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Record W4400677510 · doi:10.56083/rcv4n7-122

ESCALAS DE FUNCIONALIDADE E SINTOMAS NO MANEJO NUTRICIONAL DE PACIENTES EM CUIDADOS PALIATIVOS: REVISÃO INTEGRATIVA

2024· article· pt· W4400677510 on OpenAlexaboutno aff
Ana Luiza Barros Nascimento, Alexandre Milagres Júnior, Eunice da Silva Barros

Bibliographic record

VenueRevista Contemporânea · 2024
Typearticle
Languagept
FieldMedicine
TopicPalliative and Oncologic Care
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative careMedicinePhilosophyNursing

Abstract

fetched live from OpenAlex

Objetivo: buscar evidências científicas do uso das ferramentas de escalas de funcionalidade e de sintomas no manejo nutricional de pacientes adultos e idosos com câncer em Cuidados Paliativos. Método: revisão integrativa de artigos indexados em três bases de dados. A busca foi realizada com seis descritores, sem limite de período, nos idiomas português, inglês e espanhol, em abril de 2023. Resultados: identificaram-se 408 artigos, dos quais 244 foram selecionados para leitura do resumo. 32 artigos seguiram para leitura na íntegra, sendo que 23 atenderam aos critérios de inclusão. Foi possível avaliar a relação entre quatro escalas de funcionalidade: Edmonton Symptom Assessment System (ESAS), Eastern Cooperative Oncologic Group (ECOG), Karnofsky Performance Status (KPS) e Palliative Performance Scale (PPS), com três temáticas relacionadas à atuação do nutricionista: estado nutricional, terapias nutricionais e prognósticos de vida. Considerações finais: as escalas apresentam potencial na triagem e avaliação de riscos nutricionais, bem como na determinação e continuação de terapias nutricionais. Recomenda-se, desde a primeira consulta com o nutricionista, o uso e acompanhamento das escalas juntamente com outras ferramentas já utilizadas, tais como a Avaliação Global Subjetiva Gerada pelo Paciente (ASG-ppp) e a Glasgow modificada (GPSm).

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient 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: none
Teacher disagreement score0.625
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.003

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 head0.037
GPT teacher head0.337
Teacher spread0.300 · 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
Published2024
Admission routes1
Has abstractyes

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