Objective Outcomes of Minimally Invasive Temporalis Tendon Transfer for Prolonged Complete Facial Paralysis
Bibliographic record
Abstract
OBJECTIVES: We describe an approach to reanimation of complete, prolonged facial paralysis using minimally invasive temporalis tendon transfer (MIT3) by the melolabial or transoral approach. Objective outcome measures are evaluated based on symmetry, and grading of preoperative/post-operative results and the scar at the melolabial fold. STUDY DESIGN: Retrospective cohort study. METHODS: Twenty-five patients undergoing the MIT3 technique were studied. Photographic analysis was used to determine the percentage of difference between the 2 sides (symmetry). Using the Delphi method to achieve consensus, a panel of experts graded pre/post-operative photos using the Terzis' Facial Grading System and a 1 to 10 Likert-type scale and the melolabial scar using the Beausang Scar Scale. RESULTS: Percentage of difference (symmetry) with smiling improved from 18.6% ± 1.5% (mean ± standard error of the mean [SEM]) preoperatively to 5.0 ± 0.9% (mean ± SEM) post-operatively. Expert grading by the Terzis system showed improvement post-operatively (mean 3.7/5; median 3.6/5) versus preoperatively (mean 1.5/5; median 1.2/5). Perceived improvement was also largely favourable (mean 8.1/10; median 8.0/10). Melolabial scar grading was favourable in terms of colour (mean 1.53/4), surface character (mean 1.05/2), contour (mean 1.60/4), and distortion (mean 1.74/4). CONCLUSIONS: The MIT3 technique offers immediate, predictable, and symmetrical return of smile function. Objective symmetry analysis and favourable expert grading of both pre-/post-operative photographs and the scar at the melolabial fold demonstrate applicability for facial reanimation in patients where other procedures have failed, or when a direct return to function is desired. Both the melolabial approach and transoral approach were found to be acceptable and effective, although applicability varies.
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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 | 0.002 |
| 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) | 0.002 | 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".