A Review of Perforator Flaps for Burn Scar Contractures of Joints
Bibliographic record
Abstract
OBJECTIVE: Perforator flaps are one possible surgical treatment for burn scar contractures; however, a review of evidence on this topic is lacking. METHODS: MEDLINE was searched for articles related to perforator flaps for burn contractures. Following title and abstract screen, full texts were searched to identify articles describing perforator flaps for burn scar joint contractures. Data were extracted and summarized descriptively. Only articles that contained ≥10 patients with burn scar contracture were considered. RESULTS: Two hundred forty-eight articles were identified, of which 17 met criteria for review. Of these, 16 were low-quality case series, while 1 was an open randomized controlled trial. In total, perforator flaps were performed on 339 patients (age range: 3-75 years), with the most common contracture locations being cervical (n = 218) and knee (n = 41). Nine of the 17 articles described a rehabilitation strategy. In general, functional outcomes were excellent, with the majority of patients experiencing return of normal joint range of motion and no recontracture. Compared to full-thickness skin grafts, perforator flaps showed greater improvements in joint range of motion. Cosmetically, perforator flaps were shown to have good color match with surrounding tissue, good contour around anatomical landmarks, and improved overall patient appearance. The most common complications were marginal flap necrosis (n = 26 patients) and venous congestion (n = 17 patients). CONCLUSIONS: Preliminary evidence from low-quality case series and 1 high-quality trial suggests perforator flaps may be successful for resurfacing released burn scar contractures; however, there is a need for additional trials comparing perforator flaps to other approaches.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.013 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".