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A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit
Approximately 40% of patients admitted to the medical intensive care unit (ICU) require mechanical ventilation. An accurate prediction of successful extubation in patients is a key clinical problem in ICU due to the fact that the successful extubation is highly associated with prolonged ICU stay. Th...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5817224/ https://www.ncbi.nlm.nih.gov/pubmed/29511690 http://dx.doi.org/10.1155/2018/6820975 |
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author | Tu, Chang-Shu Chang, Chih-Hao Chang, Shu-Chin Lee, Chung-Shu Chang, Ching-Ter |
author_facet | Tu, Chang-Shu Chang, Chih-Hao Chang, Shu-Chin Lee, Chung-Shu Chang, Ching-Ter |
author_sort | Tu, Chang-Shu |
collection | PubMed |
description | Approximately 40% of patients admitted to the medical intensive care unit (ICU) require mechanical ventilation. An accurate prediction of successful extubation in patients is a key clinical problem in ICU due to the fact that the successful extubation is highly associated with prolonged ICU stay. The prolonged ICU stay is also associated with increasing cost and mortality rate in healthcare system. This study is retrospective in the aspect of ICU. Hence, a total of 41 patients were selected from the largest academic medical center in Taiwan. Our experimental results show that predicting successful rate of 87.8% is obtained from the proposed predicting function. Based on several types of statistics analysis, including logistic regression analysis, discriminant analysis, and bootstrap method, three major successful extubation predictors, namely, rapid shallow breathing index, respiratory rate, and minute ventilation, are revealed. The prediction of successful extubation function is proposed for patients, ICU, physicians, and hospital for reference. |
format | Online Article Text |
id | pubmed-5817224 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-58172242018-03-06 A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit Tu, Chang-Shu Chang, Chih-Hao Chang, Shu-Chin Lee, Chung-Shu Chang, Ching-Ter Biomed Res Int Research Article Approximately 40% of patients admitted to the medical intensive care unit (ICU) require mechanical ventilation. An accurate prediction of successful extubation in patients is a key clinical problem in ICU due to the fact that the successful extubation is highly associated with prolonged ICU stay. The prolonged ICU stay is also associated with increasing cost and mortality rate in healthcare system. This study is retrospective in the aspect of ICU. Hence, a total of 41 patients were selected from the largest academic medical center in Taiwan. Our experimental results show that predicting successful rate of 87.8% is obtained from the proposed predicting function. Based on several types of statistics analysis, including logistic regression analysis, discriminant analysis, and bootstrap method, three major successful extubation predictors, namely, rapid shallow breathing index, respiratory rate, and minute ventilation, are revealed. The prediction of successful extubation function is proposed for patients, ICU, physicians, and hospital for reference. Hindawi 2018-01-04 /pmc/articles/PMC5817224/ /pubmed/29511690 http://dx.doi.org/10.1155/2018/6820975 Text en Copyright © 2018 Chang-Shu Tu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Tu, Chang-Shu Chang, Chih-Hao Chang, Shu-Chin Lee, Chung-Shu Chang, Ching-Ter A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit |
title | A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit |
title_full | A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit |
title_fullStr | A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit |
title_full_unstemmed | A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit |
title_short | A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit |
title_sort | decision for predicting successful extubation of patients in intensive care unit |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5817224/ https://www.ncbi.nlm.nih.gov/pubmed/29511690 http://dx.doi.org/10.1155/2018/6820975 |
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