Combined use of an ibuprofen-releasing foam dressing and silver dressing on infected leg ulcers
Bibliographic record
Abstract
OBJECTIVE: To investigate the effect and safety of an ibuprofen-releasing foam (Biatain-Ibu, Coloplast A/S) combined with an ionised silver-releasing wound contact layer (Physiotulle Ag, Coloplast A/S) on painful, infected venous leg ulcers. METHOD: This open non-comparative study involved 24 patients with painful, exuding, locally infected, and stalled venous leg ulcers. Persistent pain and pain at dressing change were monitored using a 11-point numerical box scale (NBS). The composition of the wound bed, the dressing combination's ability to absorb exudate and minimise leakage, ibuprofen content in the exudate, reduction in wound area and adverse effects were also recorded. RESULTS: Persistent wound pain decreased from a mean of 6.3 +/- 2.2 to 3.0 +/- 1.7 after 12 hours and remained low thereafter. Pain at dressing change also decreased and remained low. Forty-eight hours after the first dressing application, the mean concentration of ibuprofen in the wound exudate reached a constant level of 35 +/- 21 microg/ml. After 31 days, the relative wound area had reduced by 42%, with an associated decrease in fibrin and an increase in granulation tissue. The number of patients with wound malodour decreased from 37% to 4%. No serious adverse events were reported. CONCLUSION: The combined use of the ibuprofen-releasing foam dressing and silver-releasing contact layer reduced wound pain and promoted healing without compromising safety.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".