Initial Management of Noncirrhotic Splanchnic Vein Thrombosis: When Is Anticoagulation Enough?
Bibliographic record
Abstract
BACKGROUND: The optimal initial treatment of splanchnic vein thrombosis is uncertain. Anticoagulant therapy has been shown to be associated with vessel recanalization and decreased recurrence. Furthermore, information regarding potential predictors of chronic complications is not well understood. METHODS: A retrospective cohort study involving consecutive patients diagnosed with first-episode noncirrhotic splanchnic vein thrombosis referred to the thrombosis clinic of the authors' institution between 2008 and 2011 was conducted. Demographic and clinical information was collected. The response to initial anticoagulant therapy was evaluated by determining radiographic recanalization of vessels and clinical resolution (defined as the absence of ongoing splanchnic vein thrombosis symptoms or complications requiring treatment beyond anticoagulant therapy). RESULTS: Twenty-two patients were included. Anticoagulant therapy alone resulted in vessel recanalization in 41% of patients and 68% achieved clinical resolution. Two patients experienced bleeding events. Factors associated with a lack of clinical resolution included signs of portal hypertension⁄liver failure on presentation, complete vessel occlusion at diagnosis, presence of a myeloproliferative disorder or JAK2V617F tyrosine kinase mutation and the absence of a local⁄transient predisposing factor. CONCLUSIONS: Anticoagulant therapy appeared to be an effective initial treatment in patients with splanchnic vein thrombosis. Clinical factors may help to identify patients who are at risk for developing complications thus requiring closer monitoring. These findings were limited by the small sample size and need to be explored in larger prospective studies.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".