Patient and wound factors associated with <scp>WOUND</scp>‐Q scales measuring health‐related quality of life: An international cross‐sectional study
Bibliographic record
Abstract
The WOUND-Q is a patient-reported outcome measure for individuals with any type of chronic wound. This study aimed to identify patient and wound factors associated with the four WOUND-Q health-related quality of life (HRQL) scales: Life impact, Psychological, Sleep, and Social. Adults with a chronic wound were recruited internationally through clinical settings between August 2018 and May 2020, and through an online platform (i.e. Prolific) in September 2022. Multivariable linear regression analyses were conducted to identify factors significantly associated with the WOUND-Q scales. The assessments obtained were 1273, 1275, 706, and 1256 for the Life Impact, Psychological, Sleep, and Social scales, respectively. The mean age of participants was 55 (SD = 18) years; most (66%) had a single wound, and most (56%) wounds had lasted more than 6 months. The most common causes were trauma, surgery, and diabetic foot ulcer. Wound characteristics associated with worse scores on at least one of the scales were drainage, vacuum treatment, aetiologies (i.e. diabetic foot ulcer, trauma, other, multiple), duration (i.e. 10-11 months), having four or more wounds, smell, and sleep interference, while wound location different from the face or neck was associated with better scores (p < 0.05). Patient factors associated with worse scores included having diabetes or a comorbidity, whereas increasing age or male gender were associated with better scores (p < 0.05). Sleep disturbances had the largest negative influence on HRQL scores. This study identified factors affecting HRQL in individuals with chronic wounds. Understanding these associations can inform better management and treatment strategies to improve HRQL for these patients.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".