Free thoracodorsal artery polyfoliate perforator flaps for repairing multiple soft tissue defects in the hand
Bibliographic record
Abstract
BACKGROUND: Hand injury is commonly associated with multiple soft tissue defects. Polyfoliate flaps grafting is the optimal approach for multiple wounds.The feasibility of clinical using of free thoracodorsal artery polyfoliate perforator flaps for repairing multiple soft tissue defects in the hand needs to be confirmed in clinical practice. METHODS: Fifteen patients with hand soft tissue defects that were repaired using free thoracodorsal artery polyfoliate perforator flaps from January 2015 to February 2018 was retrospectively analysed. The survival rate, the operative time, the appearance and sensory recovery of the flaps, and hand function were evaluated. RESULTS: The flaps of all 15 patients survived. Vascular crisis occurred in one patient, and the flap was saved after exploratory operation. The 15 patients were followed up for 12-26 months. Sensation in the flaps was partially recovered in all 15 patients. The wound in the donor area was closed directly with sutures. Mean score of scars at the donor site were assessed using the modified Vancouver scar scale (VSS) was 2.7. A puffed appearance in the recipient area was noted in four patients. To obtain a more satisfactory appearance, revision of the flap was performed once in these four patients. The Total Active Movement (TAM) evaluation system was used to assess the results, which were considered excellent in seven patients, good in six patients, fair in two patients, and poor in none of the patients. Ten of the 15 patients returned to their primary jobs. CONCLUSION: Free thoracodorsal artery polyfoliate perforator flaps are appropriate for repairing multiple soft tissue defects in the hand, offer a satisfactory appearance, require a short operative time, and have little impact on the function and aesthetics of the donor site.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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".