Timing of nanocrystalline silver-based dressing application: a retrospective single-center pediatric cohort study
Bibliographic record
Abstract
Recent evidence has demonstrated that silver has anti-inflammatory properties that are independent of the known antimicrobial ones. In our current model of care, nonadherent, nonsilver dressings are applied for acute presentations of pediatric partial-thickness burn injuries. The wounds are re-assessed after the progression phase (48-72 hours after injury), and silver dressings are applied. However, when logistical obstacles prevent re-assessment within the 48- to 72-hour window, nanocrystalline silver-based dressings are applied on presentation. The objective of this study was to test our model of care. We hypothesized that immediate application (<24 hours after injury) of nanocrystalline silver-based dressings would reduce surgical interventions. This was a retrospective single-center cohort study. All patients <18 years old treated at a pediatric burn center for acute partial-thickness burn injuries between January 1, 2020, and December 31, 2021, were included. Multivariable logistic regression was used to compare surgical treatment rates between patients with different timing of nanocrystalline silver-based dressing application. Four hundred and seventy-six patients were included for analysis. One hundred and four patients (21.8%) had nanocrystalline silver-based dressings and 372 (78.2%) had non-silver, non-adherent dressings applied within 24 hours of injury. Multivariable logistic regression identified 3 statistically significant variables as predictors for surgical treatment: age (odds ratio [OR] = 1.14, 95% CI [1.06-1.23]), TBSA (OR = 1.15, 95% CI [1.06-1.25]), and burns to buttocks/lower extremity (OR = 2.39, 95% CI [1.26-4.53]). Immediate (<24 hours after injury) application of nanocrystalline silver-based dressings does not affect surgical treatment rate in pediatric patients with partial-thickness burns.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".