Canadian Postoperative Dependency Protocols Following Lower Limb Microvascular Reconstruction: A National Survey and Literature Review
Bibliographic record
Abstract
INTRODUCTION: Microsurgical free tissue transfer for lower limb reconstruction presents unique challenges in the postoperative period where dependency promotes interstitial fluid diffusion and reduced tissue perfusion. Management of flap edema, venous congestion, and ischaemic conditioning is critical for flap survival. Little evidence exists to guide postoperative protocols in the initiation and progression of lower extremity dangle, monitoring, and anticoagulation. We aim to describe current trends for postoperative dependency protocols by surveying Canadian microsurgeons. METHODS: Plastic surgeons performing lower limb microvascular reconstruction at Fellow of The Royal College of Surgeons of Canada approved teaching institutions were administered a 17-question anonymous electronic survey. A literature review was conducted to identify protocols and consensus opinions in other jurisdictions. RESULTS: All respondents (n = 16) monitored flaps clinically, with conventional Doppler used by 13 respondents. Anticoagulation was employed by 15 of 16 respondents, and 9 of 16 used 2 or more agents. The most common agents were aspirin, followed by low-molecular-weight heparin. Significant variability existed in dangling protocols. Dependency was initiated at postoperative day (POD) 3 to 10 (mean POD: 6 ± 1.64 standard deviation), with intervals ranging from 5 to 20 minutes and frequencies ranging from 1 to 6 times per day. Nearly half allowed both increasing duration and frequency of dependency. Flap success rates were above 90%, and the median length of stay was 10 to 12 days. CONCLUSION: While flap success rates across the country are similar, no consensus exists for postoperative dependency protocols amongst Canadian microsurgeons. Prospective randomised controlled trials are warranted to evaluate early aggressive dependency protocols to reduce length of stay and cost.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.015 | 0.034 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".