Nerve guide conduits, nerve transfers, and local and free muscle transfer in facial nerve palsy
Bibliographic record
Abstract
PURPOSE OF REVIEW: To highlight the recent literature on reinnervation options in the management of facial nerve paralysis using nerve conduits, and nerve and muscle transfers. RECENT FINDINGS: Engineering of natural and synthetic nerve conduits has progressed and many of these products are now available on the market. The use of the masseter nerve has become more popular recently as a choice in nerve transfer procedures due to various unique advantages. Various authors have recently described mimetic muscle reinnervation using more than one nerve transfer, as well as dual and triple innervation of free muscle transfer. SUMMARY: The ideal nerve conduit continues to be elusive, however significant progress has been made with many natural and synthetic materials and designs tested and introduced on the market. Many authors have modified the classic approaches in motor nerve transfer, as well as local and free muscle transfer, and described new ones, that aim to combine their advantages, particularly the simplification to a single stage and use of multiple reinnervation to the mimetic muscles. These advances are valuable to the reconstructive surgeon as powerful tools that can be tailored to the unique challenges of patients with facial nerve palsy looking for dynamic reanimation options.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".