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Record W4406024187 · doi:10.1002/alz.084782

Correlation Between QEEG Patterns and Neuropsychological Profile in Patients with Cognitive Impairment from the Colombian Caribbean

2024· article· en· W4406024187 on OpenAlexaboutno aff
José María Nava Preciado, Alex Dominguez Vargas, Wanda Torres, Yesenia Pianneta, Mauricio Medina, Marybel Sinisterra, José Manuel Vargas Girón

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentNeuropsychologyAudiologyNeuropsychological assessmentPsychologyCognitionTrail Making TestNeuropsychological testQuantitative electroencephalographyVerbal learningClinical psychologyElectroencephalographyDevelopmental psychologyCognitive impairmentPsychiatryMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Quantitative Electroencephalography (qEEG) plays a pivotal role in the assessment and categorization of cognitive impairment (CI). The integration of qEEG markers with neuropsychological test scores can predict rapid cognitive decline in neurodegenerative diseases. The aim of this study was to correlate qEEG findings with the neuropsychological profile in patients with CI from the Colombian Caribbean. METHODS: A cross-sectional study. Patients with CI (n = 151) from the northern coast of the Colombian Caribbean region were included. Cognitive function was assessed using qEEG and it was categorized as follows: low beta activity (mild CI) (n = 6), frontal slowing (moderate CI) (n = 137), and alterations in alpha activity (severe CI) (n = 8). A cuantitative and normative EEG (Z-score) was performed using the international 10-20 system assembly, a 36 channel EEG amplifier and normative database software-Neurovirtual were used. Neuropsychological profiling was assessed using the following tests: Hopkins Verbal Learning Test-Revised (HVLT-R), Clue Recall, Delayed Recall, Memory Complaint Scale (MCS), Trail Making Test Part A and B (TMT-A/B), Symbol-Digit test, Lawton & Brody, Yesavage, and Montreal Cognitive Assessment (MoCA). Principal component analysis was used to assess relationships between qEEG categories and the neuropsychological profile (Figure 1). RESULTS: Patients with alterations in alpha activity exhibited significantly lower scores on the Lawton & Brody test (p = 0.02) and MoCA (p = 0.04) and higher scores on the Yesavage test (p = 0.04). Significant positive correlations were observed between HLVT-R and Clue recall tests (Spearman r = 0.83, p<0.001), as well as between the MOCA and Lawton & Brody tests (Spearman r = 0.74, p>0.001). In contrast, significant negative correlations were found between the Yesavage and Lawton & Brody tests (Spearman r = -0.45, p = 0.008). CONCLUSIONS: In this study, patients with alterations in alpha activity were correlated with lower cognitive performance and emotional impairment. This study underscores the importance of qEEG in conjunction with the neuropsychological profile in evaluating cognitive impairment, emphasizing its utility in diagnostic and therapeutic interventions in cognitive health planning.

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 score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.291
Teacher spread0.272 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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