Risk Factors for Developing Hidradenitis Suppurativa in Patients With Inflammatory Bowel Disease: A Retrospective Case–Control Study
Bibliographic record
Abstract
Abstract Background Hidradenitis suppurativa (HS) is associated with inflammatory bowel disease (IBD), though risk factors remain to be determined. Aim To characterize HS among a cohort of IBD patients and identify risk factors for its development. Methods This was a retrospective case–control study at the ambulatory IBD centre at Mount Sinai Hospital from inception to May 2019. Patients with IBD who developed HS were included. Cases were matched 5:1 by age, gender (male versus female) and IBD type (ulcerative colitis [UC] or Crohn’s disease [CD]) to controls who had IBD without HS. Conditional logistic regression was used to calculate odds ratios (ORs) with 95% confidence intervals (95% CIs). Results Twenty-nine cases of HS (19 CD and 10 UC) and 145 controls were included. Of the 29 patients with HS, 11 (37.9%) were male and 18 (62.1%) were female. The severity of HS was mild in 10 (34.5%), moderate in 16 (55.2%) and severe in 3 (10.3%) patients. Patients with HS and IBD were more likely to be active (OR 10.3, 95% CI 2.0 to 54.0, P = 0.006) or past (OR 8.4, 95% CI 2.7 to 25.8, P < 0.005) smokers. Patients with HS and IBD were also more likely to have active endoscopic disease (OR 3.8, 95% CI 1.2 to 12.2, P = 0.022). Furthermore, those with HS and CD were more likely to have active perianal disease (OR 21.1, 95% CI 6.2 to 71.9, P < 0.005). Conclusions Active IBD, perianal disease and smoking may be associated with HS in IBD. Larger studies are needed to better characterize this morbid condition.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".