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Record W4399892373 · doi:10.1590/ce.v29i0.90754

INSTRUMENTOS PARA AVALIAÇÃO DE PACIENTES HOSPITALIZADOS EM CUIDADOS PALIATIVOS: REVISÃO INTEGRATIVA

2024· article· pt· W4399892373 on OpenAlexaboutno aff
Tárcilla Pinto Passos Bezerra, Thaíza Teixeira Xavier Nobre, Viviane Peixoto dos Santos Pennafort, José Ronaldo Vasconcelos da Graça, Isabel Pires Barra, Gisele de Oliveira Mourão Holanda, Ana Elza Oliveira de Mendonça

Bibliographic record

VenueCogitare Enfermagem · 2024
Typearticle
Languagept
FieldMedicine
TopicPalliative and Oncologic Care
Canadian institutionsnot available
Fundersnot available
KeywordsPalliative carePhilosophyMedicineNursing

Abstract

fetched live from OpenAlex

RESUMO: Objetivo: identificar os instrumentos utilizados para a avaliação do paciente hospitalizado em cuidados paliativos. Método: revisão integrativa da literatura, realizada em janeiro de 2024, nas plataformas de dados on-line: National Library of Medicine e Literatura Latino-Americana e do Caribe de Informação em Ciências da Saúde e a biblioteca virtual Scientific Electronic Library Online. Foram analisados 12 artigos científicos. Resultados: foram identificados 16 instrumentos, sete genéricos, quatro específicos as para pessoas em cuidados paliativos, quatro específicos para os pacientes oncológicos e um para o diagnóstico de COVID-19. O Palliative Perfomance Scale e Edmonton Symptom Assessment foram os instrumentos mais utilizados nos estudos e os aspectos mais relevantes a serem avaliados nos pacientes em cuidados paliativos, foram: capacidade funcional, sintomas físicos e psicológicos e idade avançada. Conclusão: os instrumentos se mostraram úteis para direcionar os profissionais de saúde, na avaliação do paciente, no planejamento do cuidado e na tomada de decisões.

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)0.047
metaresearch head score (Gemma)0.101
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 score0.047
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0470.101
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.006
Bibliometrics0.0130.014
Science and technology studies0.0020.002
Scholarly communication0.0060.005
Open science0.0030.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.079
GPT teacher head0.379
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

Citations1
Published2024
Admission routes1
Has abstractyes

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