Frequency and Predictors of Post-Thrombotic Syndrome in Patients with a First, Unprovoked Deep Vein Thrombosis and No Prior Primary Venous Insufficiency: Results From the REVERSE Cohort Study,
Bibliographic record
Abstract
Abstract Abstract 3332 Background: Post thrombotic syndrome (PTS) is the most common complication of deep vein thrombosis (DVT). Symptoms and signs assessed by the Villalta PTS scale are non-specific and may have causes other than PTS, especially primary venous insufficiency. This may lead to an overestimate of patients categorized as having PTS. To date, the frequency and predictors of PTS in patients with DVT who are free of primary venous insufficiency have not been evaluated. Methods: Using data from the REVERSE prospective multicentre cohort study, we analyzed the prevalence and risk factors for PTS in patients who had a first, unprovoked, unilateral proximal DVT 5–7 months previously and did not have clinically significant primary venous insufficiency (defined as the absence of moderate or severe venous ectasia in the contralateral leg). At the time of enrolment in the REVERSE study, PTS was evaluated in the DVT-affected leg using the Villalta scale and was considered to be present if Villalta score >4. Independent predictors of PTS were assessed using a multivariable logistic regression model adjusting for age, sex, and use of compression stockings and included all variables achieving a p value ≤ 0.10 in univariate analysis. Results: Between October 2001 and March 2006, 664 patients were enrolled in the REVERSE study after having received a 5–7 month course of anticoagulant therapy. Of these, 452 had DVT with or without concomitant pulmonary embolism (PE) as the index event. Of these, 131 patients were excluded from this sub-study for the following reasons: previous secondary DVT/PE (n=24), presence of moderate or severe venous insufficiency in the contralateral leg (n=54), no PTS assessment (n=53). Among the remaining 321 sub-study patients, 48% (n=155) reported using compression stockings. The overall prevalence of PTS 5–7 months after DVT was 27.4% (n=88). The distribution of PTS severity category was as follows: mild PTS (Villalta score, 5–9) in 80% (n=70) of cases, moderate PTS (Villalta score, 10–14) in 17% (n=15) of cases and severe PTS (Villalta score ≥15 or ipsilateral leg ulcer) in 3.4% (n=3) of cases. In univariate analysis, age, sex, concomitant PE at presentation, thrombophilia (mutation of factor II or V, elevated factor VIII or hyperhomocysteinemia, presence of a lupus anticoagulant) and levels of the inflammatory marker C reactive protein or elevated ddimer before stopping anticoagulant therapy did not influence the risk of developing a PTS at 5–7 months (all p>0.10). Obesity (OR=2.3 [1.3 – 4.0]), household income <$25,000 per annum (OR= 2.8 [1.2 – 6.8]), mild venous insufficiency (OR=2.3 [1.2 – 4.4]) and ultrasonographic evidence of ipsilateral vein wall thickening or residual venous obstruction at 5–7 months (OR=1.9 [1.0 – 3.4]) were found to be predictors of PTS in the multivariable model. Poor INR control tripled the risk of PTS but the result did not reach statistical significance (OR=3.5 [0.8 – 15.8]). When restricting our analysis to the 226 patients without any signs, even mild, of contralateral venous insufficiency, the prevalence of PTS decreased slightly to 24.8% (n=56). Only obesity remained an independent predictor of PTS (OR=2.3 [1.2 – 4.4]). Poor INR control, ultrasonographic features described above and household income <$25,000 per annum also increased the risk of PTS, but results were no or no longer statistically significant (OR=2.8 [0.5 – 17.1], OR= 1.7 [0.9 – 3.4] and (OR=1.7 [0.7 – 4.5]) respectively). Conclusions: In a population of patients with a first unprovoked proximal DVT and without significant primary venous insufficiency, obesity and ultrasonographic evidence of DVT sequelae at 5–7 months after DVT independently influenced the risk of PTS. Mild clinical expression of primary venous insufficiency was also found to be a predictor of PTS and could therefore play a role in PTS pathophysiology. Nevertheless, it had a limited impact on the assessment of the overall prevalence of ipsilateral PTS according to the Villalta scale. Disclosures: Crowther: Pfizer: Consultancy, Honoraria; Leo Pharma: Consultancy, Honoraria; Bayer: Consultancy, Honoraria; BI: Honoraria; CSL Behring: Consultancy; Octaphram: Consultancy; Artisan: Consultancy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".