Reconstruction of Composite Soft Tissue Defect in the Distal Finger Using Partial Toenail Flap Transfer
Bibliographic record
Abstract
OBJECTIVE: Composite tissue loss involving the distal finger pulp and the nail is a common but challenging finger injury to restore. This study introduces a reconstruction procedure for a distal finger pulp and nail defect using a partial toenail flap transfer. METHODS: Twenty digits, including 16 thumbs, two index fingers, and two middle fingers, with composite soft tissue defects were treated with a partial toenail flap transfer from October 2015 to January 2020. Shortening revision of the great toe phalanx, a V-Y advancement flap of the toe pulp, and a local pedicle flap from a second toe transfer were used to cover the donor sites, and no skin grafts were required. Functionality was evaluated using the validated Spanish version of the Quick-DASH scale. The aesthetics of both the reconstructed and donor sites were evaluated using the Vancouver Scar Scale (VSS). The static two-point discrimination (2-PD) of the finger pulp was used as a measure of tactile agnosia. RESULTS: All donor site wounds healed well. The average follow-up time was 23.6 months (6-39 months). The mean Quick-DASH functional score was 7.1. The VSS scores were 4.02 ± 0.29 and 4.00 ± 0.38 for the reconstructed and donor sites, respectively. The static 2-PD of finger pulp was 4.5 ± 0.76 mm. The patients were satisfied with finger motion, sensory function, and aesthetic contour. CONCLUSIONS: Partial toenail flap transfer is the recommended treatment to regain motion, sensation, function, and a satisfactory aesthetic appearance when considering repairing a composite soft tissue distal finger defect with accompanying loss of the perionychium, particularly in the thumb, index finger, or middle finger.
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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 | 0.001 |
| 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".