Surgical Management of Adult Brainstem Gliomas: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
The present review aims to investigate the survival and functional outcomes in adult high-grade brainstem gliomas (BGSs) by comparing data from resective surgery and biopsy. MEDLINE, EMBASE and Cochrane Library were screened to conduct a systematic review of the literature, according to the PRISMA statement. Analysis was limited to articles including patients older than 18 years of age and those published from 1990 to September 2022. Case reports, review articles, meta-analyses, abstracts, reports of aggregated data, and reports on multimodal therapy where surgery was not the primary treatment were excluded. The ROBINS-I tool was applied to evaluate the risk of bias. Six studies were ultimately considered for the meta-analysis. The resective group was composed of 213 subjects and the bioptic group comprised 125. The analysis demonstrated a survival benefit in those patients in which an extensive resection was possible (STR HR 0.59 (95% CI 0.42, 0.82)) (GTR HR 0.63 (95% CI 0.43, 0.92)). Although surgical resection is associated with increased survival, the significantly higher complication rate makes it difficult to recommend surgery instead of biopsy for BSGs. Future investigations combining volumetric data and molecular profiles could add important data to better define the proper indication between resection and biopsy.
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.020 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".