Post-operative Recurrence of Crohn’s Disease: There Is More to It than Meets the Eye
Bibliographic record
Abstract
Recurrence after intestinal resection and anastomosis is a characteristic of Crohn’s disease [CD]. 1 Immunological and histological recurrence may be demonstrable within days after restoration of intestinal continuity. 2 Endoscopic ulceration indicating recurrence occurs in a significant proportion of patients within a year of resection, but clinical recurrence and complications tend to follow endoscopic recurrence at variable intervals depending on the severity of endoscopic recurrence. 3 , 4 Interventions to prevent recurrence have stratified patients either based on severity of endoscopic recurrence or based on putative phenotypic risk factors for recurrence soon after resection and anastomosis. To prevent either clinical recurrence or endoscopic recurrence, 5-aminosalicylic acid, antibiotics, thiopurines and tumour necrosis factor inhibitors [TNFi] have been used with variable single or composite endpoints and variable duration of follow-up. The results have been inconsistent and conflicting. 5 In CD, and especially in the postoperative period, there is a marked disconnect between clinical symptoms and objective parameters of recurrent inflammation. This often poses problems in designing endpoints in interventional clinical trials. 6 , 7 In an effort to establish a more objective surrogate endpoint, colonoscopy, wireless capsule video endoscopy, magnetic resonance enterography, trans-abdominal ultrasonography, and faecal calprotectin have all been used to detect early recurrence of CD after surgery. A formal scoring of the anastomotic recurrence at colonoscopy was developed to assist in the prediction of clinical recurrence and complications. This score, the Rutgeerts score, has stood the test of time though it has never been robustly validated, and it has been used widely in interventional clinical trials, in clinical practice, and in empirical algorithms designed to formulate strategies to manage CD patients after resectional [so-called ‘curative’ operations] surgery. 1 , 3 , 8
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".