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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 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)0.025
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.025
Threshold uncertainty score0.133

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.045
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0080.008
Science and technology studies0.0010.001
Scholarly communication0.0060.004
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.037
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; 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 designSystematic review
Domainnot available
GenreReview

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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