Facial nerve prognostication in vestibular schwannoma surgery: The concept of percent maximum and its predictability
Bibliographic record
Abstract
OBJECTIVES/HYPOTHESIS: To evaluate percent maximum as an intraoperative facial nerve measurement for the long-term prognostication of vestibular schwannoma surgery. STUDY DESIGN: Prospective cohort study. METHODS: Evoked amplitude responses to varying levels of stimulus intensity at the nerve root were compared to their supramaximal responses (Mmax) as a percentage, that is, percent maximum. Response charts were constructed for each of the levels of stimulus intensity between 0.05 to 0.3 mA, vis-à-vis facial nerve outcome at 1 year, to establish sensitivities, specificities, and positive predictive values. Logistic regression analyses were used to determine the impact of sex, age, tumor size, and historically defined response parameter on outcomes. RESULTS: Seventy-eight patients who underwent vestibular schwannoma surgeries between 2005 and 2010 were studied. The positive predictive value (PPV) of a good facial nerve outcome, defined as House-Brackmann (HB) I-II, increases with percent maximum responses. A 90% PPV could be established when the response amplitude was 50% or greater compared to Mmax. Long-term prognostication appeared best at a higher stimulus level of 0.3 mA. Age and sex did not have an impact on outcome, but tumor size did; with each centimeter increase in tumor size, patients were 105% more likely to have a poor outcome (HB III-VI). If the response parameter "≥240 μV at 0.05 mA" was not present, there was a trend toward poor outcome. CONCLUSIONS: Percent maximum is a valid intraoperative monitoring measure to prognosticate long-term facial nerve outcome. It should be considered a complementary method of monitoring when evoked responses do not conform to conventional predictors. LEVEL OF EVIDENCE: 4.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".