P07.05.A AWAKE CRANIOTOMY FOR ELOQUENT GLIOMA: A SINGLE CENTER COHORT REVIEW
Bibliographic record
Abstract
Abstract BACKGROUND Supratotal oncologic resection, extending beyond visible MRI boundaries, has been shown to slow and prevent malignant progression of gliomas. Despite its benefits, supratotal resection near eloquent areas poses increased risks of postoperative neurological dysfunction. This study aims to present a review of 11 years of awake craniotomies for oncological resection at a Quebec center, comparing resection rates and complication rates with current literature. MATERIAL AND METHODS This retrospective descriptive study includes patients who underwent awake craniotomies for oncologic resection at a Quebec tertiary neurosurgical center between January 2011 and December 2022. Awake craniotomy was indicated for lesions near language eloquent areas with reasonable risks of language deterioration. The surgical plan aimed for supramaximal function-limited safe resection whenever possible. The procedure followed a sleep-awake-sleep strategy. Patients were assessed immediately postoperatively, daily during hospitalization, at 2 weeks post-op with pathology results, and at 3 months post-op. Follow-up continued based on pathology. Data on demographics, pre-op KPS score, length of surgery, time awake, length of hospital stay, cause of possible resection limitation, perioperative complications, and postoperative complications were collected. The extent of resection was assessed using tumor volumetry differences between pre-op and post-op MRI. RESULTS 77 patients underwent awake craniotomy, with 38% female and a mean age of 48 years. The mean pre-op KPS was 93. Diagnoses included various grades of astrocytomas, oligodendrogliomas, glioblastomas, and other pathologies. Perioperative complications included loss of patient cooperation, significant headaches, nausea, agitation, convulsions, and significant bleeding. Resection was limited by reached neurologic functions in 60% of cases. Early postoperative complications occurred in 48% of patients, with 34% experiencing early language deteriorations. Late complications occurred in 13% of patients, with 6% involving language. The mean extent of resection (EOR) was 86.71%. CONCLUSION Despite high early postoperative language deterioration rates, low rate of late language complications suggests that aiming for supramaximal function-limited safe resection permits high EOR with low late language complication rates. Our center results are concordant with current literature, further supporting the use of awake craniotomy as a valuable approach for maximizing safe resections near eloquent cortex areas in oncologic settings.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".