P.010 5 layers reconstruction, superior semicircular canal dehiscence repair: our experience and surgical technique
Bibliographic record
Abstract
Background: Superior semicircular canal dehiscence (SSCD) is a recently described rare condition. SSCD symptoms include vertigo, oscillopsia, autophony, sound hypersensitivity , and conductive hearing loss. Patients with sever symptoms may require surgical treatment. Tranmastoid and middle fossa (MCF) approaches are common approaches. Methods: We are presenting our experience at the Ottawa Hospital over the last three years. Also we describe our multidisciplinary surgical approach and modalities to localize the SSCD intraoperatively. Demographic data, presenting symptoms, co-morbidities, radiologic imaging, and surgery length were recorded. All patients had hearing and vestibular tests before and after their surgeries. Results: 14 surgeries were performed in 11 patients (three patients had bilateral SSCD). Most patients were males (82%). Age range was 32-68 years. Surgeries were done by a team of a neurosurgeon and a neuro-otologist. Localization of SSCD was done using stereotactic guidance. Five layers’ reconstruction was performed in all patients. All patients had significant improvement in symptoms without sensorineural hearing loss. None of the patients developed post-operative hematoma, infection, seizures, CSF leakage or facial palsy. LOS was 1-2 days. Conclusions: MCF with multi layers reconstruction should be considered as a safe and effective approach in severely symptomatic patients. We demonstrated that this approach has minimal risks especially in regards to sensorineural hearing loss.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".