A Randomized Controlled Trial to Evaluate an Antimicrobial Dressing with Silver Alginate Powder for the Management of Chronic Wounds Exhibiting Signs of Critical Colonization
Bibliographic record
Abstract
OBJECTIVE: The primary objective of this study was to evaluate if a topical silver dressing that consists of silver alginate powder is effective in managing chronic wounds that exhibit signs of critical colonization and promoting wound healing. METHOD: This was a prospective, open-label, 4-week randomized controlled trial. The primary end points of the study were changes in signs associated with critical colonization and in wound surface areas. All subjects were evaluated at weeks 0, 2, and 4 at the end of the study. SUBJECT AND SETTINGS: Participants between 18 and 85 years of age were recruited from 2 wound care clinics in Canada. The study was reviewed and approved by research ethics boards. DATA ANALYSIS: Analyses of this study were carried out based on intent-to-treat principle; t tests were used to determine if the means were statistically different between treatment groups. RESULTS: Thirty-four subjects participated and completed in the study. In the control group, the mean infection checklist score was 2.2 at baseline and 2.3 at week 4 (t9 = -0.36, P = .73). In the silver alginate powder group, the infection score reduced from 3.3 at baseline to 1.3 at week 4; the result was significant (t23 = 7.62, P < .00). The difference in average surface reduction over time between the 2 groups was statistically significant (t32 = 3.56, P < .001). Subjects randomized to the silver group achieved a greater surface reduction than those who were randomized to the use of foam dressing as the control. CONCLUSION: Silver alginate powder is an effective treatment option for wounds with increased bacterial burden.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".