Patient Management Strategies and Long-Term Outcomes in Isolated Distal Deep-Vein Thrombosis versus Proximal Deep-Vein Thrombosis: Findings from XALIA
Bibliographic record
Abstract
Background Overall, 30 to 50% of lower-limb deep-vein thrombosis (DVT) cases are isolated distal DVT (IDDVT). The recurrent venous thromboembolism (VTE) risk is unclear, leaving uncertainty over optimal IDDVT treatment. We present data on patients with IDDVT and proximal DVT (PDVT) from the prospective, noninterventional XALIA study of rivaroxaban for acute and extended VTE treatment. Methods Patients aged ≥18 years scheduled to receive ≥3 months' anticoagulation with rivaroxaban or standard anticoagulation were eligible, with follow-up for ≥12 months. We describe baseline characteristics, management strategies, and incidence proportions of VTE recurrence, major bleeding, and all-cause mortality in patients with IDDVT or PDVT, with or without distal vein involvement. Findings Overall, 1,004 patients with IDDVT and 3,098 with PDVT were enrolled; 641 (63.8%) and 1,683 (54.3%) received rivaroxaban, respectively. Patients with IDDVT were younger and had lower incidences of renal impairment, cancer, and unprovoked VTE than those with PDVT. On-treatment recurrence incidences for IDDVT versus PDVT were 1.0 versus 2.4% (adjusted hazard ratio [HR]: 0.56; 95% confidence interval [CI]: 0.29–1.08), and incidences posttreatment cessation were 1.1 versus 2.1% (adjusted HR: 0.65; 95% CI: 0.32–1.35), respectively. On-treatment major bleeding incidences were 0.9 versus 1.4% and mortality was 0.8 versus 2.2%, respectively. Median treatment duration in patients with IDDVT was shorter than in those with PDVT (102 vs. 192 days, respectively). Interpretation Patients with IDDVT had fewer comorbidities and were more frequently treated with rivaroxaban than those with PDVT. On-treatment and posttreatment recurrences were less frequent in patients with IDDVT. Trial registration number: NCT01619007.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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 teacher head, 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".