Extended Endoscopic Approach for Resection of Craniopharyngiomas
Bibliographic record
Abstract
Objectives Extended endoscopic approaches are useful for resection of selected craniopharyngiomas. Midline, extraventricular, and predominantly cystic lesions are good candidates for endoscopic resection. In this video, we demonstrate the endoscopic endonasal resection of a large suprasellar craniopharyngioma and discuss the nuances of the surgical technique. Design/Setting Surgical video of an extended endoscopic approach for resection of a suprasellar craniopharyngioma. Results We report the case of a 56-year-old woman who presented with bitemporal hemianopsia and visual acuity deterioration secondary to a large suprasellar solid–cystic lesion. The patient underwent an extended endoscopic transtuberculum approach for resection of the lesion, which was diagnosed as a papillary craniopharyngioma. This video discusses the anatomy and surgical technique applied for endoscopic resection of such lesions. Conclusion Endoscopic endonasal surgery is a useful technique for management of craniopharyngiomas. It is associated with good clinical outcomes in selected cases. Complications, such as postoperative CSF leak, may occur and should be carefully managed. The link to the video can be found at: https://youtu.be/EneOCiQE7yo.
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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) | 0.000 | 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) | 0.003 | 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".