P.137 Surgical approaches to adult thalamic gliomas: a systematic review
Bibliographic record
Abstract
Background: Adult thalamic gliomas (ATGs) present a surgical challenge given their depth and proximity to eloquent brain regions.Though a relative abundance of literature has been published regarding the surgical management of thalamic lesions in pediatric patients, a scarce amount exists dedicated to adult populations. Methods: Literature regarding surgical management of thalamic gliomas in adult patients was reviewed according to the PRISMA guidelines. Fours databases were searched with keywords “‘thalamic glioma’ AND ‘surgical intervention’ OR ‘thalamic glioma’ AND ‘surgical treatment’” in July 2021 for articles assessing surgical techniques of ATG resection. Results: The mean age of adult undergoing surgical management was 33.57 years with a median preoperative KPS of 72.15. Among the 507 cases, several surgical approaches were utilized. Transcortical approaches were most frequently used accounting for 37.8% of all cases followed by transventricular (23.8%), transcallosal (22.8%), and trans-sylvian transinsular (2.92%). Conclusions: Studies in this review agree that decreased age, low grade glioma, increased KPS, and increased duration of symptoms are positive prognostic factors. Greater degree of resection provides a positive survival benefit, and transcortical approaches appear to carry a greater overall survival. Stratified guidelines could pose an overall advantage to surgical success when making decisions on treatment approach.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.009 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".