Cardiac arrhythmia in patients with inflammatory bowel disease: a retrospective, population-based cohort study in Manitoba, Canada
Bibliographic record
Abstract
OBJECTIVE: We aimed to characterise the association between inflammatory bowel disease (IBD) and IBD medications and risk of cardiac arrhythmia. DESIGN, SETTING AND PARTICIPANTS: In a retrospective population-based study using the University of Manitoba IBD Epidemiology Database (Manitoba, Canada) from 1984 to 2018, we identified 10 992 IBD cases and 102 875 matched controls. ANALYSIS: Arrhythmia risk in IBD was adjusted for the presence of comorbidities of the Charlson Comorbidity Index. The effect of IBD medications on the development of arrhythmia was assessed in a nested cohort study of individuals with IBD. Cases were censored at the date of first database identification of a diagnosis of heart failure or myocardial infarction. RESULTS: The cohort was 48.5% Crohn's disease and 51.5% ulcerative colitis, and 80.5% were incident cases. The median age of incident cases at IBD diagnosis was 35 (IQR, 25 to 49). The median age at arrhythmia diagnosis for persons with IBD was 69 years (IQR, 59 to 77) and for controls 69 years (IQR, 59 to 78). Persons diagnosed with IBD were more likely than controls (HR 1.51; 95% CI, 1.30 to 1.76) to develop arrhythmia. Persons within their sixth decade or younger had increased risk of arrhythmia. When controlling for comorbidities, the significant association between IBD and arrhythmia remains. Medications including 5-aminosalicylates, thiopurines and tumour necrosis factor-α inhibitors were not associated with arrhythmia. CONCLUSIONS: Persons with IBD have a higher risk of arrhythmia prior to a diagnosis with heart disease. Use of IBD medications was not associated with risk of arrhythmia.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".