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Record W3012756496 · doi:10.22126/jap.2020.4741.1371

مقایسه عملکرد شناختی در سالمندان با فشار خون بالا و بدون فشار خون بالا

2020· article· fa· W3012756496 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2020
Typearticle
Languagefa
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

Hypertension and cognitive disorders are common problems in the elderly and their prevalence is increasing as the population ages. The present study aimed to investigate different aspects of cognitive function in elderly people with and without hypertension. It was a causal-comparative study. The statistical population included the elderly of Arak city, among them, two groups of 30 were selected through convenience sampling, one with hypertension based on medical records and the other non-hypertensive. Montreal test was used to assess cognitive performance dimensions. Results of multivariate analysis of variance showed that in all subscales of the Montreal test, the elderly without hypertension performed significantly better than the elderly with hypertension. The most significant differences between the two groups were known in the subscales of language, computation, and attention. This finding suggested the effects of high blood pressure on brain function. According to the results of this study, it is necessary to design and implement therapeutic protocols for the elderly with hypertension for their cognitive rehabilitation.

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)0.012
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.009
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.006
Science and technology studies0.0050.001
Scholarly communication0.0030.005
Open science0.0120.007
Research integrity0.0020.010
Insufficient payload (model declined to judge)0.1290.006

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 head0.591
GPT teacher head0.698
Teacher spread0.107 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2020
Admission routes1
Has abstractyes

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