<p>Efficacy Of Silicone Gel In Reducing Scar Formation After Hypospadias Repair: A Randomized Placebo-Controlled Trial</p>
Bibliographic record
Abstract
BACKGROUND: Hypospadias is one of the most common congenital disorders of the urogenital system that is repaired by surgical method. Literature review shows that silicone gel is effective in preventing and improving hypertrophic scars after surgery. Thus, we conducted this study to evaluate the effect of silicone gel on scar reduction after surgical repair of hypospadias. MATERIALS AND METHODS: In this randomized double-blind clinical trial, 64 patients who had undergone surgical repair of hypospadias were divided into two groups: 32 patients in the intervention group (silicone gel) and 32 in the control group (placebo). Then, the patients in the silicone gel treatment group were treated twice per day for two months on the site of surgical wound, and the patients in the control group were treated with Vaseline twice per day for two months on the site of surgical wound, too. Scar characteristics (pigmentation, vascularity, pliability, and height) were recorded based on Vancouver's scars scale. Finally, the results of the two treatments on reduction of scars after surgical repair were compared between the two groups. Data were analyzed using SPSS-24. RESULTS: There were significant differences between the two groups in scar characteristics after surgical repair of hypospadias, such as vascularity, pliability, and height (P˂0.05); however, there was no significant difference in pigmentation (P>0.05). CONCLUSION: The results of this study showed that silicone gel had considerable effects on reduction of scars after surgical repair of hypospadias. However, further studies with larger sample size are recommended to confirm our conclusion.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".