A non-invasive method to monitor respiratory muscle effort during mechanical ventilation

Purpose This study introduces a method to non-invasively and automatically quantify respiratory muscle effort (P mus ) during mechanical ventilation (MV). The methodology hinges on numerically solving the respiratory system’s equation of motion, utilizing measurements of airway pressure (P aw ) and airflow (F aw ). To evaluate the technique’s effectiveness, P mus was correlated with expected physiological responses. In volume-control (VC) mode, where tidal volume (V T ) is pre-determined, P mus is expected to be linked to P aw fluctuations. In contrast, during pressure-control (PC) mode, where P aw is held constant, P mus should correlate with V T variations. Methods The study utilized data from 250 patients on invasive MV. The data included detailed recordings of P aw and F aw , sampled at 31.25 Hz and saved in 131.1-second epochs, each covering 34 to 41 breaths. The algorithm identified 51,268 epochs containing breaths on either VC or PC mode exclusively. In these epochs, P mus and its pressure-time product (P mus PTP) were computed and correlated with P aw ’s pressure-time product (P aw PTP) and V T , respectively. Results There was a strong correlation of P mus PTP with P aw PTP in VC mode (R² = 0.91 [0.76, 0.96]; n = 17,648 epochs) and with V T in PC mode (R² = 0.88 [0.74, 0.94]; n = 33,620 epochs), confirming the hypothesis. As expected, negligible correlations were observed between P mus PTP and V T in VC mode (R² = 0.03) and between P mus PTP and P aw PTP in PC mode (R² = 0.06). Conclusion The study supports the feasibility of assessing respiratory effort during MV non-invasively through airway signal analysis. Further research is warranted to validate this method and investigate its clinical applications.