Safety of Silver Dressings in Infants; a Systematic Scoping Review
Bibliographic record
Abstract
Silver-based dressings are used to reduce infection risk and optimize conditions for wound healing. They are widely used in the management of burns and other complex wounds. However, reports of elevated serum silver and concern over systemic toxicity have meant that their use in young children has been questioned. The aim of the current study was to map the literature relating to the use of silver-based dressings in children under 1 year of age. A systematic scoping review was conducted according to the methodology described by the Joanna Briggs Institute. Sources were identified from major medical databases as well as the gray literature. Inclusion criteria were the use of silver-based dressing in children under 1 year of age. Outcomes of interest were complications or adverse events attributed to silver-based dressings and elevated serum silver levels. A total of 599 sources were identified through the search strategy, with 110 included for review. Complications were described in 31 sources, with the most frequent being wound infection. No cases of argyria, kernicterus, or methemoglobinemia were reported. Six sources documented elevated serum silver levels in infants but none reported adverse events related to this. On the basis of current evidence, we suggest reserving silver dressings in infants under 1 for wounds that are at high risk of infection. Wound area and duration of treatment should be considered when assessing the risk of systemic absorption of silver. Standardized data collection and recording of complications and adverse events is recommended to better inform future clinical decision-making.
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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 | 0.011 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| 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".