Utilization of a Newly Designed Asymmetric Dorsal Gull Wing Flap for the Treatment of Postoperative Web Creep After Syndactyly Surgery
Bibliographic record
Abstract
BACKGROUND: Web creep is the most common long-term complication requiring revision after syndactyly surgery; however, few methods have been reported. The aim of this study was to introduce a newly designed asymmetric dorsal gull wing flap to reconstruct web for the postoperative web creep. METHODS: A retrospective analysis was performed for 20 patients from January 2016 to May 2019. Sex, age, original malformations, original surgical procedure, complications, time between the 2 operations, operation records, preoperative and postoperative photographs, and Withey score were reviewed. RESULTS: Eleven boys and 9 girls with average age of 60.65 ± 44.76 months underwent revision. Twenty-nine web spaces were affected (web creep, 12 cases; web creep and scar contracture, 17 cases). The original surgical procedure consisted of syndactyly separation in 15 cases, syndactyly separation with a full-thickness skin graft in 5 cases. There was 1 case of postoperative infection. All patients received an asymmetric dorsal gull wing flap and a zigzag incision, 15 patients received an additional full-thickness skin graft. The average time interval between the 2 operations was 34.60 ± 35.94 months. The follow-up time was 34.30 ± 20.73 months. No complications were noted, none of the patients redeveloped web creep. The median values for web creep, flexion-extension deformity, total Withey scores in the postoperative period were significantly lower than the preoperative values. The appearance and function of all digits were good. CONCLUSIONS: The asymmetric dorsal gull wing flap is a good choice for web reconstruction when web creep is caused by syndactyly surgery.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".