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Diagnósticos de enfermagem para idosos frágeis institucionalizados

2019· article· pt· W2997038291 on OpenAlexaboutno aff
Bruna Karen Cavalcante Fernandes, Abna Gomes Soares, Brena Valdivino Melo, Willan Nogueira Lima, Cíntia Lira Borges, Valderina Moura Lopes, Renata Kelly Lopes de Alcântara, Maria Célia de Freitas

Bibliographic record

VenueRevista de Enfermagem UFPE on line · 2019
Typearticle
Languagept
FieldNursing
TopicNursing Diagnosis and Documentation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineGerontology

Abstract

fetched live from OpenAlex

RESUMO Objetivo: elaborar diagnósticos de Enfermagem para idosos frágeis institucionalizados. Método: trata-se de um estudo quantitativo, descritivo, transversal, com 53 idosos em uma Instituição de Longa Permanência para Idosos. Utilizaram-se a escala de fragilidade de Edmonton e um instrumento de coleta de dados baseado em Henderson. Fundamentaram-se os diagnósticos na CIPE®, versão 2015. Analisaram-se os dados nos softwares SPSS e Stata apresentando-os em tabela. Resultados: elaboraram-se 178 diagnósticos de Enfermagem dos quais prevaleceram 15 em mais de 20% da amostra. Destacaram-se “Risco de Queda” (84,9%), “Visão prejudicada” (49,1%), “Marcha prejudicada” (37,7%), “Insônia” (28,3 %), “Sono prejudicado” (26,4%), “Humor deprimido” (24,5%) e “Pele seca” (24,5%). Obteve-se significância estatística entre “Risco de queda” (p = 0,008) e “Pele seca” (p= 0,021) e o nível de fragilidade. Houve, ainda, significância entre o número de diagnósticos e o nível de fragilidade (p<0,001) de modo que, quanto maior o nível de fragilidade, mais diagnósticos. Conclusão: elaborou-se 178 diagnósticos de Enfermagem, dos quais prevaleceram 15, sendo o “Risco de queda” o mais prevalente. Contribuir-se á com esse estudo para divulgar a linguagem diagnóstica CIPE® e sensibilizar os enfermeiros acerca da importância de seu uso. Descritores: Enfermagem; Terminologia; Diagnóstico de Enfermagem; Idoso; Instituição de longa permanência para idosos; Fragilidade.ABSTRACT Objective: to elaborate nursing diagnoses for institutionalized frail elderly. Method: this is a quantitative, descriptive, cross-sectional study with 53 elderly people in a Long-Term Care Institution for the Elderly. The Edmonton Frailty Scale and a Henderson-based data collection instrument were used. The diagnoses were based on CIPE®, version 2015. Data was analyzed in the SPSS and Stata software and presented in a table. Results: 178 Nursing diagnoses were elaborated, of which 15 were prevalent in more than 20% of the sample. "Impaired vision" (49.9%), "impaired vision" (37.7%), "insomnia" (28.3%), "impaired sleep" "(26.4%)," depressed mood "(24.5%) and" dry skin "(24.5%). Statistical significance was obtained between "Risk for falls" (p = 0.008) and "Dry skin" (p = 0.021) and the level of frailty. There was also a significant difference between the number of diagnoses and the level of frailty (p <0.001), so that the higher the level of frailty, the more diagnoses. Conclusion: 178 Nursing diagnoses were elaborated, of which 15 prevailed, being the "Risk for fallsing" the most prevalent. It will contribute to this study to disseminate the diagnostic language ICNP® and to make nurses aware of the importance of its use. Descriptors: Nursing; Terminology; Nursing diagnosis; Old man; Long-term institution for the elderly; Frailty.RESUMEN Objetivo: elaborar diagnósticos de enfermería para ancianos frágiles institucionalizados. Método: se trata de un estudio cuantitativo, descriptivo, transversal, realizado con 53 ancianos en una Institución de Larga Permanencia para ancianos. Se utilizaron la escala de fragilidad de Edmonton y un instrumento de recolección de datos basado en Henderson. Se fundamentaron los diagnósticos en la CIPE®, versión 2015. Se analizaron los datos en el software SPSS y Stata presentándolos en tabla. Resultados: se elaboraron 178 diagnósticos de Enfermería de los cuales prevalecieron 15 en más del 20% de la muestra. Se destacaron “Riesgo de Caída” (84,9%), “Visión perjudicada” (49,1%), “Marcha perjudicada” (37,7%), “Insomnio” (28,3%), “Sueño perjudicado” (26,4%), "Humor deprimido" (24,5%) y "Piel seca" (24,5%). Se obtuvo significancia estadística entre "Riesgo de caída" (p = 0,008) y "Piel seca" (p = 0,021) y el nivel de fragilidad. Se observó una correlación entre el número de diagnósticos y el nivel de fragilidad (p <0,001), de modo que, cuanto mayor sea el nivel de fragilidad, más diagnósticos. Conclusión: se elaboraron 178 diagnósticos de Enfermería, de los cuales prevalecieron 15, siendo el "Riesgo de caída" el más prevalente. Se contribuirá con este estudio para divulgar el lenguaje diagnóstico CIPE® y sensibilizar a los enfermeros acerca de la importancia de su uso. Descriptores: Enfermería; Terminología; Diagnóstico de Enfermería; Anciano; Hogares para Ancianos; Fragilidad.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.007

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 head0.056
GPT teacher head0.368
Teacher spread0.312 · 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".

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Citations4
Published2019
Admission routes1
Has abstractyes

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