Therapeutic efficacy and influencing factors of 5-fluorouracil combined with ultra-pulsed fractional carbon dioxide laser treatment for hypertrophic scars in burn patients
Bibliographic record
Abstract
Background Laser therapy is widely used in scar repair, and the use of 5-fluorouracil (5-FU) as an adjuvant treatment has also attracted attention. This study aimed to compare the therapeutic efficacy of 5-FU combined with ultra-pulsed fractional carbon dioxide laser (UFCL) treatment and UFCL treatment alone for hypertrophic scars after burns, and to analyse influencing factors to provide evidence for clinical practice.Methods A total of 150 patients with hypertrophic scars from burns were randomly divided into an observation group (OG) and a control group (CG). Assessments were based on the Vancouver scar scale (VSS), patient scar assessment scale (PSAS), and records of adverse reactions (AR).Results There were no statistically significant differences between the two groups in terms of burn causes, disease duration, hypertrophic scar formation time, and wound healing time (P > 0.05). After treatment, the OG showed greater improvements in VSS and PSAS scores compared to the CG. In terms of clinical efficacy, 11 cases in the OG achieved complete recovery, and 42 cases showed visible improvement, with a total effective rate of 93.33%, higher than that of the CG. The incidence of AR in the OG (6.67%) was lower as against the CG. Multivariate regression analysis indicated that advanced age, longer disease duration, and higher pre-treatment VSS scores were negatively correlated with treatment effectiveness (P < 0.05).Conclusion The combination of 5-FU and UFCL treatment is significantly more effective than laser treatment alone. Risk factors affecting clinical efficacy include advanced age, longer disease duration, and higher pre-treatment VSS scores.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".