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Record W4405258576 · doi:10.25692/asy.2024.18.1.001

Активность церебральных структур в покое у больных с хронической ишемией мозга, различающихся по тесту МоСА

2024· article· ru· W4405258576 on OpenAlexaboutno aff
В.Ф. Фокин, Н.В. Пономарева, Р.Б. Медведев, О.В. Лагода, М.М. Танашян, Р.Н. Коновалов, М.В. Кротенкова

Bibliographic record

VenueАсимметрия. · 2024
Typearticle
Languageru
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentInferior parietal lobuleNeuroscienceOrbitofrontal cortexSuperior parietal lobulePsychologyDementiaFunctional magnetic resonance imagingMedicineAnterior cingulate cortexResting state fMRICortex (anatomy)CognitionPrefrontal cortexInternal medicineCognitive impairmentDisease

Abstract

fetched live from OpenAlex

Монреальский когнитивный тест (MoCA) — широко используемый инструмент скрининга для выявления легких когнитивных нарушений и ранних стадий деменции. Целью исследования было выявление церебральных структур, связанных с успешным и неуспешным выполнением теста МоСА у пациентов с хронической ишемией головного мозга (ХИМ). Функциональная магнитно-резонансная томография (фМРТ) в состоянии покоя была проведена 83 пациентам с ХИМ в возрасте от 43 до 87 лет. Паттерны активации мозга сравнивались между пациентами, набравшими высокие (29–30) и низкие (18–22) баллы по тесту MoCA. У пациентов с успешным выполнением MoCA наблюдалась значительно более высокая активация в нескольких областях мозга, включая левую нижнюю теменную дольку, левую верхнюю височную извилину, левую среднюю затылочную извилину, левую угловую извилину, правую островковую кору, правую скорлупу, левую нижнюю теменную дольку, левую орбитофронтальную кору, левую островковую кору, переднюю поясная извилина, верхнюю лобную извилину и левое хвостатое ядро. Эти результаты позволяют предположить, что снижение когнитивных функций при ХИМ связано с дегенерацией структур мозга, участвующих в различных когнитивных областях, оцениваемых с помощью теста MoCA, с одной стороны, а с другой – с развитием заболевания. Сочетание когнитивных оценок с методами нейровизуализации позволяет лучше понять нейронные механизмы когнитивных нарушений при хронических цереброваскулярных заболеваниях. The Montreal Cognitive Assessment (MoCA) is a widely used screening tool to detect mild cognitive impairment and early stages of dementia. The aim of the study was to identify cerebral structures associated with successful and unsuccessful performance of the MoCA test in patients with chronic cerebral ischemia (CCI). Resting-state functional magnetic resonance imaging (fMRI) was performed on 83 patients with CCI aged 43 to 87 years. Brain activation patterns were compared between patients scoring high (29–30) and low (18–22) on the MoCA test. Patients who successfully completed MoCA had significantly higher activation in several brain regions, including the left inferior parietal lobule, left superior temporal gyrus, left middle occipital gyrus, left angular gyrus, right insular cortex, right putamen, left inferior parietal lobule, left orbitofrontal cortex, left insular cortex, anterior cingulate cortex, superior frontal gyrus and left caudate nucleus. These results suggest that cognitive decline in CCI is associated with degeneration of brain structures involved in various cognitive domains assessed by the MoCA test, on the one hand, and with the development of the disease, on the other. Combining cognitive assessments with neuroimaging techniques allows us to better understand the neural mechanisms of cognitive impairment in chronic cerebrovascular diseases.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.012
Scholarly communication0.0130.007
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0250.008

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 head0.020
GPT teacher head0.285
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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