Acoustic Neuroma: Outcome Study
Bibliographic record
Abstract
Three therapeutic modalities have been advocated in the management of acoustic neuromas: observation, surgery, and radiosurgery. Although surgery is still considered conventional treatment, at times the management can be controversial. The objectives of this article are to assess the results of each of these treatment modalities in a tertiary care acoustic neuroma referral setting. The methodology chosen was to group the patients along the initial intent to treat and then to see the results obtained. A total of 51 patients followed in the Skull Base Clinic of the McGill University Health Centre were included. The intent to treat was as follows: observation, 22 patients; surgery, 26 patients; and radiosurgery, 3 patients. The results showed that 50% of those followed by observation demonstrated growth and required surgery or radiotherapy. Surgical results, in terms of facial nerve outcome, varied with tumour size but also improved dramatically with the introduction of facial nerve monitoring and a multidisciplinary approach. In small and medium-size tumours (< 30 mm), intent to treat by observation or by surgery (with intraoperative monitoring) yielded similar results. The limitations of this study are discussed. In the future, a prospective multicentric study may help better in assessing the value of the various management options.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".