The Association of Smoking and Surgery in Inflammatory Bowel Disease is Modified by Age at Diagnosis
Bibliographic record
Abstract
OBJECTIVES: We assessed the association of smoking at diagnosis of inflammatory bowel disease (IBD) on the need for an intestinal resection. METHODS: The Health Improvement Network was used to identify an inception cohort of Crohn's disease (n=1519) and ulcerative colitis (n=3600) patients from 1999-2009. Poisson regression explored temporal trends for the proportion of newly diagnosed IBD patients who never smoked before their diagnosis and the risk of surgery within 3 years of diagnosis. Cox proportional hazard models assessed the association between smoking and surgery, and effect modification was explored for age at diagnosis. RESULTS: The rate of never smokers increased by 3% per year for newly diagnosed Crohn's disease patients (incidence rate ratio (IRR) 1.03; 95% confidence interval (CI): 1.02-1.05), but not for ulcerative colitis. The rate of surgery decreased among Crohn's disease patients aged 17-40 years (IRR 0.96; 95% CI: 0.93-0.98), but not for ulcerative colitis. Smoking at diagnosis increased the risk of surgery for Crohn's disease patients diagnosed after the age of 40 (hazard ratio (HR) 2.99; 95% CI: 1.52-5.92), but not for those diagnosed before age 40. Ulcerative colitis patients diagnosed between the ages of 17 and 40 years and who quit smoking before their diagnosis were more likely to undergo a colectomy (ex-smoker vs. never smoker: HR 1.66; 95% CI: 1.04-2.66). The age-specific findings were consistent across sensitivity analyses for Crohn's disease, but not ulcerative colitis. CONCLUSIONS: In this study, the association of smoking and surgical resection was dependent on the age at diagnosis of IBD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".