Methods of cognitive status research in patients with glioblastoma
Bibliographic record
Abstract
Introduction: Glioblastoma is a high-grade, aggressive central nervous system tumor with predominantly astrocytic differentiation, characterized by fast invasive growth into the surrounding brain parenchyma and aggressive clinical course. The short life expectancy of patients diagnosed with glioblastoma necessitates the need to maximize their quality of remaining life. One of the most common reasons for quality of life impairment in these patients is the cognitive deficit accompanying the disease. There is a lack of a unified and standardized method for the assessment of cognitive functions in these patients, which meets all the necessary criteria to be convenient and usable in the wide clinical practice. Aim: The aim of the present study is to compare the Montreal cognitive assessment (MoCA) brief screening test with an extended neuropsychological examination to determine its applicability in patients diagnosed with glioblastoma. Material and methods: The study includes 27 patients undergoing neurosurgical intervention for histologically proven IDH-wildtype glioblastoma in the Department of Neurosurgery, “St. Marina” University Hospital – a tertiary healthcare center, for the period January 2019 to December 2022. Preoperatively, patients were examined with the short MoCA screening test and an extended neuropsychological examination including the following subtests: Issac set test, Trail making test A and B, Luria test, Raven‘s color matrices, Stroop test and Bender test. Results: Of all the patients studied, those with a MoCA score below 26 points present at least one negative test of the extended neuropsychological examination. MoCA patients with scores of 26 or more do not demonstrate cognitive impairment in the extended neuropsychological impairment. Conclusion: The obtained results support the claim that the MoCA short screening test is applicable for preoperative diagnosis of cognitive disorders in patients with glioblastoma. Due to the study‘s small sample size, further research is needed to definitively prove this claim.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".