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BioMed Research International
Volume 2018, Article ID 6820975, 11 pages
Research Article

A Decision for Predicting Successful Extubation of Patients in Intensive Care Unit

1Department of Information Management, Chang Gung University, Taoyuan City, Taiwan
2Department of Thoracic Medicine, Chang Gung Memorial Hospital, Linkou, Taoyuan, Taiwan
3Division of Pulmonary and Critical Care, Department of Internal Medicine, Saint Paul’s Hospital, Taoyuan, Taiwan
4Department of Accounting, Chung Yuan Christian University, Taoyuan, Taiwan
5Department of Industrial Engineering and Management, Ming Chi University of Technology, New Taipei, Taiwan

Correspondence should be addressed to Ching-Ter Chang; wt.ude.ugc.liam@retgnihc

Received 2 August 2017; Revised 8 December 2017; Accepted 16 December 2017; Published 4 January 2018

Academic Editor: Fleur Tehrani

Copyright © 2018 Chang-Shu Tu et al. 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.


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.