Mechanical Ventilation Strategies Targeting Different Magnitudes of Collapse and Tidal Recruitment in Porcine Acid Aspiration-Induced Lung Injury

Reducing ventilator-associated lung injury by individualized mechanical ventilation (MV) in patients with Acute Respiratory Distress Syndrome (ARDS) remains a matter of research. We randomly assigned 27 pigs with acid aspiration-induced ARDS to three different MV protocols for 24 h, targeting different magnitudes of collapse and tidal recruitment (collapse&TR): the ARDS-network (ARDSnet) group with low positive end-expiratory pressure (PEEP) protocol (permissive collapse&TR); the Open Lung Concept (OLC) group, PaO2/FiO2 >400 mmHg, indicating collapse&TR <10%; and the minimized collapse&TR monitored by Electrical Impedance Tomography (EIT) group, standard deviation of regional ventilation delay, SDRVD. We analyzed cardiorespiratory parameters, computed tomography (CT), EIT, and post-mortem histology. Mean PEEP over post-randomization measurements was significantly lower in the ARDSnet group at 6.8 ± 1.0 cmH2O compared to the EIT (21.1 ± 2.6 cmH2O) and OLC (18.7 ± 3.2 cmH2O) groups (general linear model (GLM) p < 0.001). Collapse&TR and SDRVD, averaged over all post-randomization measurements, were significantly lower in the EIT and OLC groups than in the ARDSnet group (collapse p < 0.001, TR p = 0.006, SDRVD p < 0.004). Global histological diffuse alveolar damage (DAD) scores in the ARDSnet group (10.1 ± 4.3) exceeded those in the EIT (8.4 ± 3.7) and OLC groups (6.3 ± 3.3) (p = 0.16). Sub-scores for edema and inflammation differed significantly (ANOVA p < 0.05). In a clinically realistic model of early ARDS with recruitable and nonrecruitable collapse, mechanical ventilation involving recruitment and high-PEEP reduced collapse&TR and resulted in improved hemodynamic and physiological conditions with a tendency to reduced histologic lung damage.

Artificial intelligence for closed-loop ventilation therapy with hemodynamic control using the open lung concept

Purpose – The purpose of this paper is to develop an automatic control system for mechanical ventilation therapy based on the open lung concept (OLC) using artificial intelligence. In addition, mean arterial blood pressure (MAP) is stabilized by means of a decoupling controller with automated noradrenaline (NA) dosage to ensure adequate systemic perfusion during ventilation therapy for patients with acute respiratory distress syndrome (ARDS). Design/methodology/approach – The aim is to develop an automatic control system for mechanical ventilation therapy based on the OLC using artificial intelligence. In addition, MAP is stabilized by means of a decoupling controller with automated NA dosage to ensure adequate systemic perfusion during ventilation therapy for patients with ARDS. Findings – This innovative closed-loop mechanical ventilation system leads to a significant improvement in oxygenation, regulates end-tidal carbon dioxide for appropriate gas exchange and stabilizes MAP to guarantee proper systemic perfusion during the ventilation therapy. Research limitations/implications – Currently, this automatic ventilation system based on the OLC can only be applied in animal trials; for clinical use, such a system generally requires a mechanical ventilator and sensors with medical approval for humans. Practical implications – For implementation of a closed-loop ventilation system, reliable signals from the sensors are a prerequisite for successful application. Originality/value – The experiment with porcine dynamics demonstrates the feasibility and usefulness of this automatic closed-loop ventilation therapy, with hemodynamic control for severe ARDS. Moreover, this pilot study validated a new algorithm for implementation of the OLC, whereby all control objectives are fulfilled during the ventilation therapy with adequate hemodynamic control of patients with ARDS.