Analysis of the nursing diagnosis of [ineffective breathing pattern (00032)] in patients hospitalized with COVID‐19: A cross‐sectional study

The clinical validation of the ineffective breathing pattern diagnosis in the population of individuals infected with SARS-CoV-2 is essential for improving the level of evidence. Additionally, it contributes to the nurse's diagnostic inference in clinical practice and decision making for appropriate treatment.

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Publication Details

Journal
International Journal of Nursing Knowledge
Published
2025-06-18
DOI
https://doi.org/10.1111/2047-3095.70007
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
0.00

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article

Analysis of the nursing diagnosis of [ineffective breathing pattern (00032)] in patients hospitalized with COVID‐19: A cross‐sectional study

Damião da Conceição Araújo, Caio Rodrigo Menezes dos Santos, Thiago de Jesus Santos, Andréia Centenaro Vaez
International Journal of Nursing Knowledge
COVID-19 diagnosis using AI
article

Analysis of the nursing diagnosis of [ineffective breathing pattern (00032)] in patients hospitalized with COVID‐19: A cross‐sectional study

Damião da Conceição Araújo, Caio Rodrigo Menezes dos Santos, Thiago de Jesus Santos, Andréia Centenaro Vaez
article en

Abstract

The clinical validation of the ineffective breathing pattern diagnosis in the population of individuals infected with SARS-CoV-2 is essential for improving the level of evidence. Additionally, it contributes to the nurse's diagnostic inference in clinical practice and decision making for appropriate treatment.

International Journal of Nursing Knowledge
Universidade Federal de Sergipe (BR)
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Universidade Federal de Sergipe
Peace, Justice and strong institutions
Openalex Percentile: Top 79%
COVID-19 diagnosis using AI
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