THE IMPACT OF OBESITY ON THE PREVALENCE AND SEVERITY OF PERIANAL COMPLICATIONS OF CROHN'S DISEASE
Bibliographic record
Abstract
Abstract INTRODUCTION The incidence of obesity in patients with inflammatory bowel disease (IBD) is increasing and there is limited data on the effects of obesity on disease phenotype. Several studies have investigated the association of obesity with perianal fistulizing disease with conflicting results. In this study, we aim to examine the relationship between obesity and the prevalence and severity of perianal complications in patients with Crohn’s disease (CD). METHODS We conducted a cross-sectional study of CD patients treated at a tertiary care center from 2012 to 2022. Collected data included sex, race, smoking history, family history, maximum body mass index (BMI), and Montreal classification (Table 1). Obesity was defined as maximum BMI ≥30kg/m2 and further subdivided into 5 BMI categories (Table 2). The prevalence of perianal disease was defined by a history of perianal fistula. The severity of perianal disease was measured by four variables including history of perianal fistula surgery, number of perianal surgeries, history of fecal diversion, and median time to first anal surgery. Perianal fistula surgeries included abscess incision and drainage, seton placement, fistulectomy, and/or fistulotomy. Pearson’s chi-squared test was used to compare 2 categorical variables (non-obese vs obese). Exact Cochran-Armitage trend test was used to compare 5 BMI categorical variables. A 95% confidence interval was used with an alpha of 0.5. Values of p <0.05 was considered statistically significant. Data analysis was performed using Excel. RESULTS A total of 704 patients with CD were treated. In all, 68.9% were non-obese and 31.1% were obese. Furthermore, 2.8% were underweight, 36.5% normal weight, 29.5% overweight, 17.9% obese, and 13.2% severely obese. Non-obese patients were more likely to have a family history of IBD (p=0.043). Obese patients were more likely to have extraintestinal manifestations (p=0.004) and/or be former smokers (p=0.004). There was no significant association between obesity and prevalence of perianal fistula (p=0.719), history of perianal surgery (p=0.146), history of one or more perianal surgeries (p=0.220), history of fecal diversion (p=0.705) or median time to first perianal surgery (p=0.192) (Table 1). Increasing BMI category was not associated with the prevalence of perianal fistula (p=0.944), perianal surgery (p=0.583), more than one perianal surgery (p=0.114), fecal diversion (p=0.542) or median time to first perianal surgery (p=0.486) (Table 2). DISCUSSION In conclusion, there was no significant correlation between obesity and prevalence of perianal disease. Additionally, there was no significant correlation between obesity and severity of perianal disease. The overall impact of obesity on CD complications is still unknown and warrants further investigation.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".