Persistently High Rate of Venous Thromboembolic Disease in Inflammatory Bowel Disease: A Population-Based Study
Bibliographic record
Abstract
INTRODUCTION: Venous thromboembolism (VTE) is known to be increased in inflammatory bowel disease (IBD). We aimed to determine whether rates of VTE in IBD have reduced over the past 30 years. METHODS: We used the population-based University of Manitoba IBD Epidemiology Database (1984-2018) to determine the incidence of VTE in IBD and the incidence rate ratio vs matched controls. In persons with IBD with and without VTE, we assessed for variables that were associated with an increased risk of VTE on multivariate logistic regression. RESULTS: The incidence of VTE in the IBD cohort was 7.6% which was significantly greater than in controls (3.3%, P < 0.0001). The overall age-standardized incidence rate of VTE was 433 per 100,000 in IBD and 184 per 100,000 in controls. The incidence of VTE was higher in Crohn's disease (8.4%) than in ulcerative colitis (6.9%, P = 0.0028). The incidence rate ratio in IBD vs controls was 2.36 (95% confidence interval 2.16-2.58). The increased risk was similar in males and females and in Crohn's disease compared with ulcerative colitis. The incidence rate among persons with IBD from 1985 to 2018 decreased very slowly, with annual percent change of -0.7% (P = 0.0003). Hospital admission, high comorbidity, use of antibodies to tumor necrosis factor for less than 3 years up until the time of the VTE, and the combination of steroid and antibodies to tumor necrosis factor increased the risk of VTE. DISCUSSION: Despite advancements in IBD management in the past 30 years, the rates of VTE have only been slowly decreasing and remain significantly increased compared with controls.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".