Peri-operative electrically evoked auditory brainstem response assessment of facial nerve/cochlea interaction at cochlear implantation
Bibliographic record
Abstract
OBJECTIVES: Dehiscence between the cochlear otic capsule and the facial nerve canal is a rare and relatively newly described pathology. In cochlear implantation (CI), this dehiscence may lead to adverse electric facial nerve stimulation (FNS) already at low levels, rendering its use impossible. Here, we describe an assessment technique to foresee this complication. METHODS: Pre- and postoperative computed tomography (CT) scans and intraoperative electrically evoked auditory brainstem response (e-ABR) measurements were analyzed in two patients with cochlear-facial dehiscence (CFD). RESULTS: Because of the relatively low resolution, the confirmation of CFD with a clinical CT was difficult. The e-ABR displayed a large potential with 6 and 7.5 ms latency, respectively, which did not occur otherwise. DISCUSSION: Potential strategies to resolve and manage FNS are described. CONCLUSION: Prediction of FNS by assessing the distance between the labyrinthine portion of the facial nerve and the cochlea is difficult using conventional CT scans. A large evoked late myogenic potential at low stimulation levels during intraoperative e-ABR measurement may foresee FNS at CI activation.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".