Super-drained distally based neurofasciocutaneous sural flap: a case series and review of literature.
Bibliographic record
Abstract
OBJECTIVE: The distally based neurofasciocutaneous sural flap is central to the armamentarium for the reconstruction of leg's distal third, ankle, and hindfoot. Despite the use of adapted techniques aimed at increasing the flap's reliability, venous congestion remains a frequently encountered problem. We present a venous super-drainage technique used by the senior author to reduce venous congestion and improve flap reliability when harvesting larger flaps. METHODS: A retrospective chart review, from January 2002 to October 2008, at 2 tertiary care centers, was conducted on all cases of inferior limb reconstruction with reverse sural flaps on defects greater than 10 × 5 cm. In addition, a literature review was carried out to examine the average sural flap surface area and reported complications published from 1992 to 2012. We then compared our results with those published in the literature. RESULTS: A total of 15 flaps were identified. Mean flap dimensions were 14 × 8.5 cm (mean area = 115.27 cm(2); 95% confidence interval, 99.28-131.26). None of the flaps developed complications (arterial or venous insufficiency, partial/complete necrosis). The average flap surface area in the literature is 55.08 cm(2), with a 22% rate of total complications. We harvested significantly larger flaps (P < .001) with a significantly lower total complication rate (P < .05) when compared with that reported in the literature. CONCLUSION: Anastomosing the proximal end of the lesser saphenous vein with a vein at the defect site improves venous outflow, effectively reducing the incidence of venous congestion, increases the potential flap size, and improves reliability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".