Brain Cancer Progression: A Retrospective Multicenter Comparison of Awake Craniotomy Versus General Anesthesia in High-grade Glioma Resection
Bibliographic record
Abstract
BACKGROUND: High-grade gliomas impose substantial morbidity and mortality due to rapid cancer progression and recurrence. Factors such as surgery, chemotherapy and radiotherapy remain the cornerstones for treatment of brain cancer and brain cancer research. The role of anesthetics on glioma progression is largely unknown. METHODS: This multicenter retrospective cohort study compared patients who underwent high-grade glioma resection with minimal sedation (awake craniotomy) and those who underwent craniotomy with general anesthesia (GA). Various perioperative factors, intraoperative and postoperative complications, and adjuvant treatment regimens were recorded. The primary outcome was progression-free survival (PFS); secondary outcomes were overall survival (OS), postoperative pain score, and length of hospital stay. RESULTS: A total of 891 patients were included; 79% received GA, and 21% underwent awake craniotomy. There was no difference in median PFS between awake craniotomy (0.54, 95% confidence interval [CI]: 0.45-0.65 y) and GA (0.53, 95% CI: 0.48-0.60 y) groups (hazard ratio 1.05; P <0.553). Median OS was significantly longer in the awake craniotomy (1.70, 95% CI: 1.30-2.32 y) compared with that in the GA (1.25, 95% CI: 1.15-1.37 y) group (hazard ratio 0.76; P <0.009) but this effect did not persist after controlling for other variables of interest. Median length of hospital stay was significantly shorter in the awake craniotomy group (2 [range: 0 to 76], interquartile range 3 d vs. 5 [0 to 98], interquartile range 5 for awake craniotomy and GA groups, respectively; P <0.001). Pain scores were comparable between groups. CONCLUSIONS: There was no difference in PFS and OS between patients who underwent surgical resection of high-grade glioma with minimal sedation (awake craniotomy) or GA. Further large prospective randomized controlled studies are needed to explore the role of anesthetics on glioma progression and patient survival.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".