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Predictive Factors for Failure of Noninvasive Ventilation in Adult Intensive Care Unit: A Retrospective Clinical Study

Authors :
Liang Li
Wei Li
Tang Yan
Qimin Chen
Lulu Xie
Ming Liu
Daixiu Gao
Wang Ying
Yumei Cheng
Feng Shen
Bo Liu
Ying Liu
Liu Yuanyi
Yu Wu
Xu Liu
Source :
Canadian Respiratory Journal, Canadian Respiratory Journal, Vol 2020 (2020), Canadian respiratory journal, 2020:1324348
Publication Year :
2020
Publisher :
Hindawi Limited, 2020.

Abstract

Background. Noninvasive ventilation (NIV) has been reported to be beneficial for patients with acute respiratory failure in intensive care unit (ICU); however, factors that influence the clinical outcome of NIV were unclarified. We aim to determine the factors that predict the failure of NIV in critically ill patients with acute respiratory failure (ARF). Setting. Adult mixed ICU in a medical university affiliated hospital. Patients and Methods. A retrospective clinical study using data from critical adult patients with initial NIV admitted to ICU in the period August 2016 to November 2017. Failure of NIV was regarded as patients needing invasive ventilation. Logistic regression was employed to determine the risk factor(s) for NIV, and a predictive model for NIV outcome was set up using risk factors. Results. Of 101 included patients, 50 were unsuccessful. Although more than 20 variables were associated with NIV failure, multivariate logistic regression demonstrated that only ideal body weight (IBW) (OR 1.110 (95%1.027–1.201), P=0.009), the maximal heart rate during NIV period (HR-MAX) (OR 1.024 (1.004–1.046), P=0.021), the minimal respiratory rate during NIV period (RR-MIN) (OR 1.198(1.051–1.365), P=0.007), and the highest body temperature during NIV period (T-MAX) (OR 1.838(1.038–3.252), P=0.037) were independent risk factors for NIV failure. We set up a predictive model based on these independent risk factors, whose area under the receiver operating characteristic curve (AUROC) was 0.783 (95% CI: 0.676–0.899, P<0.001), and the sensitivity and specificity of model were 68.75% and 71.43%, respectively, with the optimal cut-off value of 0.4863. Conclusion. IBW, HR-MAX, RR-MIN, and T-MAX were associated with NIV failure in patients with ARF. A predictive model based on the risk factors could help to discriminate patients who are vulnerable to NIV failure.

Details

ISSN :
19167245 and 11982241
Volume :
2020
Database :
OpenAIRE
Journal :
Canadian Respiratory Journal
Accession number :
edsair.doi.dedup.....c6352028b046906cefc6cd9a602cb674