, and a Lewis endoscopic score (LS) > 790 (moderate-to-severe inflammation). Those with lower LS (350–790) required histological confirmation. Known IBD cases were excluded. Results. 197 VCE were performed (mean age 78; range 70–93). Main indications were iron deficiency anemia (IDA), occult GI bleeding (OGIB), chronic abdominal pain, or diarrhea. Eight (4.1%) were diagnosed as CD based on the aforementioned criteria. Fecal calprotectin (FCP) was elevated in 7/8 (mean 580 μg/g). Mean LS was 1824. Small-bowel CD detected by VCE led to a change in management in 4/8. One patient had capsule retention secondary to NSAID induced stricture, requiring surgical retrieval. Conclusions. VCE can be safely performed in the elderly. A proportion of cases may have unsuspected small-bowel CD despite negative endoscopies. FCP was the best screening test. Diagnosis frequently changed management.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".