Impact of Skin Grafting of Venous Leg Ulcers on Functional Status and Pain
Bibliographic record
Abstract
BACKGROUND: Disability and pain were assessed in patients with venous leg ulcers treated with split-thickness skin grafts to evaluate to what extent skin grafting improves functional status in this population. METHODS: A prospective, nonrandomized, multicenter case-control study was conducted from July 2008 to December 2010 in two hospitals in Brazil. One hundred patients with venous leg ulcers were divided into two treatment groups of 50 patients each: the control group (conservative treatment) and the surgery group (skin grafting). Patients were assessed at baseline (day 0) and on days 30, 90, and 180. Disability was measured with the Disability Index of the Health Assessment Questionnaire (HAQ-DI). The visual analog scale (VAS) and McGill Pain Questionnaire (MPQ) were used to assess pain. RESULTS: Surgery group patients reported significantly lower (p = 0.0001) overall HAQ-DI scores (lower disability levels) 180 days postoperatively (HAQ-DI = 0.18) compared with baseline (HAQ-DI = 2.65); mean overall HAQ-DI scores for control patients was 1.70 on day 180, with a significant difference between groups (p = 0.0001). The surgery group showed significant improvement on all HAQ-DI categories and reported significantly lower pain intensity (VAS pain scores) on days 30, 90, and 180 compared with controls (p = 0.0001). The MPQ was used to assess the sensory, affective, evaluative, and miscellaneous dimensions of pain in the two groups; there were significant differences between groups on days 30, 90, and 180 (p = 0.0001). CONCLUSIONS: Patients with venous leg ulcers treated with split-thickness skin grafts showed improvement in functional status compared with controls.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".