Evaluation of the mean airway pressure – Minute ventilation (mM) equation in Spontaneous breathing and its effects on mechanical power
Introduction Mechanical power (MP) incorporates all the variables participating in ventilator-induced lung injury, such as driving pressure (DP), tidal volume, positive end expiratory pressure (PEEP), and respiratory rate (RR), to accurately represents the energy delivered by a mechanical ventila...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Society of Mechanical Ventilation
2025-06-01
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| Series: | Journal of Mechanical Ventilation |
| Subjects: | |
| Online Access: | https://www.journalmechanicalventilation.com/evaluation-of-the-mean-airway-pressure-minute-ventilation-mm-equation-in-spontaneous-breathing-and-its-effects-on-mechanical-power/ |
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| Summary: | Introduction
Mechanical power (MP) incorporates all the variables participating in ventilator-induced lung injury, such as driving pressure (DP), tidal volume, positive end expiratory pressure (PEEP), and respiratory rate (RR), to accurately represents the energy delivered by a mechanical ventilator onto the lungs. Several equations have attempted to simplify the mathematical complexity of calculating MP, one of which being the minute ventilation – mean airway pressure (mM) equation. Although the mM equation is mathematically simple with high accuracy and validity for calculating MP in passive situations, there is no evidence of its accuracy in spontaneous breathing patients. This study assesses the clinical utility of the mM equation on mechanically ventilated patients with spontaneous breathing efforts.
Methods and Statistics
This study utilized the online SIVA simulator to create different ventilation scenarios with various combinations of compliances (10-80 mL/cmH2O) and resistances (5-30 cmH2O/L/s), with various flow and volume rates in the volume controlled (VCV) mode and inspiratory pressures and times in the pressure controlled (PCV) mode. Ventilator variables were manipulated to stimulate different ventilatory scenarios, including respiratory rate (5 – 40 BPM), tidal volume (150 – 700 mL), PEEP (0 – 15 cmH2O), and DP (5 – 30 cmH2O). The variable Pmus was manipulated to demonstrate changes in spontaneous breathing effort (1-20 cmH2O).
Over 30 different combinations of resistances and compliances with 100 different ventilatory settings were created (1500 in each of the two modes). The gold standard method of geometrically deriving the area under the Pressure-Volume curve was used to calculate MP with the SIVA simulator (range 0.1 – 105 J/min). The mM equation calculated from correspondent values of the mean airway pressure and minute ventilation using the SIVA simulator (range 0.37 – 820 cmH2O/L/min).
Results
Pearson correlation showed a very strong correlation between mM and ventilator power (R 0.969), very strong correlation between mM and total power (R 0.963), and strong correlation between mM and Pmus power (R 0.771) within PVC mode, with all demonstrating non-significant differences. Within VCV, Pearson correlation showed a very strong correlation between mM and ventilator power (R 0.963) and strong correlation between mM and total power (R 0.888), but weak correlation between mM and Pmus power (R 0.339).
Conclusion
Mechanical power allows several significant ventilatory parameters to be unified into a single variable, serving as a simplified surrogate to prevent ventilator-induced lung injury. Many equations, including the recent mM equation, reliably calculate mechanical power in pressure-controlled ventilation compared to the gold standard method. However, there was a weak correlation of Pmus power in volume-controlled ventilation, suggesting spontaneous work of breathing of the patient may affect the reproducibility of the mM equation. Future research should explore alternative equations to accurately calculate mechanical power in spontaneous breathing. |
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| ISSN: | 2694-0450 |