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Record W7132571546

Neuropsychological features of frontal meningioma: systematic literature review

2024· article· en· W7132571546 on OpenAlexaboutno aff
Silvija Žukaitė, Andrius Kazimieras Minelga, Šarūnas Tamašauskas

Bibliographic record

VenueLithuanian University of Health Sciences · 2024
Typearticle
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsnot available
Fundersnot available
KeywordsNeuropsychologyCognitionSystematic reviewAnxietyNeuropsychological assessmentDepression (economics)Neuropsychological test
DOInot available

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.754
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.300
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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