A prospective evaluation of methylene blue and gentian violet dressing for management of chronic wounds with local infection
Bibliographic record
Abstract
Abstract The objective of this prospective, non‐randomised study was to evaluate the performance of an antibacterial foam dressing containing methylene blue and gentian violet (Hydrofera Blue Classic dressing®) for the management of chronic wounds with local infection. Patients in this study were ≥18 years of age (n = 29), and each had at least one chronic wound ≥1 cm2 in size that showed signs of localised infection or critical colonisation but with good potential for healing based on clinical assessment. To all of these wounds, the dressing was applied and changed three times per week over the 4‐week study period. The primary endpoints of the study were: (i) changes in wound surface area measurement, (ii) changes in Pressure Ulcer Scale for Healing (PUSH) scores, (iii) changes in percent surface area of devitalised tissue (i.e., yellow slough or other necrotic tissue) and (iv) changes in clinical signs associated with localised wound infection/critical colonisation. Participants were evaluated at presentation (week 0 = baseline), week 2 and at week 4 (end of the study). The 29 patients completed the study, and at week 4, the following wound improvements were observed: (i) baseline mean wound surface area was significantly reduced by 42·5%, from 21·4 to 12·3 cm2 at week 4 (P = 0·005); (ii) baseline mean PUSH score decreased significantly from 13·3 to 10·7 at week 4 (P < 0·001); (iii) baseline mean wound coverage by devitalised tissue (%) was significantly reduced, from 52·6 % to 11·4% at week 4 (P < 0·001) and (iv) the mean UPPER and LOWER wound infection scores were reduced from 3·6 at baseline to 0·9 at week 4 (75%; P < 0.001). These results indicate that the Hydrofera Blue Classic dressing was effective at managing these chronic wounds and helped them progress onto a healing trajectory.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".