Pain and health-related quality of life in people with chronic leg ulcers
Bibliographic record
Abstract
INTRODUCTION: Venous leg ulceration is associated with pain and poor health-related quality of life (HRQL). The purpose of this study was to identify demographic and clinical characteristics associated with pain and decreased HRQL in patients with active venous ulcers. METHODS: Baseline data were combined from two trials that took place between 2001 and 2007 (n = 564). Pain was measured using the Numeric Pain Scale (NPS), and HRQL was measured using the Medical Outcomes Survey 12-item Short Form (SF-12), which generates a Physical (PCS) and Mental Component Summary (MCS). Analyses included logistic and linear regression (for pain and HRQL, respectively). RESULTS: Mean age was 66.5 years; 47% were male. Median NPS score was 2.2 (out of 10) and mean PCS and MCS scores were 38.0 and 50.5, respectively (scores are standardized to a mean of 50 representing average HRQL). Younger age, living with others, and arthritis were associated with pain. Poorer PCS was associated with being female, venous/mixed ulcer etiology, larger ulcers, longer ulcer duration, cardiovascular disease, arthritis and higher pain intensity. Poorer MCS was associated with younger age, longer ulcer duration, comorbidity and higher pain intensity. CONCLUSION: Research is needed to test strategies to reduce pain and possibly improve HRQL in high risk 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".