Quality of life in patients with diabetic foot ulcers: validation of the Cardiff Wound Impact Schedule in a Canadian population
Bibliographic record
Abstract
The purpose of this study was to evaluate and validate the Cardiff Wound Impact Schedule (CWIS), a disease-specific quality-of-life measure, in a diabetic foot ulcer (DFU) population. Patients with DFUs have restrictions as part of their treatment and rehabilitation, which can affect health-related quality of life (HRQoL). Because of the high number of comorbidities experienced in diabetes, a disease-specific quality-of-life measure is needed to best assess the affect of a foot ulcer on HRQoL. Patients with DFUs completed the CWIS and a World Health Organization generic quality-of-life questionnaire. Validity was assessed by comparing domains of the questionnaires. Patients were categorised using the University of Texas wound classification system. Mean CWIS scores were compared between categories to assess the questionnaire's ability to differentiate wound severity. Patients with open ulcers scored significantly lower on the CWIS than those with healed ulcers. Correlations between questionnaire domains were as follows: Social Life with Social Functioning (r = 0·641, P < 0·001); Well-Being with General Health (r = 0·533, P < 0·01); Physical Symptoms and Daily Living with Physical Functioning (r = 0·631, P < 0·01) and Health-Related Quality of Life with Vitality (r = 0·425, P < 0·01). However, there was no significant difference in mean CWIS scores between categories of wound severity. We have demonstrated the ability of the CWIS in assessing HRQoL in a DFU population and its ability to differentiate between healed and non healed states.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".