Computationally-Directed Mechanical Ventilation in a Porcine Model of ARDS

Michaela Kollisch-Singule^1*Andrea F Cruz²Jacob Herrmann²Joshua Satalin³Sarah Satalin⁴Brian P Harvey⁵Dorian LeCroy⁵George Beck⁵Mark Lutz⁴Jacob Charlamb⁴Joshua Kenna⁴Mark Baker⁶Gary Frank Nieman⁴David W Kaczka²

• ¹Arkansas Children's Research Institute (ACRI), Little Rock, United States
• ²The University of Iowa, Iowa City, Iowa, United States
• ³Cornell University, Ithaca, New York, United States
• ⁴Upstate Medical University, Syracuse, New York, United States
• ⁵ZOLL Medical Corporation, Pittsburgh, Pennsylvania, United States
• ⁶State University of New York at Oswego, Oswego, New York, United States

Background: Despite the implementation of protective mechanical ventilation, ventilator-induced lung injury remains a significant driver of ARDS-associated morbidity and mortality. Mechanical ventilation must be personalized and adaptive for the patient and evolving disease course to achieve sustained improvements in patient outcomes. In this study, we modified a military-grade transport ventilator to deliver the airway pressure release ventilation (APRV) modality. We developed a computationally-directed (CD) method of adjusting the expiratory duration (TLow) during APRV using physiologic feedback to reduce alveolar derecruitment and tested this modality in a porcine model of moderate-to-severe ARDS. Methods: Female Yorkshire-cross pigs (n=27) were ventilated using a ZOLL EMV+® 731 Series ventilator during general anesthesia and subjected to a heterogeneous Tween lung injury followed by injurious mechanical ventilation. Animals were subsequently ventilated for six hours under general anesthesia after randomization to one of three groups: VT6 (n=9) with a tidal volume (VT) of 6 mL/kg and stepwise adjustments in PEEP and FiO2; VT10 (n=9) with VT of 10 mL/kg and PEEP of 5 cmH2O; CD-APRV group (n=9) with computationally-directed adjustments in TLow based on a nonlinear equation of motion to describe respiratory mechanics. Results are reported as median [interquartile range.] Results: All groups developed moderate-to-severe ARDS and had similar recovery in lung injury, with all demonstrating final PaO2:FiO2 > 300 mmHg (VT6: 415.5 [383.0-443.4], VT10: 353.3 [297.3-397.7], CD-APRV: 316.6 [269.8-362.4]; p=0.12). PaCO2 was significantly higher in the VT6 group compared with the CD-APRV group (59.3 [52.3-60.1] mmHg vs. 38.5 [32.7-52.2] mmHg, p=0.04) but not significantly different from the VT10 group (47.5 [45.3-54.4] mmHg; p = 0.32 vs. VT6) despite having a significantly higher respiratory rate (30.0 [30.0-32.0] breaths/min) compared with VT10 (12.0 [12.0-15.0] breaths/min, p = 0.001) and CD-APRV (14.0 [14.0-14.0] breaths/min, p < 0.001) groups at the study end. Conclusions: We successfully implemented a computationally directed APRV modality on a transport ventilator, adjusting TLow based on respiratory mechanics. This study demonstrated that CD-APRV can be safely used to protect the lungs, with the advantage of guiding expiratory duration adjustments based on physiologic feedback from the patient's lungs.