International Tuberculum Sellae Meningioma Study: Preoperative Grading Scale to Predict Outcomes and Propensity-Matched Outcomes by Endonasal Versus Transcranial Approach
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Tuberculum sellae meningiomas are resected via an expanded endonasal (EEA) or transcranial approach (TCA). Which approach provides superior outcomes is debated. The Magill-McDermott (M-M) grading scale evaluating tumor size, optic canal invasion, and arterial involvement remains to be validated for outcome prediction. The objective of this study was to validate the M-M scale for predicting visual outcome, extent of resection (EOR), and recurrence, and to use propensity matching by M-M scale to determine whether visual outcome, EOR, or recurrence differ between EEA and TCA. METHODS: Forty-site retrospective study of 947 patients undergoing tuberculum sellae meningiomas resection. Standard statistical methods and propensity matching were used. RESULTS: The M-M scale predicted visual worsening (odds ratio [OR]/point: 1.22, 95% CI: 1.02-1.46, P = .0271) and gross total resection (GTR) (OR/point: 0.71, 95% CI: 0.62-0.81, P < .0001), but not recurrence ( P = .4695). The scale was simplified and validated in an independent cohort for predicting visual worsening (OR/point: 2.34, 95% CI: 1.33-4.14, P = .0032) and GTR (OR/point: 0.73, 95% CI: 0.57-0.93, P = .0127), but not recurrence ( P = .2572). In propensity-matched samples, there was no difference in visual worsening ( P = .8757) or recurrence ( P = .5678) between TCA and EEA, but GTR was more likely with TCA (OR: 1.49, 95% CI: 1.02-2.18, P = .0409). Matched patients with preoperative visual deficits who had an EEA were more likely to have visual improvement than those undergoing TCA (72.9% vs 58.4%, P = .0010) with equal rates of visual worsening (EEA 8.0% vs TCA 8.6%, P = .8018). CONCLUSION: The refined M-M scale predicts visual worsening and EOR preoperatively. Preoperative visual deficits are more likely to improve after EEA; however, individual tumor features must be considered during nuanced approach selection by experienced neurosurgeons.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".