Computational simulation indicates that moderately high-frequency ventilation can allow safe reduction of tidal volumes and airway pressures in ARDS patients

Simulation to minimise patient self-inflicted lung injury: are we almost there?

Computational modelling has been used to enlighten pathophysiological issues in patients with acute respiratory distress syndrome (ARDS) using a sophisticated, integrated cardiopulmonary model. COVID-19 ARDS is a pathophysiologically distinct entity characterised by dissociation between impairment in gas exchange and respiratory system mechanics, especially in the early stages of ARDS. Weaver and colleagues used computational modelling to elucidate factors contributing to generation of patient self-inflicted lung injury, and evaluated the effects of various spontaneous respiratory efforts with different oxygenation and ventilatory support modes. Their findings indicate that mechanical forces generated in the lung parenchyma are only counterbalanced when the respiratory support mode reduces the intensity of respiratory efforts.

Modeling Mechanical Ventilation In Silico-Potential and Pitfalls

Computer simulation offers a fresh approach to traditional medical research that is particularly well suited to investigating issues related to mechanical ventilation. Patients receiving mechanical ventilation are routinely monitored in great detail, providing extensive high-quality data-streams for model design and configuration. Models based on such data can incorporate very complex system dynamics that can be validated against patient responses for use as investigational surrogates. Crucially, simulation offers the potential to "look inside" the patient, allowing unimpeded access to all variables of interest. In contrast to trials on both animal models and human patients, in silico models are completely configurable and reproducible; for example, different ventilator settings can be applied to an identical virtual patient, or the same settings applied to different patients, to understand their mode of action and quantitatively compare their effectiveness. Here, we review progress on the mathematical modeling and computer simulation of human anatomy, physiology, and pathophysiology in the context of mechanical ventilation, with an emphasis on the clinical applications of this approach in various disease states. We present new results highlighting the link between model complexity and predictive capability, using data on the responses of individual patients with acute respiratory distress syndrome to changes in multiple ventilator settings. The current limitations and potential of in silico modeling are discussed from a clinical perspective, and future challenges and research directions highlighted.

Physiologic effects of alveolar recruitment and inspiratory pauses during moderately-high-frequency ventilation delivered by a conventional ventilator in a severe lung injury model

Background and aims

To investigate whether performing alveolar recruitment or adding inspiratory pauses could promote physiologic benefits (VT) during moderately-high-frequency positive pressure ventilation (MHFPPV) delivered by a conventional ventilator in a porcine model of severe acute respiratory distress syndrome (ARDS).

Methods

Prospective experimental laboratory study with eight pigs. Induction of acute lung injury with sequential pulmonary lavages and injurious ventilation was initially performed. Then, animals were ventilated on a conventional mechanical ventilator with a respiratory rate (RR) = 60 breaths/minute and PEEP titrated according to ARDS Network table. The first two steps consisted of a randomized order of inspiratory pauses of 10 and 30% of inspiratory time. In final step, we removed the inspiratory pause and titrated PEEP, after lung recruitment, with the aid of electrical impedance tomography. At each step, PaCO₂ was allowed to stabilize between 57–63 mmHg for 30 minutes.

Results

The step with RR of 60 after lung recruitment had the highest PEEP when compared with all other steps (17 [16,19] vs 14 [10, 17]cmH₂O), but had lower driving pressures (13 [13,11] vs 16 [14, 17]cmH₂O), higher P/F ratios (212 [191,243] vs 141 [105, 184] mmHg), lower shunt (23 [20, 23] vs 32 [27, 49]%), lower dead space ventilation (10 [0, 15] vs 30 [20, 37]%), and a more homogeneous alveolar ventilation distribution. There were no detrimental effects in terms of lung mechanics, hemodynamics, or gas exchange. Neither the addition of inspiratory pauses or the alveolar recruitment maneuver followed by decremental PEEP titration resulted in further reductions in VT.

Conclusions

During MHFPPV set with RR of 60 bpm delivered by a conventional ventilator in severe ARDS swine model, neither the inspiratory pauses or PEEP titration after recruitment maneuver allowed reduction of VT significantly, however the last strategy decreased driving pressures and improved both shunt and dead space.