Effect of Early Physical Activity on Long-Term Outcome After Venous Thrombosis
Bibliographic record
Abstract
OBJECTIVE: To determine if the level of self-reported physical activity 1 month after deep vein thrombosis (DVT) is associated with the risk of post-thrombotic syndrome (PTS) in the first 2 years post-DVT. DESIGN: Prospective cohort study. SETTING: Multicenter study (8 hospitals). PARTICIPANTS: Patients presenting with objectively diagnosed acute DVT to 8 hospitals in Quebec and Ontario, Canada. ASSESSMENT OF RISK FACTORS: We used validated questionnaires to measure physical activity (Godin questionnaire) and venous disease severity [generic physical quality of life (SF-36 PCS scale) or VEINES-QOL]. We adjusted for potential confounding effects of age, sex, and body mass index. We used multiple imputation to account for missing data. MAIN OUTCOME MEASURES: Post-thrombotic syndrome (validated Villalta scale). RESULTS: For the 387 patients enrolled, univariate analysis suggested no association between 1-month activity and risk of PTS. After adjusting for missing data and potential confounders, there was no evidence of a trend toward increasing risk of PTS with increasing physical activity [1.65 (95% confidence interval, 0.87-3.14) for mild-moderate activity and 1.35 (95% confidence interval, 0.69-2.67) for high activity]. The results were similar when PTS was dichotomized as none/mild versus moderate/severe. Finally, patients with PTS had lower levels of activity at 2 years post-DVT. CONCLUSIONS: The level of self-reported exercise in the first month post-DVT is not associated with an increased risk of PTS in the first 2 years after DVT. Post-thrombotic syndrome is associated with decreased levels of physical activity 2 years after DVT.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".