SOLVe: a closed-loop system focused on protective mechanical ventilation.

BACKGROUND: Mechanical ventilation is an essential component in the treatment of patients with acute respiratory distress syndrome. Prompt adaptation of the settings of a ventilator to the variable needs of patients is essential to ensure personalised and protective ventilation. Still, it is challenging and time-consuming for the therapist at the bedside. In addition, general implementation barriers hinder the timely incorporation of new evidence from clinical studies into routine clinical practice. RESULTS: We present a system combing clinical evidence and expert knowledge within a physiological closed-loop control structure for mechanical ventilation. The system includes multiple controllers to support adequate gas exchange while adhering to multiple evidence-based components of lung protective ventilation. We performed a pilot study on three animals with an induced ARDS. The system achieved a time-in-target of over 75 % for all targets and avoided any critical phases of low oxygen saturation, despite provoked disturbances such as disconnections from the ventilator and positional changes of the subject. CONCLUSIONS: The presented system can provide personalised and lung-protective ventilation and reduce clinician workload in clinical practice.

Induction of severe hypoxemia and low lung recruitability for the evaluation of therapeutic ventilation strategies: a translational model of combined surfactant-depletion and ventilator-induced lung injury.

BACKGROUND: Models of hypoxemic lung injury caused by lavage-induced pulmonary surfactant depletion are prone to prompt recovery of blood oxygenation following recruitment maneuvers and have limited translational validity. We hypothesized that addition of injurious ventilation following surfactant-depletion creates a model of the acute respiratory distress syndrome (ARDS) with persistently low recruitability and higher levels of titrated "best" positive end-expiratory pressure (PEEP) during protective ventilation. METHODS: Two types of porcine lung injury were induced by lung lavage and 3 h of either protective or injurious ventilation, followed by 3 h of protective ventilation (N = 6 per group). Recruitment maneuvers (RM) and decremental PEEP trials comparing oxygenation versus dynamic compliance were performed after lavage and at 3 h intervals of ventilation. Pulmonary gas exchange function, respiratory mechanics, and ventilator-derived parameters were assessed after each RM to map the course of injury severity and recruitability. RESULTS: Lung lavage impaired respiratory system compliance (Crs) and produced arterial oxygen tensions (PaO2) of 84±13 and 80±15 (FIO2 = 1.0) with prompt increase after RM to 270-395 mmHg in both groups. After subsequent 3 h of either protective or injurious ventilation, PaO2/FIO2 was 104±26 vs. 154±123 and increased to 369±132 vs. 167±87 mmHg in response to RM, respectively. After additional 3 h of protective ventilation, PaO2/FIO2 was 120±15 vs. 128±37 and increased to 470±68 vs. 185±129 mmHg in response to RM, respectively. Subsequently, decremental PEEP titration revealed that Crs peaked at 36 ± 10 vs. 25 ± 5 ml/cm H2O with PEEP of 12 vs. 16 cmH2O, and PaO2/FIO2 peaked at 563 ± 83 vs. 334 ± 148 mm Hg with PEEP of 16 vs. 22 cmH2O in the protective vs. injurious ventilation groups, respectively. The large disparity of recruitability between groups was not reflected in the Crs nor the magnitude of mechanical power present after injurious ventilation, once protective ventilation was resumed. CONCLUSION: Addition of transitory injurious ventilation after lung lavage causes prolonged acute lung injury with diffuse alveolar damage and low recruitability yielding high titrated PEEP levels. Mimicking lung mechanical and functional characteristics of ARDS, this porcine model rectifies the constraints of single-hit lavage models and may enhance the translation of experimental research on mechanical ventilation strategies.

The dawn of physiological closed-loop ventilation-a review.

