Rising Prevalence of Venous Thromboembolism and Its Impact on Mortality Among Hospitalized Inflammatory Bowel Disease Patients
Bibliographic record
Abstract
BACKGROUND: We sought to determine nationwide, population-based trends in rates of venous thromboembolism (VTE) among hospitalized inflammatory bowel disease (IBD) patients in the United States and to determine its mortality and economic impact. METHODS: We analyzed discharges from the Nationwide Inpatient Sample and used ICD-9-CM codes to identify Crohn's disease (CD) and ulcerative colitis (UC) between 1998 and 2004. Rates of VTE were compared between those with and without IBD. The impact of VTE on in-hospital mortality and resource utilization was quantified using regression analysis. RESULTS: After multivariate adjustment, both UC (OR 1.85, 95% CI 1.70-2.01) and CD discharges (OR 1.48, 95% CI 1.35-1.62) had higher rates of VTE compared to non-IBD discharges. Prevalence of VTE was greater among UC compared to CD discharges (OR 1.32, 95% CI 1.17-1.48). Among CD patients, active fistulizing disease was independently associated with greater VTE (OR 1.39, 95% CI 1.13-1.70). There was an annual 17% rise in odds of VTE among IBD admissions over 7 yr. VTE was associated with greater mortality among IBD patients (adjusted OR 2.50, 95% CI 1.83-3.43). This age- and comorbidity-adjusted excess mortality from VTE was 2.1-fold higher for IBD than for non-IBD patients (P < 0.0001). IBD patients with VTE had longer length of stay (11.7 vs 6.1 days, P < 0.0001) and incurred higher hospital charges ($47,515 vs $21,499; P < 0.0001). CONCLUSIONS: VTE is increasingly prevalent among hospitalized IBD patients and has substantial mortality and economic impact. These findings drive the need for widespread prophylaxis against and early detection of VTE among IBD inpatients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".