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Record W4293237696 · doi:10.7759/cureus.28397

Assessment of Cognition in Hypertensives and Normotensives: A Comparative P300 Study

2022· article· en· W4293237696 on OpenAlexaboutno aff
Yeswanth Gogisetti, Monika Pathania, Sunita Mittal, Pradeep Yadav, Prabin Kharibam, Ravi Kant

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDementiaMontreal Cognitive AssessmentCognitionAudiologyCognitive declinePopulationPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: Hypertension is an established risk factor for dementia, and the prevalence of hypertension and dementia is rising. Current tests to diagnose cognitive dysfunction at an early stage lack sensitivity and specificity. Recently event-related potentials (ERPs) have gained much attention in diagnosing cognitive dysfunction and are independent of the education status of the subject. This study was done to find any cognitive deficits in the hypertensive population with electrophysiological evidence, which might open the doors for the need to screen the population at an earlier stage so that the population can be prevented from dementia. METHODS: Some 31 middle-aged (18-65 years) hypertensives were compared with 31 age, sex, education, and handedness matched normotensives about cognition by neuropsychometric test battery including Hindi Mini-mental Status Examination (HMSE), Hindi Montreal Cognitive Assessment (MoCA), choice reaction time (CRT), and auditory event-related potentials. RESULTS: Hypertensives and normotensives differed significantly concerning P300 potentials' latency (Fz and Cz P300 latencies: p-value: 0.001), and this change was correlated well with the duration of diastolic blood pressure (BP) (r-value: 0.670). The remaining tests, HMSE, Hindi MoCA, and CRT, were dependent on the education status of the patient. CONCLUSIONS: The effect of hypertension on cognitive impairment is evident and can be proved early in its pre-clinical stage using ERPs. Early identification can help in specifying high-risk individuals. ERPs have great potential in screening and diagnosing and can also help in assessing cognition as a reliable tool to show the effect of treatments/interventions on cognitive defects.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.043
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

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

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 head0.051
GPT teacher head0.389
Teacher spread0.338 · 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.

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

Citations6
Published2022
Admission routes1
Has abstractyes

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