One or two venous pedicles by anastomoses for free flaps in reconstruction of the lower extremity: A systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Microsurgical free tissue transfers are a mainstay of lower extremity reconstruction. Despite being a reliable source of soft tissue, complications do arise. Venous congestion is among the most common causes of flap failure in lower extremity reconstruction, an issue that is attributed to venous stasis and impaired venous return in this region. There remains significant debate whether dual venous drainage improves outcomes. The aim of this study was thus to compare one versus two venous anastomoses in lower limb free flap reconstruction. METHODS: A systematic review of Medline, EMBASE, EBSCO CINAHL, SCOPUS, Proquest Dissertations and Theses Global, Cochrane Library, and PROSPERO from inception to May 20, 2020, was conducted. Two independent reviewers screened titles and extracted data. Our primary outcome was total free flap necrosis. Secondary outcomes were partial flap necrosis, minor complications, flap reoperation, venous thrombosis, and amputation. Methodological quality was assessed using the MINORS criteria and level of evidence. RESULTS: Three-hundred and fourteen unique titles were identified. All studies were level VI evidence and had a mean MINORS score of 16.1/24. Seven studies (comprising 1499 patients, 910 single venous anastomoses, and 579 double venous anastomoses) met criteria for inclusion. The mean (SD) patient age was 46.5 (7.1) years. Double venous anastomoses did not reduce the rate of minor complications, flap takeback, venous thrombosis, total flap necrosis, or partial flap necrosis when compared to a single vein (all p > .05). CONCLUSION: In microvascular lower extremity reconstruction, two venous anastomoses did not reduce the rate of minor or major complications.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.034 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".