Endoscopic endonasal transpterygoid nasopharyngectomy
Bibliographic record
Abstract
OBJECTIVE: Describe our technique for endoscopic transpterygoid nasopharyngectomy and support its feasibility with our early clinical outcomes. METHODS: Our endoscopic technique comprises an extended inferomedial maxillectomy, mobilization of the pterygopalatine fossa, removal of the pterygoid plates and Eustachian tube to access the posterolateral nasopharynx. Control of the parapharyngeal and petrous segments of the internal carotid artery is the keystone of the approach. RESULTS: Various histopathologies were treated, including epidermoid carcinomas (n = 9), lymphoepithelioma (n = 1), adenoid cystic carcinoma (n = 5), adenocarcinoma (n = 2), mucoepidermoid carcinoma (n = 2), and sarcoma (n = 1). Negative microscopic margins were obtained in 95% (19/20) of patients. No perioperative mortality, cerebral spinal fluid (CSF) leak, meningitis, or cerebrovascular accident was encountered; however, one patient suffered an internal carotid artery (ICA) injury, without permanent sequelae. All but one patient received adjuvant therapy (external and/or stereotactic radiotherapy with or without chemotherapy). Follow-up ranged from 15 to 68 months (mean = 33). Overall survival was 45% (9/20) and local control was 65% (13/20). CONCLUSIONS: Endoscopic transpterygoid nasopharyngectomy for primary and recurrent nasopharyngeal malignancies is feasible and safe in properly selected patients. Preliminary outcomes compare to that of conventional techniques. Endoscopic resections, however, are demanding; they require specialized equipment and a team versed in endoscopic oncologic surgery. Long-term follow-up and reproducibility remain undefined.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".