Comparing Cochlear Implant Outcomes in 100 Patients with Sporadic Vestibular Schwannoma Managed with Observation, Radiosurgery, or Microsurgery: A Multi-Institutional Review
Bibliographic record
Abstract
Objective: To compare cochlear implant (CI) speech perception outcomes in patients with sporadic vestibular schwannoma (VS) managed with observation, radiosurgery, or microsurgery. Study Design:: Retrospective review. Setting:: Eleven tertiary academic medical centers. Patients:: One hundred patients with sporadic VS who received an ipsilateral CI. Interventions:: Ipsilateral cochlear implantation. Main Outcome Measures:: Pure tone thresholds, consonant–nucleus–consonant (CNC) speech perception testing scores, and rates of open-set speech acquisition. Results: Of the 100 patients studied, 54 underwent microsurgery, 26 radiosurgery, 19 continued observation, and 1 underwent multimodal therapy. Among all patients, the median postimplantation pure tone average was 31 dB (IQR: 25–39) and the median CNC word score was 32% (IQR: 5–66) at a median of 12 months (IQR: 5–25) postimplantation. Patients who were managed with microsurgery (median CNC: 16%, IQR: 0–55) exhibited poorer implant outcomes overall compared to those managed with observation (median CNC: 52%, IQR: 40–72) or radiosurgery (median CNC: 32%, IQR: 26–67). Open-set speech perception was achieved in 56% of patients managed with microsurgery, 94% with observation, and 80% with radiosurgery. In a multivariable setting, those managed with observation ( p = 0.01) or who underwent radiosurgery ( p = 0.03) were significantly more likely to achieve open-set speech perception compared to patients who underwent microsurgery. Conclusions: Cochlear implants offer benefit in selected patients with sporadic VS. Although achieved in over half of people after microsurgery, open-set speech perception is more reliably attained in patients who are treated with observation or radiosurgery compared to microsurgical resection. These data may inform patient counseling and VS tumor management in people who may benefit from implantation. Publication History Article published online: 05 February 2024 © 2024. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".