Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts
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134_2018_5375_ReferencePDF.pdf
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Author(s)
Serpa Neto, Ary
Deliberato, Rodrigo O
Johnson, Alistair E W
Bos, Lieuwe D
Amorim, Pedro
Pereira, Silvio M
Cazati, Denise C
Cordioli, Ricardo L
Correa, Thiago D
Pollard, Tom J
Date Issued
October 5, 2018
Publisher
Springer Berlin Heidelberg
Version
Author's final manuscript
Abstract
Abstract
Purpose
Mechanical power (MP) may unify variables known to be related to development of ventilator-induced lung injury. The aim of this study is to examine the association between MP and mortality in critically ill patients receiving invasive ventilation for at least 48 h.
Methods
This is an analysis of data stored in the databases of the MIMIC–III and eICU. Critically ill patients receiving invasive ventilation for at least 48 h were included. The exposure of interest was MP. The primary outcome was in-hospital mortality.
Results
Data from 8207 patients were analyzed. Median MP during the second 24 h was 21.4 (16.2–28.1) J/min in MIMIC-III and 16.0 (11.7–22.1) J/min in eICU. MP was independently associated with in-hospital mortality [odds ratio per 5 J/min increase (OR) 1.06 (95% confidence interval (CI) 1.01–1.11); p = 0.021 in MIMIC-III, and 1.10 (1.02–1.18); p = 0.010 in eICU]. MP was also associated with ICU mortality, 30-day mortality, and with ventilator-free days, ICU and hospital length of stay. Even at low tidal volume, high MP was associated with in-hospital mortality [OR 1.70 (1.32–2.18); p < 0.001] and other secondary outcomes. Finally, there is a consistent increase in the risk of death with MP higher than 17.0 J/min.
Conclusion
High MP of ventilation is independently associated with higher in-hospital mortality and several other outcomes in ICU patients receiving invasive ventilation for at least 48 h.
MIT Department
Massachusetts Institute of Technology. Institute for Medical Engineering & Science
Harvard--MIT Program in Health Sciences and Technology. Laboratory for Computational Physiology
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DOI of Published Version
https://doi.org/10.1007/s00134-018-5375-6
