Isolated Distal Deep Vein Thrombosis: Perspectives from the GARFIELD-VTE Registry
Bibliographic record
Abstract
Abstract Isolated distal deep vein thrombosis (IDDVT) represents up to half of all lower limb DVT. This study investigated treatment patterns and outcomes in 2,145 patients with IDDVT in comparison with those with proximal DVT (PDVT; n = 3,846) and pulmonary embolism (PE; n = 4,097) enrolled in the GARFIELD-VTE registry. IDDVT patients were more likely to have recently undergone surgery (14.6%) or experienced leg trauma (13.2%) than PDVT patients (11.0 and 8.7%, respectively) and PE patients (12.7 and 4.5%, respectively). Compared with IDDVT, patients with PDVT or PE were more likely to have active cancer (7.2% vs. 9.9% and 10.3%). However, influence of provoking factors on risk of recurrence in IDDVT remains controversial. Nearly all patients (IDDVT, PDVT, and PE) were given anticoagulant therapy. In IDDVT, PDVT, and PE groups the proportion of patients receiving anticoagulant therapy was 61.4, 73.9, and 81.1% at 6 months and 45.8, 54.7, and 61.9% at 12 months. Over 12 months, the incidence of all-cause mortality, cancer, and recurrence was significantly lower in IDDVT patients than PDVT patients (hazard ratio [HR], 0.61 [95% confidence interval [CI], 0.48–0.77]; sub-HR [sHR], 0.60 [95% CI, 0.39–0.93]; and sHR, 0.76 [95% CI, 0.60–0.97]). Likewise, risk of death and incident cancer was significantly (both p < 0.05) lower in patients with IDDVT compared with PE. This study reveals a global trend that most IDDVT patients as well as those with PDVT and PE are given anticoagulant therapy, in many cases for at least 12 months.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".