Comparison of hypoglossal nerve transfer and hypoglossal jump nerve graft techniques for facial reanimation: A systematic review
Bibliographic record
Abstract
BACKGROUND: Facial paralysis significantly affects patient quality of life by impairing facial expression, speech, and swallowing. Hypoglossal nerve transfer (HNT) and hypoglossal jump nerve graft (HJG) are established surgical techniques for facial reanimation, each with distinct advantages and complications. This systematic review compares the functional outcomes and complications of HNT and HJG to guide optimal surgical decision making. METHODS: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic review was conducted across 7 databases. Studies comparing HNT (end-to-end [ETE] or end-to-side [ETS]) and HJG techniques in adults with facial paralysis were included. Primary outcomes included facial movement recovery assessed via the House-Brackmann (HB) scale, Sunnybrook grading system, FaCE survey, or Facial Disability Index. Secondary outcomes included complication rates, quality of life, and predictors of surgical success. Risk of bias was assessed using ROB-2, Newcastle-Ottawa Scale, and ROBINS-I tools. RESULTS: A total of 34 studies comprising 1008 patients were included. HNT (ETE) provided robust facial reanimation but was associated with high rates of tongue atrophy (73%) and speech/swallowing difficulties (57%). HNT (ETS) preserved partial hypoglossal function and reduced morbidity while maintaining favorable outcomes (HB II-III recovery in 78-86%). HJG minimized complications, with no severe tongue atrophy and HB II-III recovery in 62.5-91.6% of patients. Recovery was slower in patients who underwent HJG due to nerve grafting but resulted in improved long-term facial symmetry and reduced synkinesis. CONCLUSION: Both HNT and HJG are effective for facial reanimation. HNT (ETE) offers faster recovery but has higher morbidity, while HJG minimizes complications and maintains functional outcomes. HNT (ETS) provides a balance between efficacy and morbidity. Future comparative studies using standardized outcome measures are needed to refine patient-specific surgical selection, guided by accumulated clinical experience and published outcomes.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.011 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".