Review article: Risk of cardiovascular events in patients with inflammatory bowel disease receiving small molecule drugs
Bibliographic record
Abstract
BACKGROUND: In the context of an ageing inflammatory bowel disease (IBD) population, cardiovascular comorbidities become particularly relevant. Novel small molecule drugs (SMDs) for the treatment of moderate-to-severe IBD have been recently approved, including Janus kinase (JAK) inhibitors and sphingosine-1-phosphate receptor (S1P) modulators. Data from rheumatoid arthritis population have raised concerns about the risk of cardiovascular events with the use of tofacitinib, which was extrapolated to other immune-mediated diseases and other JAK inhibitors. S1P receptor modulation has been associated with potential cardiovascular events, especially bradycardia and cardiac conduction abnormalities. AIM: To review the incidence of cardiovascular events with the use of SMDs in patients with IBD and to provide practical recommendations on mitigation strategies. METHODS: Published literature was reviewed; recommendations were synthesised by experts in both cardiovascular diseases and IBD. RESULTS: Evidence from the IBD population does not indicate a higher risk of cardiovascular events with tofacitinib and other JAK inhibitors. The risk is higher in patients with intermediate to high cardiovascular risk. S1P modulators may be associated with a dose-dependent, first-dose effect, transient risk of conduction abnormalities (bradycardia and AV block). Screening and monitoring of cardiovascular risk factors should be done in all patients with IBD. Risk stratification for cardiovascular disease should be performed before starting treatment with SMDs. CONCLUSIONS: Available evidence of both JAK inhibitors and S1P modulators indicates a reassuring safety profile of SMDs from the cardiovascular perspective in the overall IBD population. Efforts should be made to identify patients with IBD at a higher risk of cardiovascular events.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".