Localized Transcranial Electrical Motor Evoked Potentials for Monitoring Cranial Nerves in Cranial Base Surgery
Bibliographic record
Abstract
OBJECTIVE: To describe a novel monitoring technique that allows "functional" assessment of cranial nerve continuity during cranial base surgery. METHODS: Facial motor evoked potentials (MEP) in 71 consecutive patients were obtained by localized transcranial electrical stimulation in all patients requiring facial nerve monitoring during the period from November 2002 to August 2004. With transcranial electrical stimulation localized to the contralateral cortex, facial nerve MEPs are obtained through stimulation of more proximal intracranial structures. RESULTS: Logistic regression revealed that the final-to-baseline facial MEP ratio predicted satisfactory (House-Brackmann Grade 1 and 2 function) immediate postoperative facial function (0.005 > P > 0.0005). Contingency table analysis showed high correlation (chi2, P < or = 2 x 10(8)) and acceptable test characteristics using a 50% final-to-baseline MEP ratio. CONCLUSION: Facial nerve MEPs recorded intraoperatively during cranial base surgery using the proposed technique predicts immediate postoperative facial nerve outcome. This technique can also be used to monitor other motor cranial nerves in cranial base surgery.
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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 | 0.002 |
| 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) | 0.001 | 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".