Determinants and Time Course of the Postthrombotic Syndrome after Acute Deep Venous Thrombosis
Bibliographic record
Abstract
BACKGROUND: The reason some patients with deep venous thrombosis (DVT) develop the postthrombotic syndrome is not well understood. OBJECTIVE: To determine the frequency, time course, and predictors of the postthrombotic syndrome after acute DVT. DESIGN: Prospective, multicenter cohort study. SETTING: 8 Canadian hospital centers. PATIENTS: 387 outpatients and inpatients who received an objective diagnosis of acute symptomatic DVT were recruited from 2001 to 2004. MEASUREMENTS: Standardized assessments for the postthrombotic syndrome using the Villalta scale at 1, 4, 8, 12, and 24 months after enrollment. Mean postthrombotic score and severity category at each interval was calculated. Predictors of postthrombotic score profiles over time since diagnosis of DVT were identified by using linear mixed modeling. RESULTS: At all study intervals, about 30% of patients had mild (score, 5 to 9), 10% had moderate (score, 10 to 14), and 3% had severe (score >14 or ulcer) postthrombotic syndrome. Greater postthrombotic severity category at the 1-month visit strongly predicted higher mean postthrombotic scores throughout 24 months of follow-up (1.97, 5.03, and 7.00 increase in Villalta score for mild, moderate, and severe 1-month severity categories, respectively, vs. none; P < 0.001). Additional predictors of higher scores over time were venous thrombosis of the common femoral or iliac vein (2.23 increase in score vs. distal [calf] venous thrombosis; P < 0.001), higher body mass index (0.14 increase in score per kg/m(2); P < 0.001), previous ipsilateral venous thrombosis (1.78 increase in score; P = 0.001), older age (0.30 increase in score per 10-year age increase; P = 0.011), and female sex (0.79 increase in score; P = 0.020). LIMITATIONS: Decisions to prescribe compression stockings were left to treating physicians rather than by protocol. Because international normalized ratio data were unavailable, the relationship between anticoagulation quality and Villalta scores could not be assessed. CONCLUSION: The postthrombotic syndrome occurs frequently after DVT. Patients with extensive DVT and those with more severe postthrombotic manifestations 1 month after DVT have poorer long-term outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".