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Função cognitiva e controle da pressão arterial em idosos hipertensos

2022· article· pt· W4281836228 on OpenAlexaboutno aff
Alyne Leal de Alencar Luz, Aline Silva‐Costa, Elizabeth Leite Barbosa, Larissa Pruner Marques, Ester Paiva Souto, Rosane Härter Griep

Bibliographic record

VenueCiência & Saúde Coletiva · 2022
Typearticle
Languagept
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentBlood pressureMedicinePoisson regressionCognitionCognitive impairmentGerontologyCognitive Assessment SystemInternal medicinePsychiatryEnvironmental healthPopulation

Abstract

fetched live from OpenAlex

This article aims to estimate the prevalence of cognitive impairment and analyze its association with blood pressure control in elderly hypertensive individuals. Cross-sectional study of 383 elderly hypertensive individuals in the state of Piauí, Brazil. The authors collected sociodemographic and clinical data, performed blood pressure measurement, and assessed cognitive function using the Montreal Cognitive Assessment (MoCA) test. Poisson regression with robust variance was used. Overall prevalence of cognitive impairment was 74.4%, higher in the age group 80 years and over and among older persons with less schooling. Prevalence of uncontrolled blood pressure was 61.6%, with a higher proportion in the elderly with cognitive impairment. An association was observed between cognitive impairment and uncontrolled blood pressure (aPR: 3.98; 95%CI = 2.51-6.33). The significant association between cognitive function and blood pressure control suggest that cognitive impairment is an important risk factor for uncontrolled blood pressure in older persons. The inclusion of screening measures for possible cognitive deficits may be useful for better monitoring blood pressure levels among elderly hypertensive individuals.

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)0.003
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 score0.027
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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)0.0010.000

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 head0.033
GPT teacher head0.264
Teacher spread0.231 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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