Functional Outcomes of Tongue Reconstruction After Cancer Extirpation in Different Flaps: Pedicled Versus Free Flaps: A Systematic Review
Bibliographic record
Abstract
Background: Tongue reconstruction poses significant challenges, involving either pedicle or free flaps, with variations arising from the remnant native tongue tissue or complete neotongue formation. Distinct differences exist between oral tongue and posterior-tongue reconstruction, and the impact of flap nature on functional outcomes remains inconclusive. This study aimed to identify the best flap options for tongue resections based on functional outcomes, help surgeons predict posttreatment quality of life, and explore standardized methods for evaluating swallowing, tongue mobility, speech, and quality of life. Methods: A systematic search of Embase, PubMed, Cochrane Library, and Web of Science identified studies on functional outcomes after tongue reconstruction with flaps. From 782 articles, 42 were included in the review. Four independent researchers assessed bias risk using the Critical Appraisal Skills Program tool. Results: The submental flap was the most common pedicle flap, whereas free flaps such as the anterolateral thigh and radial forearm were frequently used. Functional outcomes were influenced by resection extent, reconstruction type, and postoperative radiotherapy. Neo-tongue reconstruction differed functionally from oral tongue reconstruction. Sensory or motor-innervated flaps showed better swallowing outcomes, but speech results were similar between pedicle and free flaps. Conclusions: The study's findings are limited by inconsistent data, retrospective designs, and lack of standardized methods, necessitating cautious interpretation. Free flaps consistently offer better functional outcomes for tongue reconstruction, improving over time with rehabilitation. Free flaps tailored to defect size are preferred over pedicle flaps for superior results, regardless of reconstruction site.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".