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Record W7045391665

Análise da intensidade, aspectos sensoriais e afetivos da dor de pacientes em pós-operatório imediato

2017· article· pt· W7045391665 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Electronic Library Online (Fundação de Amparo à Pesquisa do Estado de São Paulo) · 2017
Typearticle
Languagept
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMcGill Pain QuestionnairePain sensationClinical PracticeUniversity hospital
DOInot available

Abstract

fetched live from OpenAlex

RESUMO Objetivo Avaliar a dor de pacientes em pós-operatório imediato, na admissão, uma hora após e na alta de uma Unidade de Recuperação Pós-Anestésica quanto a intensidade, aspectos sensoriais e afetivos. Métodos Analítico, transversal, com 336 pacientes, formulário sociodemográfico e clínico, escala numérica da dor e McGill reduzida. Dados coletados em setembro-outubro de 2015 em Unidade de Recuperação Pós-Anestésica (URPA), hospital geral do Noroeste do Rio Grande do Sul. Estatística descritiva, analítica, com significância para p<0,05. Resultados 57,3% não referiram dor, 47% dor da admissão à alta, estatisticamente significativas. Pacientes submetidos a cirurgias oncológicas e traumatológicas relataram mais dor (p<0,01). Na admissão e manutenção prevaleceu dor moderada e intensa; na alta, dor leve e moderada. Conclusões Percentual elevado de pacientes com dor no pós-operatório imediato, desde a admissão na unidade até a alta. Resultados podem instigar pesquisadores e profissionais de saúde às investigações, inclusive com maior número de participantes que permitam inferências.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.003
Science and technology studies0.0090.006
Scholarly communication0.0150.005
Open science0.0100.002
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.308
Teacher spread0.275 · 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 designQualitative
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
Published2017
Admission routes1
Has abstractyes

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