Less pain with Biatain–Ibu: initial findings from a randomised, controlled, double‐blind clinical investigation on painful venous leg ulcers
Bibliographic record
Abstract
Six out of 10 patients with chronic wounds suffer from persistent wound pain. A multinational and multicentre, randomised, double-blind clinical investigation of 122 patients compared two moist wound-healing dressings, a non adhesive foam dressing with ibuprofen (62 patients randomised to Biatain-Ibu non adhesive, Coloplast A/S) with a non adhesive foam without ibuprofen (60 to Biatain non adhesive). The ibuprofen-foam was regarded successful, if the pain relief on a 5-point verbal rating scale was higher than the comparator without compromising safety, including appropriate healing rate. Additional endpoints were change in persistent wound pain between dressing changes and pain at dressing change on days 1-5 and days 43-47. The primary response variable, persistent pain relief, was significantly higher in the ibuprofen-foam group compared with the comparator on days 1-5, with a quick onset of action (P < 0.05). The patients in the ibuprofen-foam group had a significant (P < 0.05) higher reduction in the persistent wound pain from baseline (40%) as the comparator (30%). Women reported less pain intensity than men, and pain intensity decreased with increasing age. In addition, pain intensity increased with increasing initial pain intensity and increasing wound size. Wound healing was similar in the ibuprofen-foam group to that of the comparator group. No difference in adverse events between placebo and local sustained release of low-dose ibuprofen was observed in this study. This study has demonstrated that the ibuprofen-foam dressing provided pain relief and reduced pain intensity without compromising healing or other safety parameters. The full report of this study will be published in Wound Repair and Regeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".