Minimizing donor site morbidity in free fibula flap reconstruction: A comprehensive systematic review of outcomes and strategies
Bibliographic record
Abstract
This paper presents a systematic review of donor site morbidity in free fibula flap (FFF) reconstruction, one of the fundamental options for mandibular reconstruction and extremity reconstruction, to define novel methods to reduce complications and maximize patient outcomes and quality of life. A systematic literature review with the implementation of PRISMA followed and included the combination of the following keywords: free fibula flap, donor site morbidity, and surgical strategies in PubMed, Embase, Scopus, Cochrane Library, and Web of Science (20002025). Studies that had previously undergone peer review, clinical trials, or cohort studies with a minimum of 10 patients were included in the study. Case reports were excluded, as were studies that were not in English. The extraction of data included morbidity rates (such as wound dehiscence, infection, and chronic pain), surgical methods, and demographics. The quality of the data was evaluated using the Newcastle-Ottawa Scale and the ROBINS-I tool. Qualitative synthesis and, where possible, quantitative meta-analysis were carried out with subgroup analysis based on patient age, site of reconstruction, and method of closure. Available evidence suggests that wound complications (10 to 30 percent), functional disability (e.g., ankle instability, 5 to 20 percent), and chronic pain (5 to 15 percent) are commonly reported morbidities. These novel discoveries, includes perforator-sparing techniques, endoscopic harvesting, and biomaterials (such as collagen matrices), have shown potential in reducing the rates of complications to over 25%. Custom surgical plans and new technologies, such as 3D-printed guides and regenerative medicine, are effective ways to alleviate donor site morbidity, which necessitates their inclusion in practice to maximize FFF outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".