Repair of Ocular-Oral Synkinesis of Postfacial Paralysis Using Cross-Facial Nerve Grafting
Bibliographic record
Abstract
We present the surgical techniques and results of cross-facial nerve grafting that have been developed in the repair of ocular-oral synkinesis after facial paralysis. Eleven patients with ocular-oral synkinesis after facial paralysis underwent the cross-facial nerve grafting with facial nerve transposition at a tertiary academic hospital between 2003 and 2009. The patient selection for the study was based on the degree of disfigurement and facial function parameter rating using the Toronto Facial Grading System. The procedures used were surgeries done in two stages. All cases were followed up for 2 months to 6 years after the second surgery. The degree of improvement was evaluated at 6 to 7 months after the procedures. Six of the patients were followed up for more than 2 years after the stage-two surgery and demonstrated significant reduction in the ocular-oral synkinetic movements. The Toronto Facial Grading System scores from the postoperative follow-ups increased an average of 16 points (28%), and the patients had achieved symmetrical facial movement. We concluded that cross-facial nerve grafting with facial nerve branch transposition is effective and can be considered as an option for the repair of ocular-oral synkinesis after facial paralysis in select patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; 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".