Neuropsychological features of frontal meningioma: systematic literature review
Bibliographic record
Abstract
Introduction. A frontal meningioma is a slow-growing tumour that arises from the meninges, the membranes that surround the brain. It is most commonly benign and often occurs in the frontal region of the brain. Neuropsychological assessment plays a crucial role in understanding and addressing the cognitive and psychiatric implications of frontal meningiomas, ultimately contributing to better patient care and outcomes. Aim. This paper aims to review the existing literature regarding neuropsychological assessment of patients with frontal meningiomas cognitive and emotional functioning. . Methods. After thorough examination, out of 109 studies 16 were included into review using PRISMA protocol for systematic literature reviews. Conclusions. Mini-Mental State Exam (MMSE), Montreal Cognitive Assessment (MoCA) and Trail Making Test (TMT) were found to be the most popular neuropsychological instruments used to assess cognitive functioning. Results indicate, that in most cases shortterm memory, attention and visuospatial functions were impaired. 8 articles also mentioned progressive personality or behavioural change. Emotional functioning was assessed in 15 out of 16 studies using neuropsychological instruments and/or interview. Vast majority of cases mentioned changes in mood, most common being depression or anxiety symptoms and/or diagnosis of major depressive disorder.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".