Purpose: To evaluate the lung compliance variation over the course of COVID-19 pneumonia, and to classify the patients into different types described as recruitable and non-recruitable, which lead to different ventilator support treatment Method: Two ICU admitted COVID-19 patients, who were mechanically ventilated for more than 7 days, were included into this investigation During a daily recruitment maneuver - a PEEP trial - they were monitored by Electrical Impedance Tomography (EIT) Deflation time constants were calculated offline from EIT data to determine the type of patient and to observe the transition of different types over the course of pneumonia Result: The first patient was recruitable and had the tendency of transition to the other type The second patient is non-recruitable Both patients showed low lung compliance, but the first patient started in a better condition (higher compliance) Conclusion: EIT-based breath-by-breath time constant analysis can classify COVID-19 pneumonia into different classes of patients The deterioration of lung mechanics can be monitored online by EIT which may help to find proper ventilation treatment © 2021, Springer Nature Switzerland AG
EIT Based Time Constant Analysis to Determine Different Types of Patients in COVID-19 Pneumonia