Intra-Abdominal Venous and Arterial Thromboembolism in Inflammatory Bowel Disease
Bibliographic record
Abstract
Venous and arterial thromboembolism constitutes a significant cause of morbidity and mortality in patients with inflammatory bowel disease. The most common thrombotic manifestations are lower extremity deep vein thromboses with or without pulmonary embolism. Occasionally, thromboembolic events occur in the main abdominal vessels, such as the portal and superior mesenteric veins, vena cava and hepatic vein, aorta, splanchnic and iliac arteries, or in the limb arteries. The decision-making process for the treatment of these uncommon thromboembolic complications in inflammatory bowel disease may be very challenging for several reasons: 1) no standardized therapies are available; 2) the decision of starting anticoagulant therapy implies the potential risk of intestinal bleeding; 3) thromboembolic events may recur and be life-threatening if inadequately treated. The literature was searched by using MEDLINE, Embase, and the Cochrane library database. Studies published between 1970 and 2007 were reviewed. We discuss the medical and surgical therapeutic options that should be considered to optimize the outcome and reduce the risk of complications in abdominal thromboembolisms associated with inflammatory bowel disease.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".