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Some features of morphometric characteristics of the brain in patients with lacunar stroke

2014· article· en· W2339651763 on OpenAlexaboutno aff
М. І. Салій, Z.V. Salii, Svitlana Shkrobot

Bibliographic record

VenueS S Korsakov Journal of Neurology and Psychiatry · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsLacunar strokeMedicineAtrophyCognitionStroke (engine)CardiologyCognitive deficitInternal medicineMontreal Cognitive AssessmentSulcusIschemic strokeCognitive impairmentSurgeryIschemiaPsychiatry

Abstract

fetched live from OpenAlex

Objective. To determine the structural-morphometric peculiarities of the brain in patients with lacunar ischemic stroke and their influence on cognitive functions. Material and methods. A morphometric analysis of brain CT was performed in 48 patients in the acute period of lacunar stroke. The width of subarachnoid spaces at the pole of the frontal lobes and the lateral sulcus was measured in axial sections, the ventricular system was assessed be several parameters. To adjust for the total head size, the data were evaluated as ratios. Mean populations values adjusted for age were used as normal values. Cognitive functions were measured with the MoCA scale. Results. It was determined that 71% of the patients had lacunar stroke as a result of the atrophic process in the brain. Atrophic process of the brain was often diagnosed in the age group of 61-70 years, multiple lacunar lesions were diagnosed in the group of 51-60 years. Cognitive functions were impaired in 91% of the patients in the acute period of lacunar stroke. Conclusion. Correlations between the level of cognitive functions and morphometric markers of subcortical atrophy demonstrate the leading role of the subcortical atrophy in the development and progression of cognitive deficit.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.006
GPT teacher head0.211
Teacher spread0.205 · 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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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