Risk Factor Analysis and Prevalence of Infectious Agents in Inflammatory Bowel Disease Flares: A Retrospective Study
Bibliographic record
Abstract
Background: Inflammatory bowel disease (IBD), which includes Crohn's disease (CD) and ulcerative colitis (UC), is a chronic relapsing-remitting disorder with a rising global incidence. Infectious agents, particularly Clostridium difficile, are frequently considered during IBD flares. However, the role of other infectious agents during these exacerbations remains unclear. Objectives: The objective of the current study was to assess the prevalence of infectious agents, including C. difficile, in stool samples of patients with IBD flares and to assess potential risk factors. Methods: A retrospective review was conducted on medical records of IBD patients admitted for flare-ups at Mount Sinai Hospital, Toronto, from October 2018 to August 2019. Stool testing, including cultures, ova, parasites, and C. difficile, was analyzed. Demographic and clinical data were collected, and chi-square tests were used for statistical analysis. Results: A total of 96 patients (51 CD, 43 UC, 2 IBD-U) were included. Nine patients (9%) tested positive for C. difficile. No other bacterial or parasitic infections were detected. Testing for Cytomegalovirus was performed in 33 patients, with no positive cases. Risk factors, including IBD phenotype, biologic or steroid therapy, and prior antibiotic use, showed no significant association with C. difficile infection. Conclusions: Clostridium difficile was the predominant infectious agent in IBD flares, while other bacterial and parasitic infections were rare. Routine stool testing, particularly for non-C. difficile pathogens, has a low diagnostic yield in this population. Further studies with larger, generalized cohorts are needed to explore these associations and identify risk factors for infectious colitis in IBD patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".