Functional and Aesthetic Outcomes of the Anterolateral Thigh Flap in Reconstruction of Upper Limb Defects: A Systematic Review
Bibliographic record
Abstract
Background: Soft tissue coverage in the upper limb after trauma, burn injury, or tumour removal is a commonly addressed problem by the plastic surgeon. The anterolateral thigh flap (ALT) is recognized as a popular free flap option for covering various types of soft tissue defects due to its versatility. We aimed to assess the functional and aesthetic outcomes of the ALT flap for reconstruction of upper limb defects. Methods: Four electronic databases were searched (MEDLINE (PubMed), Scopus, Web of Science, and Cochrane) from inception to Feb 2021. Two reviewers independently extracted the data and performed risk assessment using the modified Downs and Black (MDB) quality assessment tool and the modified Newcastle Ottawa Scale for case series. Results: This review included seven studies for quantitative assessment. The eligible studies had 67 patients. Included studies had used a varied number of validated upper extremity functional scoring systems; the most commonly used score was QuickDASH with mean of 21.24, DASH score was 15.5. In regard to aesthetic outcome, an overall satisfactory result was reported. A secondary debulking procedure was performed in 7 patients. Conclusion: Further studies are recommended to ascertain the functional and aesthetic outcomes of the ALT free flap for upper limb defects, especially using standardized outcome scoring systems. This may be supplemented with a questionnaire that addresses common patient concerns (such as colour, contour, textile and hair growth) for the aesthetic outcome. Nevertheless, based on our review, the ALT flap may be a good reliable reconstructive option for upper limb defects with good functional outcome and satisfactory aesthetic results.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".