Appendectomy does not decrease the risk of future colectomy in UC: results from a large cohort and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: Early appendectomy is inversely associated with the development of UC. However, the impact of appendectomy on the clinical course of UC is controversial, generally favouring a milder disease course. We aim to describe the effect appendectomy has on the disease course of UC with focus on the timing of appendectomy in relation to UC diagnosis. DESIGN: Using the National Institute of Diabetes and Digestive and Kidney Diseases Inflammatory Bowel Disease Genetics Consortium database of patients with UC, the risk of colectomy was compared between patients who did and did not undergo appendectomy. In addition, we performed a meta-analysis of studies that examined the association between appendectomy and colectomy. RESULTS: 2980 patients with UC were initially included. 111 (4.4%) patients with UC had an appendectomy; of which 63 were performed prior to UC diagnosis and 48 after diagnosis. In multivariable analysis, appendectomy performed at any time was an independent risk factor for colectomy (OR 1.9, 95% CI 1.1 to 3.1), with appendectomy performed after UC diagnosis most strongly associated with colectomy (OR 2.2, 95% CI 1.1 to 4.5). An updated meta-analysis showed appendectomy performed either prior to or after UC diagnosis had no effect on colectomy rates. CONCLUSIONS: Appendectomy performed at any time in relation to UC diagnosis was not associated with a decrease in severity of disease. In fact, appendectomy after UC diagnosis may be associated with a higher risk of colectomy. These findings question the proposed use of appendectomy as treatment for UC.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 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 teacher head, 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".