Conservative Management of Wound Dehiscence Following Pediatric Cavus Foot Surgery
Bibliographic record
Abstract
UNLABELLED: Cavus foot surgeries are relatively common procedures in pediatric orthopedics. Following surgery, the tensile forces exerted on the wound by the newly corrected foot may hinder soft tissue healing and lead to wound dehiscence. Treatments including skin grafting and other plastic surgery procedures have been described in order to manage this complication. However, the effectiveness of conservative treatment regimens in cases of large dehiscence of these wounds has not yet been reported. METHODS: The charts of 7 patients between the ages of 7 and 19 who had surgical correction of severe cavus deformity and who developed wound dehiscence postoperatively were reviewed. All patients were treated conservatively with regular cleaning with chlorhexedine and application of different ointments and dressings along with surgical debridements. Three patients also received antibiotics. The primary outcome was wound healing as documented by clinical notes and photographs. RESULTS: The treatment was successful in producing the desired outcome in all cases with no other systemic or wound complications developing. Complete wound healing was obtained within a median time of 6 months and 5 days of treatment without the need for skin grafting or other plastic surgery procedures. CONCLUSIONS: In pediatric patients with wound dehiscence postcavus foot surgery, conservative management with minimal surgical debridement and regular cleaning and dressing of the wound is a viable treatment option that has been shown to be effective in 7 cases. It should be considered in such patients before proceeding to more invasive surgical treatment.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".