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Record W4404660446 · doi:10.56238/arev6n3-224

AVALIAÇÃO DE CONSTRUCTOS COGNITIVOS EM PACIENTES COM DOENÇA RENAL CRÔNICA, EM HEMODIÁLISE

2024· article· pt· W4404660446 on OpenAlexaboutno aff
Jayne Zaniratto, Karina Kelly Borges, Carla Rodrigues Zanin

Bibliographic record

VenueAracê. · 2024
Typearticle
Languagept
FieldPsychology
TopicHealth and Well-being Studies
Canadian institutionsnot available
Fundersnot available
KeywordsHemodialysisKidney diseaseMedicineCognitionDiseaseInternal medicineIntensive care medicinePsychiatry

Abstract

fetched live from OpenAlex

Pacientes com doença renal crônica, frequentemente apresentam comprometimento cognitivo, sendo assim, o objetivo foi caracterizar e avaliar a presença de disfunções cognitivas e executivas em pacientes que realizam hemodiálise. O estudo é quantitativo, exploratório, transversal, onde foi utilizado os instrumentos: questionário sociodemográfico, Montreal cognitive assessment basic, Teste dos cinco dígitos, Escala de avaliação de disfunções executivas de Barkley e o kidney disease quality of life short form. Participaram da pesquisa 25 indivíduos, sendo 52% do sexo feminino, com média de idade de ± 52 anos, casadas, com mais de 8 anos de estudo e mais de 02 anos em diálise. Quanto às disfunções foram identificadas 28% de disfunção cognitiva geral e mais de 24 % déficits proeminentes em linguagem, memória operacional, controle de tomada de decisão e escolhas. Em relação à qualidade de vida, os domínios com menores pontuações foram saúde geral, limitações emocionais, trabalho e carga da doença renal. A pesquisa indica alterações cognitivas significativas, mais especificamente em linguagem, funções executivas, orientação, linguagem, abstração, cálculo, memória, atenção, percepção visual e concentração. Os resultados podem indicar fatores importantes que interfiram na compreensão do tratamento e consequentemente à adesão.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.031
GPT teacher head0.347
Teacher spread0.316 · 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
Published2024
Admission routes1
Has abstractyes

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