Awake Surgical Management of Third Ventricular Tumors: A Preliminary Safety, Feasibility, and Clinical Applications Study
Bibliographic record
Abstract
BACKGROUND: Endoscopic and microneurosurgical approaches to third ventricular lesions are commonly performed under general anesthesia. OBJECTIVE: To report our initial experience with awake transsulcal parafascicular corridor surgery (TPCS) of the third ventricle and its safety, feasibility, and limitations. METHODS: A total of 12 cases are reviewed: 6 colloid cysts, 2 central neurocytomas, 1 papillary craniopharyngioma, 1 basal ganglia glioblastoma, 1 thalamic glioblastoma, and 1 ependymal cyst. Lesions were approached using TPCS through the superior frontal sulcus. Pre-, intra-, and postoperative neurocognitive (NC) testing were performed on all patients. RESULTS: No cases required conversion to general anesthesia. Awake anesthesia changed intraoperative management in 4/12 cases with intraoperative cognitive changes that required port re-positioning; 3/4 recovered. Average length of stay (LOS) was 6.1 d ± 6.6. Excluding 3 outliers who had preoperative NC impairment, the average LOS was 2.5 d ± 1.2. Average operative time was 3.00 h ± 0.44. Average awake anesthesia time was 5.05 h ± 0.54. There were no mortalities. CONCLUSION: This report demonstrated the feasibility and safety of awake third ventricular surgery, and was not limited by pathology, size, or vascularity. The most significant factor impacting LOS was preoperative NC deficit. The most significant risk factor predicting a permanent NC deficit was preoperative 2/3 domain impairment combined with radiologic evidence of invasion of limbic structures - defined as a "NC resilience/reserve" in our surgical algorithm. Larger efficacy studies will be required to demonstrate the validity of the algorithm and impact on long-term cognitive outcomes, as well as generalizability of awake TPCS for third ventricular surgery.
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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 | 0.001 |
| 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".