Mechanical power normalized to predicted body weight as a predictor of mortality in patients with acute respiratory distress syndrome
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.
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.
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.
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.
KeywordsAcute respiratory distress syndrome Mortality Gradient boosting machine Mechanical power
We would like to thank Leo M. A. Heunks for reviewing this manuscript and providing insightful comments.
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.
- 5.Network Acute Respiratory Distress Syndrome, Brower RG, Matthay MA et al (2000) Ventilation with lower tidal volumes as compared with traditional tidal volumes for acute lung injury and the acute respiratory distress syndrome. N Engl J Med 342:1301–1308. https://doi.org/10.1056/NEJM200005043421801 CrossRefGoogle Scholar
- 14.The ARDS Network (2000) Ketoconazole for early treatment of acute lung injury and acute respiratory distress syndrome: a randomized controlled trial. J Am Med Assoc 283:1995–2002Google Scholar
- 16.National Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Matthay MA, Brower RG et al (2011) Randomized, placebo-controlled clinical trial of an aerosolized β2-agonist for treatment of acute lung injury. Am J Respir Crit Care Med 184:561–568. https://doi.org/10.1164/rccm.201012-2090OC CrossRefGoogle Scholar
- 18.National Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Rice TW, Wheeler AP et al (2012) Initial trophic vs full enteral feeding in patients with acute lung injury: the EDEN randomized trial. JAMA 307:795–803. https://doi.org/10.1001/jama.2012.137 CrossRefGoogle Scholar
- 21.National Heart, Lung, and Blood Institute Acute Respiratory Distress Syndrome (ARDS) Clinical Trials Network, Wiedemann HP, Wheeler AP et al (2006) Comparison of two fluid-management strategies in acute lung injury. N Engl J Med 354:2564–2575. https://doi.org/10.1056/NEJMoa062200 CrossRefGoogle Scholar
- 22.Zhang Z (2016) Multiple imputation with multivariate imputation by chained equation (MICE) package. Ann Transl Med 4:30. https://doi.org/10.3978/j.issn.2305-5839.2015.12.63 CrossRefGoogle Scholar
- 24.ARDS Definition Task Force, Ranieri VM, Rubenfeld GD et al (2012) Acute respiratory distress syndrome: the Berlin definition. JAMA 307:2526–2533Google Scholar
- 31.Villar J, Martín-Rodríguez C, Domínguez-Berrot AM et al (2017) A quantile analysis of plateau and driving pressures: effects on mortality in patients with acute respiratory distress syndrome receiving lung-protective ventilation. Crit Care Med 45:843–850. https://doi.org/10.1097/CCM.0000000000002330 CrossRefGoogle Scholar
- 37.Fujita Y, Fujino Y, Uchiyama A et al (2007) High peak inspiratory flow can aggravate ventilator-induced lung injury in rabbits. Med Sci Monit 13:BR95–BR100Google Scholar