The Use of Silver Oxynitrate Wound Dressings in the Treatment of Chronic Wounds: A Feasibility Pilot Study
Bibliographic record
Abstract
OBJECTIVE: To evaluate the feasibility and effectiveness of a silver oxynitrate (Ag 7 NO 11 ) dressing on wound healing in patients with stalled chronic wounds. METHODS: A prospective pilot study was conducted to determine the feasibility and effect of using silver oxynitrate dressings within an outpatient setting in Alberta, Canada. A total of 23 patients (12 women and 11 men; mean age, 66.1 ± 13.8 years) with a chronic wound that failed to heal with conventional treatment were included in the study. Wound assessments including the Bates-Jensen Wound Assessment Tool, wound-related pain, wound size, and patient quality of life (QoL) were conducted at baseline, after dressing application for 1 and 2 weeks, and during 4- and 12-week follow-ups. RESULTS: Dressing application at 1 and 2 weeks improved patients' wound healing progression as measured through significantly decreased Bates-Jensen Wound Assessment Tool scores with a more than 10% decrease at 4- and 12-week follow-up ( P < .001). Pain ( P = .004), and QoL psyche subscore ( P = .008) significantly improved at 4-week follow-ups, although wound area, perimeter, and QoL body and everyday subscores were not significantly affected. Wound size was not significantly affected. CONCLUSIONS: The silver oxynitrate dressing may improve healing progression in patients with chronic wounds, enhance patient experience by reducing wound-related pain, and improve patients' mental well-being. Further studies are warranted to elucidate the effect of silver oxynitrate dressings on wound area, perimeter, and volume measurements.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".