4.6 Article

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

期刊

INTENSIVE CARE MEDICINE
卷 45, 期 6, 页码 856-864

出版社

SPRINGER
DOI: 10.1007/s00134-019-05627-9

关键词

Acute respiratory distress syndrome; Mortality; Gradient boosting machine; Mechanical power

资金

  1. Zhejiang Province Public Welfare Technology Application Research Project (CN) [LGF18H150005]
  2. Scientific research project of Zhejiang Education Commission [Y201737841]

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PurposeProtective 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.MethodsThe 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.ResultsA 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.ConclusionsThe 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.

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