Optimal site for facial nerve transection and neurorrhaphy: A randomized prospective animal study
Bibliographic record
Abstract
BACKGROUND: Since the first facial allograft transplantation was performed, several institutions have performed the procedure with the main objectives being restoration of the aesthetic appearance and expressive function of the face. The optimal location to transect the facial nerve during flap harvest in transplantation to preserve facial movement function is currently unknown. There are currently two primary methods to perform facial nerve neurorrhaphy between the donor and recipient-one protocol involves transection and repair of the facial nerve at the main trunk while the another protocol advocates for the neurorrhaphy to be performed distally at the main branches. The purpose of this study is to establish the optimal location for transection and repair of the facial nerve to optimize functional recovery of facial movement. METHODS: A prospective randomized controlled trial using a rat model was performed. Two groups of 12 rats underwent facial nerve transection and subsequent repair either at the main trunk of the nerve (group 1) or 2 cm distally, at the main bifurcation (group 2). Primary outcome of nerve functional recovery was measured using a previously validated laser curtain model, which measured amplitude of whisking at 2, 4, and 6 post-operatively. The deflection of the laser curtain sent a digital signal that was interpreted by central computer software. RESULTS: At week 2 post-nerve surgery, the average amplitude observed for group 1 and 2 was 4.4 and 10.8 degrees, respectively. At week 4, group 1 showed improvement with an average amplitude of 9.7 degrees, while group 2 displayed an average of 10.2 degrees. The week 6 results showed the greatest improvement from baseline for group 1. Group 1 and 2 had average amplitudes of 17.2 and 6.9 degrees, respectively. There was no statistically significant difference between the two groups at 2, 4, and 6 weeks after facial nerve surgery (p > 0.05). CONCLUSIONS: We found no statistical difference between these two locations of nerve repair using identical methods. Therefore, the authors recommend a single versus multiple nerve repair technique. This finding has potential implications for future facial allograft transplantations and at minimum necessitates further study with long-term follow-up data.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".