Computational models were used to investigate the flow in the upper airway during different types of non-invasive ventilatory assist. High flow nasal cannula (HFNC) ventilatory assist and high velocit..
Computational models were used to investigate the flow in the upper airway during different types of non-invasive ventilatory assist. High flow nasal cannula (HFNC) ventilatory assist and high velocity nasal insufflation (HVNI) were tested. A realistic patient breathing cycle was applied to the base of the trachea. The patient mouth was “closed” to specific percentages by modifying the cross sectional area of a plane in the patient mouth. The total amount of CO2 remaining in the airway was collected as a measure of flush effectiveness for each therapy type. Area-averaged pressure was collected on a plane at the base of the patient trachea. A pressure adjustment factor was developed based on the equation of motion of ventilation to modify the pressure collected at the base of the trachea based on the expected feedback of the lung pressure at this location. The goal of each therapy type was to decrease CO2 remaining (increase CO2 flush) and increase pressure generation in the domain. It was found that HVNI generated higher pressures in the domain and more effectively flushed CO2 from the airway when compared to HFNC, given that all other factors were held constant. When varying mouth position, the lower mouth open percentages caused pressure generation to increase but also caused CO2 flush to decrease (more CO2 retained in the airway). Further study could provide more in-depth analysis of what clinical scenarios may benefit from a patient intentionally modifying their mouth opening percentage to increase one of the desired therapeutic effects.
