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 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 | 0.001 | 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".