Capsule Endoscopy Complements Magnetic Resonance Enterography and Endoscopy in Evaluating Small Bowel Crohn’s Disease
Bibliographic record
Abstract
Abstract Aims Wireless capsule endoscopy (WCE) and magnetic resonance enterography (MRE) are increasingly utilized to evaluate the small bowel (SB) in Crohn’s disease (CD). The primary aims were to compare the ability of WCE and MRE to detect SB inflammation in children with newly diagnosed CD, and in the terminal ileum (TI) to compare them to ileo-colonoscopy. Secondary aims were to compare diagnostic accuracy of WCE and MRE and changes in Paris classification after each study. Methods Patients (10 to 17 years of age) requiring ileo-colonoscopy for suspected CD were invited to participate. Only patients with endoscopic/histologic evidence of CD underwent MRE and WCE. SB inflammation and extent were documented and comparative analyses performed. Results Of 38 initially recruited subjects, 20 completed the study. WCE and MRE were similarly sensitive in identifying active TI inflammation (16 [80%] versus 12 [60%]) and any SB inflammation (17 [85%] versus 16 [80%]). However, WCE detected more extensive SB disease than MRE with active inflammation throughout the SB in 15 [75%] versus 1 [5%] patient (P < 0.001). Moreover, WCE was more likely to detect proximal SB disease (jejunum and ileum) compared to MRE (85% versus 50%, P = 0.04). Overall, the Paris classification changed in 65% and 85% of patients following MRE and WCE, respectively. Conclusions WCE is as sensitive as MRE for identifying active TI inflammation, but appears more sensitive in identifying more proximal SB inflammation. In the absence of concern regarding stricturing or extra-luminal disease WCE can be considered for the evaluation of suspected SB CD.
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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".