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Intensive Care Medicine

, Volume 45, Issue 6, pp 856–864 | Cite as

Mechanical power normalized to predicted body weight as a predictor of mortality in patients with acute respiratory distress syndrome

  • Zhongheng ZhangEmail author
  • Bin Zheng
  • Nan Liu
  • Huiqing Ge
  • Yucai Hong
Original

Abstract

Purpose

Protective mechanical ventilation based on multiple ventilator parameters such as tidal volume, plateau pressure, and driving pressure has been widely used in acute respiratory distress syndrome (ARDS). More recently, mechanical power (MP) was found to be associated with mortality. The study aimed to investigate whether MP normalized to predicted body weight (norMP) was superior to other ventilator variables and to prove that the discrimination power cannot be further improved with a sophisticated machine learning method.

Methods

The study included individual patient data from eight randomized controlled trials conducted by the ARDSNet. The data was split 3:1 into training and testing subsamples. The discrimination of each ventilator variable was calculated in the testing subsample using the area under receiver operating characteristic curve. The gradient boosting machine was used to examine whether the discrimination could be further improved.

Results

A total of 5159 patients with acute onset ARDS were included for analysis. The discrimination of norMP in predicting mortality was significantly better than the absolute MP (p = 0.011 for DeLong’s test). The gradient boosting machine was not able to improve the discrimination as compared to norMP (p = 0.913 for DeLong’s test). The multivariable regression model showed a significant interaction between norMP and ARDS severity (p < 0.05). While the norMP was not significantly associated with mortality outcome (OR 0.99; 95% CI 0.91–1.07; p = 0.862) in patients with mild ARDS, it was associated with increased risk of mortality in moderate (OR 1.11; 95% CI 1.02–1.23; p = 0.021) and severe (OR 1.13; 95% CI 1.03–1.24; p < 0.008) ARDS.

Conclusions

The study showed that norMP was a good ventilator variable associated with mortality, and its predictive discrimination cannot be further improved with a sophisticated machine learning method. Further experimental trials are needed to investigate whether adjusting ventilator variables according to norMP will significantly improve clinical outcomes.

Keywords

Acute respiratory distress syndrome Mortality Gradient boosting machine Mechanical power 

Notes

Acknowledgements

We would like to thank Leo M. A. Heunks for reviewing this manuscript and providing insightful comments.

Funding

Z. Z. received funding from Zhejiang Province Public Welfare Technology Application Research Project (CN) (LGF18H150005) and Scientific research project of Zhejiang Education Commission (Y201737841).

Compliance with ethical standards

Conflicts of interest

There is no conflict of interest.

Supplementary material

134_2019_5627_MOESM1_ESM.docx (45 kb)
Supplementary material 1 (DOCX 45 kb)

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Emergency Medicine, Sir Run Run Shaw HospitalZhejiang University School of MedicineHangzhouChina
  2. 2.Department of Surgery, 2D, Walter C Mackenzie Health Sciences CentreUniversity of AlbertaEdmontonCanada
  3. 3.Duke-NUS Medical SchoolNational University of SingaporeSingaporeSingapore
  4. 4.Health Services Research CentreSingapore Health ServicesSingaporeSingapore
  5. 5.Department of Respiratory Care, Sir Run Run Shaw HospitalZhejiang University School of MedicineHangzhouChina

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