The clinical efficacy of single-hole punch excision combined with intralesional steroid injection for nodular keloid treatment: a self-controlled trial
Bibliographic record
Abstract
Abstract There are many methods to treat keloid, including various excision operations, laser, injection and radiotherapy. However, few studies have explored the effectiveness of single-hole punch excision in keloid treatment. This study aimed to investigate the efficacy and safety of lateral punch excision combined with intralesional steroid injection for keloid treatment through self-control trial. In this self-controlled trial, 50 patients meet the diagnosis of nodular keloid, and try to choose left–right symmetrical control, one skin lesion in the control group (50 skin lesionsin total) and the other in the observation group (50 skin lesions in total).The keloids in the treatment group were initially treated with punch excision combined with intralesional steroid injection, followed by injection treatment alone. Keloids in the control group received intralesional steroid injection alone. The Vancouver Scar Scale (VSS) of the keloid before and after the punch excision was evaluated; the keloid scores at different time points and the number of injection treatments required in both groups were compared, and adverse reactions were observed. The effective rate of the observation group was 86.0%, which was significantly higher than that of the control group (66.0%), and the recurrence rate of 22% was lower than that of the control group (χ 2 = 4.141,63417), all of which were statistically significant (all P < 0.05). At the end of treatment, the VSS and total injection times in the observation group were significantly lower than those in the control group (t = 5.900,3.361), with statistical significance ( P < 0.01). The combination of single-hole punch excision and intralesional steroid injection is an effective method to treat multiple nodular keloids, shortening the treatment course of tralesional steroid injection without obvious adverse reactions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".