[The Place of Groin, Colson and McGregor Flaps in the Acute Care of Deep Burns to the Hand Dorsum : A Series of 6 Cases In Lille's Burn Centre].
Bibliographic record
Abstract
The acute management of deep burns to the dorsum of the hand and fingers represents a challenge for the reconstructive surgeon. The exposure of osteo-tendinous structures often requires flap coverage, in a context where loco-regional or free flaps are not always feasible. The aims of reconstruction are to preserve a maximum of digital length, provide supple tissue, obtain protective sensitivity, and achieve a functional hand at 1 year. We report here on a series of 8 deep burns to the dorsum of the hand. Six hands were covered by Colson abdominal flap-graft and two by pedicled inguinal flap. Four out of 6 patients were reviewed in consultation, 1 patient was lost to follow-up, and 1 patient died. Clinical evaluation was performed by a surgeon other than the operator. Functional results are highly variable. Coverage time varies according to lesion depth and patient severity. Flap weaning took place at an average of 30 days. DASH scores ranged from 17.5 to 93/100, with average to poor total active motion (TAM) scores. The aesthetic result was satisfactory, with a Vancouver score of 4.5/13 on average, and an overall patient opinion of 3.75/10 on the POSAS scale. For deep burns to the dorsum of the hand and fingers, local flaps are rarely possible, and loco-regional flaps are not feasible in cases of associated upper limb damage. For medium to large surface areas, pedicled inguinal flaps and pocketing are two reliable techniques. Nevertheless, they require relative immobilization of the upper limb, which leads to stiffness. The question of digital pinning in the intrinsic or straight position remains unresolved, and does not appear to prevent secondary deformities. There is also a learning curve for these two flaps, even though they are reputed to be easy to lift. McGregor's flap or pocketing can be weighed against free flaps. However, the operating time is long, the surgical technique is complex, and vascular damage is common in the burn patient population. Although there have been enormous technical advances since their descriptions, the pedicled inguinal flap and pocketing remain alternatives to be considered in the acute management of deep burns to the dorsum of the hand. In this presentation, we propose a surgical management algorithm to situate these two techniques in the plastic surgeon's therapeutic armament.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".