Gauging the effectiveness of canal occlusion surgery: how I do it
Bibliographic record
Abstract
BACKGROUND: Transmastoid occlusion of the posterior or superior semicircular canal is an effective and safe management option in patients with refractory benign paroxysmal positional vertigo or symptomatic superior semicircular canal dehiscence. A method of quantifying successful canal occlusion surgery is described. METHODS: This paper presents representative patients with intractable benign paroxysmal positional vertigo or symptomatic superior semicircular canal dehiscence, who underwent transmastoid occlusion of the posterior or superior semicircular canal respectively. Vestibular function was assessed pre- and post-operatively. The video head impulse test was included as a measure of semicircular canal and vestibulo-ocular reflex functions. RESULTS: Post-operative video head impulse testing showed reduced vestibulo-ocular reflex gain in occluded canals. Gain remained normal in the non-operated canals. Post-operative audiometry demonstrated no change in hearing in the benign paroxysmal positional vertigo patient and slight hearing improvement in the superior semicircular canal dehiscence syndrome patient. CONCLUSION: Transmastoid occlusion of the posterior or superior semicircular canal is effective and safe for treating troublesome benign paroxysmal positional vertigo or symptomatic superior semicircular canal dehiscence. Post-operative video head impulse testing demonstrating a reduction in vestibulo-ocular reflex gain can reliably confirm successful occlusion of the canal and is a useful adjunct in post-operative evaluation.
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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 | 0.038 | 0.140 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".