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Effect of Refined Perioperative Nursing on the Efficacy of Noninvasive Ventilation in Elderly Patients with Lung Cancer and Respiratory Failure
NIV (noninvasive ventilation) is becoming more popular as a first-line treatment for older patients with lung cancer who are experiencing acute respiratory failure. In the ICU, older age is linked to worse results with mechanical breathing. When dealing with severely sick patients, noninvasive venti...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9217533/ https://www.ncbi.nlm.nih.gov/pubmed/35756083 http://dx.doi.org/10.1155/2022/4711935 |
Sumario: | NIV (noninvasive ventilation) is becoming more popular as a first-line treatment for older patients with lung cancer who are experiencing acute respiratory failure. In the ICU, older age is linked to worse results with mechanical breathing. When dealing with severely sick patients, noninvasive ventilation is beneficial. Due to the risk of NIV failure and the higher mortality induced by delayed intubation, it is difficult to apply to older patients, especially those with lung cancer and respiratory insufficiency. As a result, for a successful outcome, nurse interventions should be provided to patients during noninvasive ventilation. This paper proposes the application of integrated perioperative nursing models on the elderly patients with lung cancer and respiratory failure. We have applied three nursing models: peer support nursing model, multidisciplinary cooperative nursing model, and transcultural nursing theory. The effect of the proposed nursing model on the efficacy of NIV is evaluated using the Logical Decision Tree Regression (LDTR) model. It is optimized using Iterative Fruit Fly Optimization Algorithm (IFOA). The performance of the suggested system is analysed, and it is observed that the patients showed better surgical outcomes when provided with the integrated nursing models. |
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