Pain Management With Topical Ibuprofen in Partial-Thickness Burn Wounds and Effects on Wound Healing: A Prospective Randomized Clinical Study
Bibliographic record
Abstract
BACKGROUND: Pain management is important for patient comfort in the treatment of partial-thickness burn wounds. The topical application of ibuprofen provides analgesic and anti-inflammatory effects. PURPOSE: To evaluate the efficacy of ibuprofen-containing foam dressing in partial-thickness burns. METHODS: The study included 50 patients with superficial second-degree burn wounds. Ibuprofen-containing foam dressing was used in 25 patients and paraffin gauze dressing in 25 patients as controls. The visual analogue score (VAS) was evaluated 30 min after dressing. On the 90th day following wound healing, the Vancouver scar scale (VSS) was administered to the patients to evaluate healing and scar formation. RESULTS: The rate of wound healing significantly increased in the study (ibuprofen-containing foam dressing) group compared to control group (8.84±2.97 vs 11.32±4.39, P = 0.010), and the frequency of dressing change significantly decreased in the study group vs control group (1.36±0.49 vs 5.68±2.07, P = 0.000). The oral analgesic needs and VAS scores of the patients were also found to be statistically significantly lower in the study group (5.04 ± 2.44) than for the control group (8.64 ± 1.29, P = 0.000). In the evaluation of the VSS, the total score was lower in the study group, but no statistically significant difference was observed. CONCLUSION: The use of ibuprofen-containing foam dressing in patients with superficial second-degree burns eligible for outpatient follow-up provides effective pain management and increases patient comfort. It does not have a negative effect on wound healing. We consider that ibuprofen-containing foam dressing can be safely used in partial-thickness burns.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".