Prospective Evaluation of Health-Related Quality of Life in Patients With Deep Venous Thrombosis
Bibliographic record
Abstract
BACKGROUND: To our knowledge, the burden of deep venous thrombosis from the patient's perspective has not been quantified. We evaluated health-related quality of life (QOL) after deep vein thrombosis and compared results with general population norms. METHODS: This was a multicenter prospective cohort study of 359 consecutive eligible patients with deep vein thrombosis recruited at 7 Canadian hospital centers. Quality of life was assessed at baseline and at 1 and 4 months after diagnosis using generic (36-Item Short-Form Health Survey) and disease-specific (Venous Insufficiency Epidemiological and Economic Study [VEINES]-QOL and VEINES symptom [VEINES-Sym] questionnaires) measures. Changes in QOL scores during the 4-month period were calculated, and determinants of lack of improvement in QOL were evaluated. RESULTS: During the 4 months, mean 36-Item Short-Form Health Survey physical and mental component summary scores improved by 5.1 and 4.6 points, respectively, and VEINES-QOL and VEINES-Sym scores improved by 3.1 and 2.2 points, respectively (P < .001 for time trend for all measures). However, about one third of patients had worsening of QOL during follow-up. Multivariate analyses showed that worsening of the postthrombotic syndrome score was an independent predictor of worsening of 36-Item Short-Form Health Survey physical component summary (P = .04), VEINES-QOL (P < .001), and VEINES-Sym (P < .001) scores. The 36-Item Short-Form Health Survey physical component summary scores were lower than population norms at all points assessed. CONCLUSIONS: On average, QOL improves during the 4 months following deep vein thrombosis. However, in about one third of patients, QOL deteriorates, and at 4 months, average QOL remains poorer than population norms. Worsening of the postthrombotic syndrome score is associated with worsening of QOL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".