Impact of self-reported race on Villalta Scale postthrombotic syndrome scores and correlation with venous disease-specific quality of life: an exploratory analysis of the Acute Venous Thrombosis: Thrombus Removal with Adjunctive Catheter-Directed Thrombolysis Trial
Bibliographic record
Abstract
Background The Villalta Scale (VS) to diagnose postthrombotic syndrome (PTS) consists of 5 patient-reported leg symptoms and 6 clinician-rated leg signs. It is unknown how the scale performs across racial groups. Objectives Our study explored if there were differences in VS scores, particularly clinician-rated signs components, according to self-reported race. Methods Exploratory analysis of the ATTRACT trial, a randomized controlled trial conducted at 56 US sites that investigated pharmacomechanical catheter-directed thrombolysis to prevent PTS after proximal deep vein thrombosis (DVT). At the 6-month visit after randomization, we compared self-reported Black (n = 123) and White (n = 541) participants for mean total VS score, VS symptoms score, VS signs score, individual signs scores, and correlation coefficients between VS signs and VS symptoms scores and between VS signs and Venous Insufficiency Epidemiological and Economic Study Quality of Life (VEINES-QOL) scores (a self-reported venous disease-specific quality of life measure). Results Mean total VS score (4.67 vs. 4.12, P = .54),VS signs score (1.66 vs. 2.00, P = .07), and VS symptoms score (2.83 vs. 2.04, P = .10) were similar between Black and White participants. The mean score for one individual VS sign, venous ectasia, was lower in Black vs. White participants (0.24 vs. 0.63, P < .01). There was similar, modest correlation in Black and White participants between VS signs and VS symptoms scores ( r black = 0.19; r white = 0.23) and between VS signs and VEINES-QOL scores ( r black = −0.32; r white = −0.30). Results were adjusted for ATTRACT trial treatment group, age, sex, body mass index, DVT extent, hypertension, diabetes, dyslipidemia, and congestive heart failure. Conclusion The findings suggest that some differences in VS scores exist according to self-reported race. It is unclear whether these reflect clinicians' underrating of some VS signs and/or differences in PTS severity. Further work is needed to understand how the VS performs across racial groups.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".