Transglabellar Butterfly Incision for Anterior Cranial Vault Access: Case Report
Bibliographic record
Abstract
(1) Background: The transglabellar approach, a type of transfacial technique, typically involves glabellar resection and opening the frontal sinus via a bicoronal incision, providing access to the anterior cranial vault. To prevent complications, the frontal sinus is typically obliterated. However, the success of transnasal endoscopic techniques has prompted a re-evaluation of these traditional methods. (2) Methods: This paper provides a brief literature review and discusses the removal of an elongated glioma of the left gyrus rectus (4.4 × 1.9 × 2.2 cm) in a 63-year-old male using a transglabellar subfrontal approach via a butterfly incision, with frontal sinus preservation. (3) Results: An uneventful gross-total resection of a WHO grade II oligodendroglioma was achieved. There is a paucity of literature describing a transglabellar subfrontal approach via a butterfly incision with frontal sinus preservation. (4) Conclusions: The described approach could be utilized in selected cases such as small intra-axial lesions oriented longitudinally along the inferomedial frontal lobe from the posterior wall of the frontal sinus to the anterior communicating artery complex in patients with pre-existing glabellar rhytids. Since this is merely a case presentation, we cannot conclude that this represents established clinical practice. The outcomes of this approach should be investigated in the future.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| 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".