Feasibility of Venous Thromboembolism Prophylaxis During Inflammatory Bowel Disease Flares in the Outpatient Setting
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease (IBD) patients are at increased risk of venous thromboembolism (VTE), which is most pronounced during a disease flare. We explored the cost-effectiveness of pharmacological VTE prophylaxis in an outpatient setting. METHODS: Markov decision analysis was conducted from a societal perspective to compare the relative costs and effectiveness of pharmacological VTE prophylaxis versus no anticoagulation during ambulatory IBD flares among a hypothetical cohort of 10,000 IBD patients. The time horizon was from time of IBD diagnosis until death. Univariate and probabilistic sensitivity analyses were performed. RESULTS: In base case analysis, VTE prophylaxis was, compared with no anticoagulation, associated with higher average costs (U.S. $141,036 versus $90,338) and quality-adjusted life-years (QALYs) (22.29 versus 22.25), yielding an incremental cost-effectiveness ratio of $1,267,450/QALY. Venous thromboembolism prophylaxis resulted in higher unadjusted life-years (47.76 life-years versus 46.67 life-years) and lower lifetime risk of VTE (6.2% versus 9.3%). The number needed to treat to prevent one VTE event over a lifetime was 32.3. Univariate sensitivity analysis showed that the incremental cost-effectiveness ratio was most sensitive to variations in the efficacy of VTE prophylaxis. In probabilistic sensitivity analysis, only 20% of 1000 simulated trials showed that VTE prophylaxis increased QALYs. In the remaining 80%, it was associated with both higher costs and fewer QALYs. CONCLUSIONS: Although the administration of pharmacological VTE prophylaxis during IBD flares in the outpatient setting was associated with increased life-years and reduced VTE events, it was not cost effective. Moreover, the benefits of VTE prophylaxis were not robust to probabilistic sensitivity analysis.
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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 | 0.003 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".