Pre-Operative Factors Affecting Resectability of Giant Intracranial Meningiomas
Bibliographic record
Abstract
OBJECTIVE: Larger intracranial tumors require extended operating times and may be associated with increased perioperative complications. There are few reports describing the experience of resecting large meningiomas > or =5cm in a variety of locations. As a group, it remains largely unknown whether these relatively rare lesions are amenable to radical resection, and what factors influence their resectability. METHODS: Sixty-seven patients undergoing surgery for a large intracranial meningioma (> or =5cm in the longest dimension) between 1998 and 2004 were retrospectively reviewed. The surgeries were performed at a single institution University of California at San Francisco. Predictors of resectability were assessed via multivariate logistical regression analysis. RESULTS: Thirty-nine (58%) patients underwent gross total resection (GTR) (Simpson grades I/II). There were no cases of perioperative mortality. At last follow-up, symptoms improved in 39 (58%) patients, remained unchanged in 20 (30%), and were aggravated in 8 (12%). In the multivariate model for all large meningiomas, age>45 years [OR (95%CI); 0.127 (0.026-0.616), p=0.01] and superior sagittal sinus involvement [OR (95%CI); 0.160 (0.026-0.976), p=0.05] were negative predictors of GTR, while preoperative embolization [OR (95%CI); 8.087 (1.719-38.044), p=0.008] was positively associated with GTR. For only supratentorial meningiomas, superior sagittal sinus involvement [OR (95%CI); 0.077 (0.010-0.571), p=0.01] and preoperative embolization [OR (95%CI); 10.492 (1.961-56.135), p=0.006] were independently associated with GTR. CONCLUSIONS: This study evaluated a subset of large intracranial meningiomas > or =5cm. The results indicate that GTR can be achieved in the majority of cases with limited morbidity and mortality, where symptoms will likely improve and recurrences seldom occur. This study may provide useful insights for patients undergoing surgery for large intracranial meningiomas.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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 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".