Resection of the Odontoid Process through Expanded Endoscopic Endonasal Approach: Our Clinical Experience and Surgical Techniques
Bibliographic record
Abstract
Introduction: patients with ventral cervical-medullary compression e.g., rheumatoid arthritis patients require anterior decompression of the cervico-medullary junction. Resection of the odontoid process can be accomplished through expanded endoscopic endonasal approach especially in cases of irreducible basilar invagination in which the pathology is situated well above the palatine line. Methods: We are presenting our experience at the Ottawa Hospital (TOH) and University of Ottawa over the last seven years in patients who underwent expanded endoscopic endonasal decompression of their cervicomedullary junction. Over the last seven years, 16 patients underwent such procedure, those patients with preoperative cervical instability underwent posterior fusion of the upper cervical spine to the occiput for stabilization at the same surgical setting. Our follow up ranged from 9 months to 5 years. Results: All patients presented with severe symptoms of myelopathy and some lower cranial nerves dysfunction. All patients demonstrated improvement in their symptoms. All patients were extubated after recovery from anesthesia and allowed oral food intake the next day. None of our patients required tracheostomy. 12.5% experienced transient velopharyngeal insufficiency. one patient had CSF leak which was successfully treated with lumbar drain. One of our patients developed infection from the posterior cervical fusion and required debridement and antibiotics treatment. All of our patients were eventually discharged home. Postoperative imaging demonstrated excellent decompression of the anterior cervicomedullary junction pathology. Conclusions: The expanded endoscopic endonasal approach for odontoidectomy should be considered as a minimally invasive approach for anterior decompression in selected cases.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".