Negative pressure wound therapy as a definitive treatment for upper extremity wound defects: A systematic review
Bibliographic record
Abstract
Negative pressure wound therapy (NPWT) represents one of the many solutions for complex wounds of the upper extremity. The goal of this study was to investigate the most common indications for definitive treatment of wound defects in the upper extremity with NPWT and to report revision surgery outcomes after its use. A systematic review of the literature was performed. The following keywords and their combinations were used: "upper extremity," "arm," "forearm," "wrist," "hand," "finger" AND "negative-pressure wound therapy," "VAC therapy," "vacuum assisted closure." A total of 45 articles were included, regrouping 404 cases of NPWT in the upper extremity. The forearm was involved in 53% of cases, followed by hand (36%), fingers (10%), and arm (1%). Seventeen different indications were cited, the most common of which were radial forearm flap reconstruction (23%), burn wounds (18%), and compartment syndromes (17%). Of the cases, 90% did not require any subsequent surgical procedure, as opposed to 6% considered partial failures requiring minor revisions and 4% total failures requiring major revisions. Closure of radial forearm flap donor site required the most revision procedures when treated with NPWT. NPWT can be used for several indications pertaining to the reconstruction of the upper extremity. Positive outcomes as a definitive treatment are demonstrated in this systematic review, which reaffirms NPWT as a potent tool for reconstructive endeavours.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".