A Comparison of two Sphenoidotomy Approaches using a Novel Computerized Tomography grading System
Bibliographic record
Abstract
BACKGROUND: Endoscopic management of sphenoid sinus disease has great potential for surgical complications. A variety of endoscopic surgical techniques have been described for entering the sphenoid sinus. The utility of these surgical techniques is based on the position of the superior turbinate attachment to the sphenoid face (Parson's ridge). We introduce a novel computerized tomography (CT) grading system for the attachment of the superior turbinate to the sphenoid face. Using this new grading system, we recommend a safer systematic approach for entry into the sphenoid sinus. METHODS: A grading based on the attachment of the superior turbinate to the sphenoid face at the level of the natural sphenoid ostium was developed. A total of 53 patients were enrolled. Types A, B, and C refer to the superior turbinate attachment at the medial, middle, or lateral third of the anterior sphenoid face, respectively, and type D refers to orbital attachment of the superior turbinate. The surgical approach used (superior turbinate intact [STI] or superior turbinate resection [STR]) was recorded and correlated to the type of superior turbinate attachment. RESULTS: The overall incidence of the various superior turbinate attachments were 40% (41) for type A, 41% (42) for type B, 18% (19) for type C, and 1% (1) for type D. STR was used in 38 sides (44%) and STI was used in 48 sides (56%). Spearman correlation study showed that the closer the superior turbinate attachment was to the orbit the more likely STR was used as the choice of entry into the sphenoid (p < 0.001). CONCLUSION: To perform a safe sphenoid entry it is pertinent to evaluate the superior turbinate attachment to the sphenoid face before making a decision on the method of entry.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".