Cochlear Implantation and Facial Nerve Stimulation: Clinical and Anatomic Correlations
Bibliographic record
Abstract
OBJECTIVES: One rare complication of cochlear implantation (CI) is facial nerve stimulation (FNS). The aim of the study was to analyze the location and insertion depths for electrode contacts causing FNS. The anatomical variance of the human facial nerve canal (FNC) was explored to elucidate the mechanisms underlying FNS. METHODS: Data were collected from adults that had received a CI from a single tertiary care center. Medical records from 307 patients were retrospectively reviewed. The Uppsala human temporal bone library was leveraged to analyze anatomical structures relevant to FNS. Micro-computed tomography (CT) images of temporal bones (n = 246) were used for three-dimensional (3D) analyses after rendering. Data from synchrotron radiation phase-contrast imaging (SR-PCI) of 83 human temporal bones were analyzed. RESULTS: Nineteen (5.8%) patients experienced FNS. No statistical difference in FNS rates between lateral wall (LW) and peri modiolar (PM) electrodes was found (p > 0.05). Electrode contacts with an angular insertion depth from 250° to 340° were associated with FNS. Analyses of the macerated temporal bones and corrosion casts showed that the average distance between the cochlea and the FNC was 0.3 mm and the closest position of the FNC varied from 253° to 304°. CONCLUSION: The labyrinthine segment of the FN is in close proximity to the cochlea and can be affected by dehiscence. Typically, the bony partition between the FNC and the cochlea is thicker than the modiolar wall and provides insulation against electrical stimulation from nearby CI electrodes. FNS may occur from both LW and PM electrodes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".