Risk Factors for Venous Ulcer Following ACUTE Venous Thromboembolism: Results from the Riete Registry
Bibliographic record
Abstract
Abstract Background: Venous ulcer, the most serious consequence of chronic venous insufficiency (CVI), is associated with a high morbidity, impaired quality of life and high costs. To date, risk factors for venous ulcer after acute VTE have not been characterized. Objective: To identify independent predictors of venous ulcer development one year after an acute VTE event. Methods: Using data from the RIETE international registry, we analysed risk factors for venous ulcers in patients with an objectively confirmed symptomatic acute VTE (DVT and/or pulmonary embolism (PE)) and followed up for at least one year. During follow-up, signs and symptoms of CVI, occurrence of a venous ulcer in the leg ipsilateral to DVT or, in the absence of reported DVT, in any leg were reported by local investigators. Independent predictors of venous ulcers were assessed using a stepwise multivariable model. Results: Of the 34,144 patients included in the RIETE registry, 4,305 were recruited in centres participating in long-term (1 to 3 years) follow-up. Of these, 54% (n=2,337) underwent an assessment for CVI. After a mean (SD) follow-up of 383 (+/-575) days, 55% (n=1297) had signs or symptoms of CVI and 2.5% (n=59) had developed a venous ulcer. History of previous VTE (OR=4.4 [2.6 - 7.7], signs of venous insufficiency (i.e. leg varicosities) at time of VTE event (OR=2.3 [1.3 - 4.0]), diabetes (OR=2.0 [1.0 - 3.8]), obesity (OR=1.8 [1.1 - 3.2]) and male sex (OR=2.7 [1.5 - 4.9]) were independent predictors of an increased risk of venous ulcer. Conversely, older age, presence of an objectively confirmed DVT at study enrolment, anticoagulant duration (<1 vs. >1 year), anticoagulant type (extended low molecular weight heparin vs. vitamin K antagonist), or presence of vena cava filter had no significant impact on risk of venous ulcer. When restricting our analysis to the 1790 patients with objectively confirmed DVT only, results remained similar in magnitude. Proximal character of DVT was associated with a 30% non-significant increased risk of - unquestionable - post-thrombotic ulcer but the proportion of distal DVT was low in our population (11%). Conclusions: After an acute VTE event, history of VTE, pre-existing signs of CVI, male sex, diabetes and obesity independently influenced the risk of venous ulcer. VTE therapeutic management (neither duration nor drugs) did not appear to modify this risk. Our results suggest that clinicians should consider strategies aimed to prevent ulcers in high risk patients, such as preventing VTE recurrence, use of compression stockings in those with CVI and encouraging weight loss in obese patients. Disclosures Galanaud: bayer: Membership on an entity's Board of Directors or advisory committees, Research Funding; Daichi: Membership on an entity's Board of Directors or advisory committees, Research Funding. Bertoletti:Daichi: Honoraria; bayer: Honoraria; BMS-Pfizer: Consultancy, Honoraria. Monreal:Bayer: Consultancy, Membership on an entity's Board of Directors or advisory committees; sanofi: Consultancy, Membership on an entity's Board of Directors or advisory committees; boehringer: Consultancy, Membership on an entity's Board of Directors or advisory committees; daichii: Consultancy, Membership on an entity's Board of Directors or advisory committees.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".