Reduction of Bacterial Burden and Pain in Chronic Wounds Using a New Polyhexamethylene Biguanide Antimicrobial Foam Dressing-Clinical Trial Results
Bibliographic record
Abstract
OBJECTIVE: A randomized controlled trial to evaluate the effectiveness of a polyhexamethylene biguanide (PHMB) foam dressing compared with a similar non-antimicrobial foam for the treatment of superficial bacterial burden, wound-associated pain, and reduction in wound size. SETTING AND PARTICIPANTS: This study was conducted in 2 wound healing clinics-a university hospital-based clinic and a community-based clinic. Forty-five chronic wound subjects, stratified to either foot or leg ulcers, were followed for 5 weeks. METHODS: A multicenter, prospective, double-blind, pilot, randomized controlled clinical trial with 3 study visits (Weeks 0, 2, 4) documented pain and local wound characteristics using NERDS and STONEES clinical criteria to determine superficial bacterial damage or deep/surrounding infection. RESULTS: The use of PHMB foam dressing was a significant predictor of reduced wound superficial bacterial burden (P = .016) at week 4 as compared with the foam alone. Pain reduction was also statistically significant at week 2 (P = .0006) and at week 4 (P = .02) in favor of the PHMB foam dressings. Polymicrobial organisms were recovered at week 4 in 5.3% in the PHMB foam dressing group versus 33% in the control group (P = .04). Subjects randomized to the PHMB foam dressing had a 35% median reduction in wound size by week 4, compared with 28% in the control group. CONCLUSIONS: PHMB foam dressing successfully reduced chronic wound pain and bacterial burden.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".