Distally based posterior interosseous adipofascial flap with delayed skin grafting for soft-tissue reconstruction of the dorsal hand
Bibliographic record
Abstract
Objective To investigate the clinical results of reverse interosseous adipofascial flap with delayed skin grafting in the reconstruction of defects on the dorsal hand. Methods From March 2012 to May 2014, 16 patients with soft tissue defects on the dorsum of the hand were treated dorsal interosseous adipofascial flap in emergency setting. The size of the flaps ranged from 5 cm×4 cm to 10 cm×6 cm. The donor site at the forearm was closed directly. Seven days later, the fascial flap was covered with a full-thickness skin graft taken from the groin area. Vancouver Scar Scale was applied to assess the donor site scar. Five-point Likert scale was used to evaluate the appearance of the recipient site. Results One patient had partial loss of the flap involving 5% of the area at the distal end. All the other flaps survived completely. The skin grafts took well in all 16 patients. The duration of postoperative follow-up ranged from 6 to 12 months, with an average of 8 months. The texture and color of the skin graft were good, and the esthetic result was satisfactory. The mean score of Vancouver Scar Scale was 0.8. The mean score of Five-point Likert scale was 17. Conclusion The described adipofascial flap transfer with delayed skin graft is rather easy to perform without causing significant functional and aesthetic deficits to the donor site. It is a good method for repairing defects of the dorsal hand. Key words: Hand injuries; Treatment ontcome; Adipofascial flap; Posterior interosseous artery
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".