The efficacy of sequentially comprehensive treatment based on surgery in the treatment of keloids: a retrospective study
Bibliographic record
Abstract
Purpose The objective of this study is to investigate the clinical efficacy of sequentially comprehensive treatment based on surgery and to furnish clinical evidence for the management of keloids. Patients and methods The patients with keloids were retrospectively analyzed who underwent surgery-based sequentially comprehensive treatment at the Plastic Surgery Department of Shandong Provincial Hospital from January 2018 to August 2021. The recurrence rate and incidence of adverse reactions were explored for all the included patients. For patients who were followed up for more than 1 year, the clinical response rate was calculated, and the chi-square test was used to analyze which factors could influence clinical effectiveness. Binary logistic analysis was performed on the factors with statistical differences. For patients with a follow-up time of less than 1-year, paired t -test was used to evaluate their Vancouver Scar Scale (VSS) before and after treatment. Results A total of 67 patients with 80 keloids were included. The clinical response rate was 81.5% (44/54), the recurrence rate was 15.0% (12/80) and the adverse reaction rate was 4.5% (3/67). The clinical response rate of tumor-type keloids (95.8%) was higher than that of inflammatory-type (70.0%) with a significant difference ( P = 0.040). After treatment, the color, blood vessel distribution, softness, thickness, and VSS score were all decreased, and the difference was statistically significant ( P < 0.001). Conclusion The sequentially comprehensive treatment based on surgery has a significant curative effect, as well as a low recurrence rate and a low adverse effect rate. The type of keloid has a statistically significant effect on clinical efficacy, and tumor-type keloids are more suitable for sequentially comprehensive treatment based on surgery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| 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".