Novel Approach to Avoid Manipulation of the Medial Pterygopalatine Fossa Contents during Surgical Management of Sphenoid Sinus Lateral Recess Cerebrospinal Fluid Leaks: The Posterior Maxillary Sinus Window Technique
Bibliographic record
Abstract
Endoscopic endonasal techniques for the management of the majority meningo(encephalo)celes and/or leakage of cerebrospinal fluid (CSF) into the lateral recess of the sphenoid sinus have a high success rate with low complication rates. However, in certain cases, the aperture between the second branch of the trigeminal nerve (V2) and the Vidian nerve is too narrow to efficiently access the lateral recess from medially through the sphenoid sinus airspace. In these situations, it is thought necessary to expose and lateralize the pterygopalatine fossa contents to visualize the entirety of the skull base defect. In this setting, the manipulation of V2, vidian, and descending palatine nerves may be injured, leading to higher morbidity including dry eye and numbness of the ipsilateral palate and/or larger V2 innervation area. To address this issue, we describe an alternative endoscopic endonasal access route to the sphenoid lateral recess (novel technique). This technique involves the creation of a window in the posterior wall of the maxillary sinus directly anterior to the lateral recess airspace, avoiding manipulation and dissection of the pterygopalatine fossa contents. The intention of this technique is to reduce the postoperative morbidity associated with the transpterygoid approach. We present in detail two such cases in whom this technique was used with CSF leaks and meningoceles. A detailed description of the clinical cases with pre-, intra-, and postoperative images is presented as well as important considerations for case selection and technical nuances of the surgical technique.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".