Incidence Rates for Surgery in Crohn’s Disease Have Decreased: A Population-based Time-trend Analysis
Bibliographic record
Abstract
BACKGROUND: Many Crohn's disease (CD) patients will undergo surgery over the course of their life. It is thought that with the introduction of disease-modifying agents like anti-TNF therapy, there would be a population-level decrease in the need for surgery. This time-trend study aimed to assess the changes in surgical rates following the induction of anti-TNF therapy. METHODS: Adult CD patients who underwent abdominal surgery (identified by administrative coding) between January of 1996 and December of 2013 at 1 of the 4 Edmonton-area hospitals were included. Patient charts were manually reviewed to confirm diagnosis and gather demographic and disease-related data. Population-adjusted annual incidence rates for IBD surgery were calculated by dividing the number of surgeries by estimates for total population of CD patients in Edmonton. Time-trend analysis was conducted to identify change points, calculate annual percent change (APC), and associated 95% confidence intervals (CIs). RESULTS: A total of 1410 patients with Crohn's disease underwent surgery for their disease. The surgical rate decreased by 8.4% each year (95% CI, -9.6% to -7.3%). There was a 36.2% increase in the use of anti-TNF therapy per year (95% CI, 31.3% to 41.5%). Changes in modifiable risk factors for surgery were also seen, including the proportion of active smokers decreasing by 2.2% per year (95% CI, -3.7% to -0.6%). CONCLUSIONS: Although anti-TNF therapy seems to play a role, the decrease in surgical trends is likely multifactorial, owing to a decline in smoking trends, earlier diagnosis, earlier treatment, improved patient education, and changes in clinical practice.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".