To extubate or not to extubate: Risk factors for extubation failure and deterioration with further mechanical ventilation-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

To extubate or not to extubate: Risk factors for extubation failure and deterioration with further mechanical ventilation

Published:2019-08-02 Issue:10 Volume:34 Page:1004-1011
ISSN:0886-0440
Container-title:Journal of Cardiac Surgery
language:en
Short-container-title:J Card Surg

Author:

Xie Jingui¹²,Cheng Guang²,Zheng Zhichao³,Luo Haidong⁴^ORCID,Ooi Oon Cheong⁴

Affiliation:

1. The First Affiliated Hospital of USTC, Division of Life Sciences and MedicineUniversity of Science and Technology of China Hefei China

2. School of ManagementUniversity of Science and Technology of China Hefei China

3. Lee Kong Chian School of BusinessSingapore Management University Singapore

4. Department of Cardiac, Thoracic & Vascular SurgeryNational University Hospital Singapore

Publisher

Wiley

Subject

Cardiology and Cardiovascular Medicine,Surgery,Pulmonary and Respiratory Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/jocs.14189

Reference32 articles.

1. The Decision to Extubate in the Intensive Care Unit

2. Risk Factors for and Prediction by Caregivers of Extubation Failure in ICU Patients

3. Variation in extubation failure rates after neonatal congenital heart surgery across Pediatric Cardiac Critical Care Consortium hospitals

4. Extubation Failure in Brain-injured Patients

5. Effect of Failed Extubation on the Outcome of Mechanical Ventilation

Cited by 9 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia;BMC Pulmonary Medicine;2024-07-01

2. Independent Risk Factors of Failed Extubation among Adult Critically Ill Patients: A Prospective Observational Study from Saudi Arabia;Saudi Journal of Medicine & Medical Sciences;2024-06-20

3. Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived parameters;Frontiers in Medicine;2023-05-09

4. Development and validation of a mechanical power-oriented prediction model of weaning failure in mechanically ventilated patients: a retrospective cohort study;BMJ Open;2022-12

5. A machine learning model for prediction of successful extubation in patients admitted to the intensive care unit;2022-08-17

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3