The Risk of Developing Crohn's Disease After an Appendectomy: A Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Studies exploring the association between appendectomy and Crohn's disease (CD) have reported conflicting findings. We conducted a systematic review of the literature and a meta-analysis to assess the risk of CD following an appendectomy and determine the effect of time between appendectomy and CD diagnosis. METHODS: MEDLINE was used to identify observational studies evaluating the association between appendectomy and CD. Authors were contacted when data were insufficient. Relative risks (RR) with 95% confidence intervals (CI) were calculated using a random effects model. Studies that analyzed their data by the interval between the appendectomy and the diagnosis of CD were assessed separately. The Woolf chi(2) statistic was used to test for homogeneity. Egger's test was used to evaluate publication bias. RESULTS: The summary RR estimate for CD following an appendectomy was significantly elevated (RR 1.61, 95% CI 1.28-2.02), though heterogeneity was observed (P < 0.0001). The risk was elevated within the first year following the operation (RR 6.69, 95% CI 5.42-8.25). The risk of CD was also significantly increased 1-4 yr following an appendectomy (RR 1.99, 95% CI 1.66- 2.38); however, after 5 yr or more, the risk fell to baseline levels (RR 1.08, 95% CI 0.99-1.18). Publication bias was not detected (P = 0.2). CONCLUSION: The meta-analysis demonstrated a significant risk of CD following an appendectomy, though heterogeneity was observed between the studies. The elevated risk early after an appendectomy, which diminishes thereafter, likely reflects diagnostic problems in patients with incipient CD.
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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 | 0.018 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.072 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".