Aplicação da escala de Mcgill para avaliação da dor em pacientes oncológicos
Bibliographic record
Abstract
1024x768 ABSTRACT Objective: to assess pain in cancer patients. Method: a descriptive, prospective study of a quantitative approach, with application of McGill Questionnaire in 52 cancer patients. After collecting the data there was stored and tabulated in Microsoft Office Excel. In statistical analysis, simple measures such as frequency distribution, percentage, average and other appropriate to the studied variables. Results: prevalence of females (51.9%) of Cervical CA (44.2%) in less than one year of treatment (44.2%) and 51.9% were in clinical treatment. The most commonly used descriptors were: Pang (69.2%), Dizzy (65.4%), Unbearable (48.1%) and spreads (40.4%). The Estimated Total Pain Intensity (PRI-T) was 47-56 points in 13 individuals. Pain Intensity Present (PPI) in 19 subjects was uncomfortable. Regarding the time and location of the pain, 16 patients reported that the pain was constant and located. Conclusion : it was found that the qualitative assessment of the pain of cancer patients is constant, localized and uncomfortable. Descriptors: Pain ; Neoplasms; Nursing . RESUMO Objetivo: avaliar a dor em pacientes oncologicos. Metodo: estudo descritivo, prospectivo, de abordagem quantitativa, com aplicacao do Questionario de Mcgill em 52 pacientes oncologicos. Apos a coleta os dados foram armazenados e tabulados no Microsoft Office Excel. Na analise estatistica foram utilizadas medidas simples como: distribuicao de frequencias, percentuais, media e outras apropriadas as variaveis estudadas. Resultados: prevalencia do sexo feminino (51,9%), CA do Colo do Utero (44,2%), em tratamento a menos de 1 ano (44,2%) e 51,9% estavam em tratamento clinico. Os descritores mais usados foram: Pontada (69,2%), Enjoada (65,4%), Insuportavel (48,1%) e Esparrama (40,4%). A Estimativa da Intensidade de Dor Total (PRI-T) foi de 47 – 56 pontos em 13 individuos. A Intensidade de Dor Presente (PPI) em 19 individuos significa desconforto. Quanto ao tempo e localizacao da dor, 16 pacientes relataram que a dor era constante e localizada. Conclusao: Constatou-se que a avaliacao qualitativa da dor dos pacientes oncologicos e constante, localizada e desconfortavel. Descritores: Dor; Neoplasia; Enfermagem. RESUMEN Objetivo: evaluar el dolor en pacientes con cancer. Metodo: un estudio descriptivo, prospectivo, de abordaje cuantitativo, con la aplicacion del Cuestionario McGill en 52 pacientes con cancer. Despues de recoger los datos fueron almacenados y tabulados en Microsoft Office Excel. En el analisis estadistico, medidas sencillas como la distribucion de frecuencias, porcentajes, media y de otra indole para las variables estudiadas. Resultados: la prevalencia de las mujeres (51,9%) de CA cervical (44,2%) en menos de un ano de tratamiento (44,2%) y el 51,9% estaba en tratamiento clinico. Los descriptores utilizados con mayor frecuencia fueron: Pang (69,2%), mareado (65,4%), Insoportable (48,1%) y de que se extienda (40,4%). La intensidad total estimado Dolor (PRI-T) fue de 47-56 puntos en 13 individuos. Intensidad del Dolor Presente (PPI) en 19 sujetos era incomoda. En cuanto a la hora y el lugar del dolor, 16 pacientes informaron que el dolor era constante y situado. Conclusion: se encontro que la evaluacion cualitativa del dolor de pacientes con cancer es constante, localizada e incomoda. Descriptores: Dolor; Neoplasias; Enfermeria. Normal 0 21 false false false PT-BR X-NONE X-NONE
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".