Evaluation of the PADIS score stratifying risk for venous thromboembolism recurrence after a first unprovoked pulmonary embolism: results from the REVERSE study
Bibliographic record
Abstract
Current guidelines suggest that most patients presenting with a first episode of an unprovoked venous thromboembolism (VTE) event be considered for indefinite anticoagulation, as long as their bleeding risk remains acceptably low [1, 2]. However, this exposes a considerable number of patients to long term anticoagulation as 70% of patients with a first unprovoked VTE will have no recurrence [3]. In 2010, a guidance from the International Society on Thrombosis and Haemostasis (ISTH) suggested that a 1-year cumulative rate of recurrent VTE after stopping anticoagulation of less than 5%, with a 95% confidence interval (CI) upper limit lower than 8%, is low enough to consider that long-term anticoagulant therapy would not be beneficial [4]. As such, efforts are ongoing to identify risk factors and scoring tools to help discriminate between subsets of patients whose risk/benefit ratio most- or least-strongly favours continued therapy. This study does not support that the PADIS-PE score can safely identify patients who could stop anticoagulation after a first unprovoked PE The REVERSE investigators: P.S. Wells and T. Ramsay, Ottawa, ON, Canada; S.R. Kahn, I. Chagnon and S. Solymoss, Montreal, QC, Canada; D.A. Anderson, Halifax, NS, Canada; M. Crowther, Hamilton, ON, Canada; R. White, Sacramento, CA, USA.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".