The Incidence of Deep Venous Thrombosis and Pulmonary Embolism among Patients with Inflammatory Bowel Disease: A Population-based Cohort Study
Bibliographic record
Abstract
BACKGROUND: There is an impression mostly from specialty clinics that patients with inflammatory bowel disease (IBD) have an increased risk of venous thromboembolic disorders. Our aim was to determine the incidence of deep venous thrombosis (DVT) and pulmonary embolism (PE) from a population-based database of IBD patients and, to compare the incidence rates to that of an age, gender and geographically matched population control group. METHODS: IBD patients identified from the administrative claims data of the universal provincial insurance plan of Manitoba were matched 1:10 to randomly selected members of the general population without IBD by year, age, gender, and postal area of residence using Manitoba Health's population registry. The incidence of hospitalization for DVT and PE was calculated from hospital discharge abstracts using ICD-9-CM codes 451.1, 453.x for DVT and 415.1x for PE. Rates were calculated based on person-years of follow-up for 1984-1997. Comparisons to the population cohort yielded age-adjusted incidence rate ratios (IRR). Rates were calculated based on person-years of follow-up (Crohn's disease = 21,340, ulcerative colitis = 19,665) for 1984-1997. RESULTS: In Crohn's disease the incidence rate of DVT was 31.4/10,000 person-years and of PE was 10.3/10,000 person-years. In ulcerative colitis the incidence rates were 30.0/10,000 person-years for DVT and 19.8/10,000 person-years for PE. The IRR was 4.7 (95% CI, 3.5-6.3) for DVT and 2.9 (1.8-4.7) for PE in Crohn's disease and 2.8 (2.1-3.7) for DVT and 3.6 (2.5-5.2) for PE, in ulcerative colitis. There were no gender differences for IRR. The highest rates of DVT and PE were seen among patients over 60 years old; however the highest IRR for these events were among patients less than 40 years. CONCLUSION: IBD patients have a threefold increased risk of developing DVT or PE.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".