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BMJ Open Respir Res . Mechanical power is an early predictor of mortality in mechanically ventilated patients with COVID-19

tetano

Editor, Senior Moderator
BMJ Open Respir Res


. 2025 Oct 22;12(1):e003131.
doi: 10.1136/bmjresp-2024-003131. Mechanical power is an early predictor of mortality in mechanically ventilated patients with COVID-19

Uday Rallabhandi[SUP] 1 [/SUP], Clark Walker[SUP] 2 [/SUP], Ann Davis[SUP] 2 [/SUP], J W Hollingsworth[SUP] 3 2 [/SUP]



Affiliations
Abstract

Background: The inherent unpredictability of COVID-19 has compelled clinicians to seek early predictors of in-hospital mortality. This study explored the association between mechanical power and in-hospital mortality in mechanically ventilated COVID-19 patients and provides an evidence-based foundation for mortality prediction.
Study design and methods: A multi-centre, retrospective analysis of 600 mechanically ventilated COVID-19 patients aged 18-98 years at 16 Texas Health Resources hospitals between 2020 and 2023 was conducted. Peak inspiratory pressure, static compliance, plateau pressure, driving pressure and mechanical power were analysed for association with in-hospital mortality. Mechanical power was further categorised to provide clinicians with a straightforward approach for mortality prediction.
Results: The overall in-hospital mortality was 57% (53% to 60%). All five parameters were strongly associated with mortality after adjusting for confounders. In the first 24-hours of mechanical ventilation, 72 patients with mechanical power below 10 J/min had a mortality of 31% (20% to 42%), 159 patients with mechanical power between 10 J/min and 15 J/min had a mortality of 47% (39% to 55%), and 369 patients with mechanical power greater than 15 J/min had a mortality of 66% (61% to 71%). Patients still intubated on day 7 had a 2.1% increase in mortality for each J/min increase in mechanical power.
Conclusion: Mechanical power in the first 24 hours of mechanical ventilation in COVID-19 patients is associated with in-hospital mortality and is useful for clinical prognostication.

Keywords: COVID-19; Critical Care.

 
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