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EEG markers of cognitive impairments in patients with coronary artery disease

2016· article· en· W2740357464 on OpenAlexaboutno aff
И. В. Тарасова, И. Н. Кухарева, О. Л. Барбараш

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsElectroencephalographyCoronary artery diseaseCardiologyAudiologyMedicineInternal medicineLateralization of brain functionMontreal Cognitive AssessmentPsychologyCognitive impairmentDiseasePsychiatry

Abstract

fetched live from OpenAlex

Objective: to identify the indicators of bioelectrical activity of the cerebral cortex, which are associated with cognitive impairments in patients with coronary artery disease (CAD).Patients and methods. The study included 122 male patients aged 45 to 69 years with CAD. Sixty of them were found to have mild cognitive impairments (MCI), their average Mini-Mental State Examination (MMSE) score was 26.2±0.90; the other 62 patients had no cognitive impairment; their MMSE score was 28.5±0.86. All the patients underwent clinical and instrumental examinations and computer-based multichannel electroencephalography (EEG). Eyes-closed and eyes-open resting EEG monopolarly recorded in 62 standard leads of the 10-20 system. A binary logistic regression analysis was used to identify EEG predictors of MCI in patients with CAD.Results. The high power values of theta1-rhythm biopotentials with closed eyes in the frontal and occipital areas of the left hemisphere and those of alpha2-rhythm ones with open eyes in the frontal areas of the right hemisphere, and the high theta/alpha EEG power ratio are associated with an increased risk of MCI in CAD patients. The most important clinical and anamnestic factors associated with a decreased risk of MCI were higher education level, the lack of type 2 diabetes, and milder coronary bed lesions according to the SYNTAX scale. There was an association of the power values of the biopotentials and theta/alpha EEG power ratio and the development of MCI in CAD patients.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.119
GPT teacher head0.453
Teacher spread0.335 · 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.

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

Citations3
Published2016
Admission routes1
Has abstractyes

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