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Record W4377007940 · doi:10.22408/reva702022466e-7054

INCAPACIDADE FUNCIONAL, FRAGILIDADE E COMPROMETIMENTO COGNITIVO SÃO FATORES ASSOCIADOS A SINTOMAS DEPRESSIVOS EM PACIENTES EM HEMODIÁLISE

2022· article· pt· W4377007940 on OpenAlexaboutno aff
Aimê Cunha, Franciane Trelha, Geovane Barbosa, Laura S. Rubin, Kalina Durigon Keller, Paulo Ricardo Moreira, Rodrigo de Rosso Krug

Bibliographic record

VenueRevista Valore · 2022
Typearticle
Languagept
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesMedicinePhilosophy

Abstract

fetched live from OpenAlex

O objetivo do presente estudo foi associar a presença de sintomas depressivos com características sociais, comportamentais e de saúde em pacientes hemodialíticos. Esta pesquisa quantitativa descritiva teve como amostra 61 pacientes que realizavam hemodiálise em uma clínica renal da região noroeste do estado do Rio Grande do Sul, ano de 2018. Os instrumentos aplicados foram: Prontuário físico funcional (tempo de hemodiálise, idade, peso, altura, profissão e doenças associadas); Teste de seis minutos de caminhada (capacidade funcional); Flexão de antebraço (força de membros superiores); Teste de sentar e levantar (força de membros inferiores); Teste de sentar e alcançar (flexibilidade); Questionários de Lawton e Barthel (atividade de vida diária); Questionário Internacional de Atividade Física (nível de atividade física); Mini Exame de Estado Mental (função cognitiva); Questionário de Edmonton Frail Scale (fragilidade); e, Inventário de Depressão de Beck (depressão). Os dados foram analisados pelo Teste de Exato de Fisher e considerou-se p≤0,05. Foi possível constatar na amostra estudada que possuir sintomas depressivos associou-se a ser dependente nas atividades instrumentais de vida diária, a possuir algum grau de fragilidade e a ter possível comprometimento cognitivo.

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 score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.054
GPT teacher head0.364
Teacher spread0.311 · 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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