Management of Hypertrophic Burn Scar: A Comparison between the Efficacy of Exercise-Physiotherapy and Pressure Garment-Silicone on Hypertrophic Scar
Bibliographic record
Abstract
PURPOSE: Our study aims to investigate the effectiveness of other treatment methods for burn related scarring and to determine the possibility of their routine administration in similar clinical settings. METHODS: Through a prospective study, 66 patients were enrolled to receive either the conventional pressure garment therapy (PGT) and Silicone (control group) or exercise and physiotherapy (case group). Patients were visited regularly to be examined for the status of their scars' regression, limbs' dysfunction, and joint motion. Then, these two groups were compared to determine the efficacy of exercise and physiotherapy as an alternative to the conventional treatment with PGT. RESULTS: After about 20 months follow-up, decreased articular range of motion (ROM) was: 16 (51.5%) cases compared to 5 (15%) of controls had mild, 11 (35.5%) of the cases compared to 13 (39.5%) of the controls had moderate; and 4 (13%) of the cases compared to 15 (45.5%) of the controls had severe decreased ROM which revealed statistically significant difference (P<0.01). At the same time, Vancouver Scar Scale score was: 15 (48%) of the cases and 6 (18%) of the controls had mild Scar Scale, 12 (39%) of the cases and 14 (42.5%) of the controls had moderate score and 4 (3%) of the cases and 13 (39.5%) of the controls had severe score which revealed a statistically significant difference (P<0.05). CONCLUSION: Our study showed that physical therapy andexercise are more effective than PGT, in management of burn hypertrophic scar, hence could be an alternative in cases that conventional therapy cannot be used for any reason.
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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) | 0.000 | 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) | 0.001 | 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".