Natural History of Hearing Deterioration in Intracanalicular Vestibular Schwannoma
Bibliographic record
Abstract
BACKGROUND: Intracanalicular vestibular schwannomas have a range of treatment options that can preserve hearing: microsurgery, stereotactic radiotherapy, and conservative observation. OBJECTIVE: To evaluate the natural course of hearing deterioration during a period of conservative observation. METHODS: A retrospective case review was performed on 47 patients with a unilateral intracanalicular vestibular schwannoma. Evaluation of growth was monitored by repeat MRI scanning. Repeated pure-tone and speech audiometry results were evaluated for subgroups of patients showing growth or no growth and by subsite location of tumor in the internal auditory canal. RESULTS: Patients had a mean follow-up of 3.6 years. Over the entire population, the pure-tone average thresholds at 0.5, 1, 2, and 3 kHz and the word recognition scores both significantly deteriorated from 38 to 51 dB HL, and from 66% to 55%, respectively. Overall, 74% of subjects with good hearing, according to the 50/50 rule, maintained hearing above this rule. There were no significant differences in hearing loss by subsite in the internal auditory canal (porus, fundus, central) or by growth status (stable, growing, shrinking). Only 6 patients showed a large hearing change. This happened early during follow-up, with relatively stable hearing after this. CONCLUSION: Hearing will deteriorate in some intracanalicular vestibular schwannomas, regardless of tumor growth. Hearing deterioration, if on a large scale, most likely occurs early in follow-up. The present results using conservative management in these tumors appear similar to those reported for stereotactic radiotherapy or microsurgery.
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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 | 0.001 | 0.003 |
| 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 | 0.000 |
| 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".