Hearing Preservation After Microsurgical Resection of Large Vestibular Schwannomas
Bibliographic record
Abstract
BACKGROUND: Hearing, which is often still clinically useful at presentation even with larger tumors, is a major determinant of quality of life in vestibular schwannoma (VS) patients. OBJECTIVE: To present the hearing preservation rate after surgery in patients with large (>or=3 cm) VSs and identify clinical or radiologic predictors of hearing preservation. METHODS: From April 2003 to March 2009, 192 patients underwent resection of a VS, including 46 large (>or=3 cm) tumors, of whom 28 had serviceable hearing preoperatively. Six of 28 patients (21.4%) had preserved hearing postoperatively. RESULTS: Mean tumor diameter was 3.6 cm (range, 3.0-5.0 cm) and tumor volume was 17.2 mL (range, 6.9-45.2 mL). For patients with grade A Sanna-Fukushima hearing, the hearing preservation rate was 4 of 11 (36.4%). Complete resection was achieved in 6 of 6 cases with hearing preservation (41/47 for all patients). Six of 6 patients with preserved hearing had a cerebrospinal fluid cleft in the internal auditory canal (IAC) compared with 9 of 16 patients without preoperative hearing and 9 of 20 for patients with serviceable hearing that was lost postoperatively (P=.045). Six of 6 patients with preserved hearing had less than 35% of the tumor anterior to the longitudinal axis of the IAC compared with 13 of 20 in the serviceable hearing that was lost group (P=.036). CONCLUSION: Our series demonstrates hearing preservation is possible for patients with large VSs and should be attempted in all patients with preoperative hearing. The quality of preoperative hearing, a cerebrospinal fluid cleft at the apex of the IAC, and a smaller proportion of tumor anterior to the IAC were positively associated with hearing preservation.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".