P410 Which patients with established Crohn’s disease benefit most from the use of the Patency capsule test prior to small bowel capsule endoscopy?
Bibliographic record
Abstract
Abstract Background An important factor that limits a wider utilization of small bowel capsule endoscopy (SBCE) in Crohn’s Disease (CD) is the potential risk of retention. The Patency® capsule (PC) lowers the risk of SBCE retention by assessing pre-procedure intestinal patency. Our aims were to evaluate the use of PC in patients with established CD in routine clinical practice and to identify predictive factors of intestinal patency in CD patients. Methods We included all patients with CD followed in the Inflammatory Bowel Disease Unit of the Complejo Hospitalario de Navarra in which a SBCE was performed from 01/01/2008 to 31/12/2019. An intact PC excreted in its original shape within 30 hours after swallowing was considered a positive patency test. Results A total of 465 SBCE were indicated in 333 patients. In 61.9% a previous patency test with PC was performed, with significant differences in its use according to the age at diagnosis according to the Montreal classification (A1 75.9%, A2 64.8%, A3 46.1%) and behaviour (B2 81.3%, B3 80%, B1 54.2%), the indication (postoperative recurrence monitoring 87.2%, flare 65.5%, staging small bowel disease 52.4%, assessing mucosal healing 44.8%) and the presence of previous CD surgery (68.6% vs. 55.6%). In 33 cases (7%) SBCE was contraindicated due to negative patency test. Eleven SBCE were retained of the 432 procedures finally performed (incidence 2.5%; 95% CI 1.06%-4.02%). Retention occurred in 5.6% of procedures without prior PC compared to 0.4% with previous PC (p<0.001). Stricturing disease (OR 2.94; 1.31-6.58), penetrating disease (OR 3.85; 1.59-9.31) and presence of elevated inflammatory markers (OR 3.73; 1.85-7.50) were identified as independent factors associated with retention (negative PC test or SBCE retention) in the multivariate analysis. Conclusion A patency test prior to SBCE was performed in 61.9% of patients with known CD. The use of PC is associated with a lower risk of SBCE retention in a routine clinical setting. Patients with stricturing or penetrating disease or elevation of inflammatory markers have significantly higher risk of retention and would therefore benefit from a pre-SBCE PC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".