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Record W7065845863

Função cognitiva e controle da pressão arterial em idosos hipertensos

2022· article· pt· W7065845863 on OpenAlexaboutno aff

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2022
Typearticle
Languagept
FieldEngineering
TopicElectromagnetic Compatibility and Measurements
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionCognitive impairmentPopulationElderly peopleArterial disease
DOInot available

Abstract

fetched live from OpenAlex

Resumo O objetivo deste artigo é estimar a prevalência de comprometimento cognitivo e analisar sua associação com o controle da pressão arterial em idosos hipertensos. Trata-se de um estudo transversal realizado com 383 idosos hipertensos no estado do Piauí, Brasil. Foram coletados dados sociodemográficos, clínicos, realizada aferição da pressão arterial e avaliação da função cognitiva utilizando o teste Montreal Cognitive Assessment (MoCA). Utilizou-se regressão de Poisson com variância robusta. A prevalência de comprometimento cognitivo foi de 74,4%, sendo maior na faixa etária entre 80 anos ou mais de idade e naqueles com menor escolaridade. A prevalência de pressão arterial não controlada foi de 61,6%, com maior proporção entre os idosos com comprometimento cognitivo. Observou-se associação entre o comprometimento cognitivo e pressão arterial não controlada (RPAjustada: 3,98; IC95% = 2,51-6,33). A associação significativa entre função cognitiva e controle pressórico sugere que comprometimento cognitivo é um importante fator de risco para pressão arterial não controlada em pessoas idosas. A inclusão de medidas de rastreamento para possíveis déficits cognitivos podem ser úteis para melhor monitoramento da elevação dos níveis pressóricos entre idosos hipertensos.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.233
Teacher spread0.207 · 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
Published2022
Admission routes1
Has abstractyes

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