Effects of Preoperative Extracorporeal Shockwave Therapy on Scar Formation—A Pilot Study on 24 Subjects Undergoing Abdominoplasty Surgery
Bibliographic record
Abstract
OBJECTIVES: Extracorporeal shockwave therapy (ESWT) has been demonstrated as a feasible noninvasive method to improve wound healing. This effect was demonstrated to result from increased perfusion and angiogenesis due to systemic growth factor expression. We, therefore, hypothesized that preoperative ESWT reduces scar formation after surgery. METHODS: A prospective, controlled pilot study on 24 patients undergoing abdominoplasty was conducted and the efficacy of preoperative unfocused, low energy EWST was evaluated. The right and left half of the operative area were randomly allocated to ESWT or placebo treatment in intrapatient control design. At 6 and 12 weeks after surgery, scar formation was evaluated by 19 different scar parameters included in the patient, observer scar assessment, and the Vancouver scar scale. RESULTS: The overall rating of the Vancouver and POSAS scale with Mann-Whitney (MW) analysis revealed a clear trend favoring ESWT. At week 6, 7 of 19 parameters clearly favored ESWT (MW > 0.53). At week 12, 8 of 19 parameters clearly favored ESWT. The largest differences were observed in thickness and overall impression (Vancouver scar scale). CONCLUSIONS: ESWT presumably reduces scar formation and postoperative symptoms after abdominoplasty surgery. Further studies are required to confirm ESWT efficacy with statistical significance. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".