Association of Splanchnic Vein Thrombosis on Survival: 15‐Year Institutional Experience With 1561 Cases
Bibliographic record
Abstract
Background Previous studies regarding survival in patients with splanchnic vein thrombosis (SVT) are limited. This study measured overall survival in a large cohort of SVTs through linkage to population-based data. Methods and Results Using a previously derived text-search algorithm, we screened the reports of all abdominal ultrasound and contrast-enhanced computed tomography studies at The Ottawa Hospital over 14 years. Screen-positive reports were manually reviewed by at least 2 authors to identify definite SVT cases by consensus. Images of uncertain studies were independently reviewed by 2 radiologists. One thousand five hundred sixty-one adults with SVT (annual incidence ranging from 2.8 to 5.9 cases/10 000 patients) were linked with population-based data sets to measure the presence of concomitant cancer and survival status. Thrombosis involved multiple veins in 314 patients (20.1%), most commonly the portal vein (n=1410, 90.3%). Compared with an age-sex-year matched population, patients with SVT had significantly reduced survival in particular with local cancer (adjusted relative excess risk for recent cases 12.0 [95% CI, 9.8-14.6] and for remote cases 9.7 [7.7-12.2]), distant cancer (relative excess risk for recent cases 5.7 [4.5-7.3] and for remote cases 5.4 [4.4-6.6]), cirrhosis (relative excess risk 8.2 [5.3-12.7]), and previous venous thromboembolism (relative excess risk 3.8 [2.4-6.0]). One hundred fifty (23.9%) of patients >65 years of age were anticoagulated within 1 month of diagnosis. Conclusions SVT is more common than expected. Most patients have cancer and the portal vein is by far the most common vein involved. Compared with the general population, patients with SVT had significantly reduced survival, particularly in patients with concomitant cancer, cirrhosis, and previous venous thromboembolic disease. Most elderly patients did not receive anticoagulant therapy.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".