A152 RISK OF VENOUS THROMBOEMBOLIC EVENTS IN PATIENTS WITH INFLAMMATORY BOWEL DISEASE IN THE POST-DISCHARGE PERIOD
Bibliographic record
Abstract
Patients with inflammatory bowel disease (IBD) are at increased risk of venous thromboembolism (VTE), particularly in the hospital setting. A number of factors which place these patients at increased risk of VTE, may persist after discharge. Although guidelines recommend thromboprophylaxis for all admitted patients with IBD, it remains unclear if prophylaxis should be extended after hospital discharge. To determine the incidence and timing of VTE in patients with IBD in the post discharge setting, and to identify which patients are at highest risk. A retrospective, single center, observational cohort study was conducted between January 1, 2009 and December 31, 2016. Patients with IBD admitted to our institution were identified by our institutional database. A manual chart review was conducted to confirm a diagnosis of IBD, and VTE events during hospitalization and within 6 months of discharge. Patients with a VTE event during hospitalization and those with inadequate follow-up were excluded. Risk factors associated with developing VTE were determined by univariate logistic regression accounting for repeated observations from a single patient using a random effects model. Our search identified 1175 eligible patients with a total of 2161 encounters; 1453 (67%) Crohn’s disease (CD) encounters and 688 (32%) ulcerative colitis (UC) encounters. Overall 1370 (63%) were admissions for an IBD flare, and 679 (31.4%) involved inpatient surgery. Fifty-nine encounters (2.7%) were diagnosed with a VTE within 6 months of discharge; 43 (3.0%) of all CD encounters, and 16 (2.3%) of all UC encounters. Of the patients who underwent surgery, 12(1.8%) were diagnosed with a VTE event. Overall the median time to event was 60 days (range 3–182 days). Age (OR, 1.02; 95% CI, 1.01–1.04), length of hospitalization (OR, 1.01; 95% CI, 1.00–1.03), and prior VTE event (OR, 31.73; 95% CI, 14.14–71.22) were significantly associated with risk of VTE following discharge. A minority of patients with IBD develop VTE events after discharge from hospital. Age, length of hospitalization, and prior VTE events may predict patients at highest risk that would benefit from extended thromboprophylaxis. Further studies are required to confirm these findings and to determine if extended prophylaxis can reduce the risk of VTE in the post discharge setting. None
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".