The level of automation in mechanical ventilation has been steadily increasing over the last few decades. There has recently been renewed interest in physiological closed-loop control of ventilation. The development of these systems has followed a similar path to that of manual clinical ventilation, starting with ensuring optimal gas exchange and shifting to the prevention of ventilator-induced lung injury. Systems currently aim to encompass both aspects, and early commercial systems are appearing. These developments remain unknown to many clinicians and, hence, limit their adoption into the clinical environment. This review shows the evolution of the physiological closed-loop control of mechanical ventilation.

Backstepping Control with Radial Basis Function Network for a Nonlinear Cardiopulmonary System.

Oxygen therapy plays a vital role to recover a patient from severe hypoxia as well as to minimize the risk of hypoxia in a critical situation. Based on this therapeutic technique, this article presents an application of backstepping control for the oxygenation in a cardiopulmonary system. A nonlinear multi-compartment system with unknown hysteresis is used as a human model in this study. With no a priori knowledge of the underlying system dynamics, a radial basis function (RBF) network is integrated into a closed-loop subsystem and trained to identify the unknown nonlinear functions. Consequently, a backstepping controller is designed based on the Lyapunov stability theorem for regulating oxygenation. The theoretical framework and simulation are presented and demonstrated in terms of stability and control performance under the presence of simulated physiological changes, possibly caused by pathophysiological effects in the cardiopulmonary system i.e. critically ill patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Closed-loop mechanical ventilation for lung injury: a novel physiological-feedback mode following the principles of the open lung concept.

Adherence to low tidal volume (VT) ventilation and selected positive end-expiratory pressures are low during mechanical ventilation for treatment of the acute respiratory distress syndrome. Using a pig model of severe lung injury, we tested the feasibility and physiological responses to a novel fully closed-loop mechanical ventilation algorithm based on the "open lung" concept. Lung injury was induced by surfactant washout in pigs (n = 8). Animals were ventilated following the principles of the "open lung approach" (OLA) using a fully closed-loop physiological feedback algorithm for mechanical ventilation. Standard gas exchange, respiratory- and hemodynamic parameters were measured. Electrical impedance tomography was used to quantify regional ventilation distribution during mechanical ventilation. Automatized mechanical ventilation provided strict adherence to low VT-ventilation for 6 h in severely lung injured pigs. Using the "open lung" approach, tidal volume delivery required low lung distending pressures, increased recruitment and ventilation of dorsal lung regions and improved arterial blood oxygenation. Physiological feedback closed-loop mechanical ventilation according to the principles of the open lung concept is feasible and provides low tidal volume ventilation without human intervention. Of importance, the "open lung approach"-ventilation improved gas exchange and reduced lung driving pressures by opening atelectasis and shifting of ventilation to dorsal lung regions.

Automatic protective ventilation using the ARDSNet protocol with the additional monitoring of electrical impedance tomography.

INTRODUCTION: Automatic ventilation for patients with respiratory failure aims at reducing mortality and can minimize the workload of clinical staff, offer standardized continuous care, and ultimately save the overall cost of therapy. We therefore developed a prototype for closed-loop ventilation using acute respiratory distress syndrome network (ARDSNet) protocol, called autoARDSNet. METHODS: A protocol-driven ventilation using goal-oriented structural programming was implemented and used for 4 hours in seven pigs with lavage-induced acute respiratory distress syndrome (ARDS). Oxygenation, plateau pressure and pH goals were controlled during the automatic ventilation therapy using autoARDSNet. Monitoring included standard respiratory, arterial blood gas analysis and electrical impedance tomography (EIT) images. After 2-hour automatic ventilation, a disconnection of the animal from the ventilator was carried out for 10 seconds, simulating a frequent clinical scenario for routine clinical care or intra-hospital transport. RESULTS: This pilot study of seven pigs showed stable and robust response for oxygenation, plateau pressure and pH value using the automated system. A 10-second disconnection at the patient-ventilator interface caused impaired oxygenation and severe acidosis. However, the automated protocol-driven ventilation was able to solve these problems. Additionally, regional ventilation was monitored by EIT for the evaluation of ventilation in real-time at bedside with one prominent case of pneumothorax. CONCLUSIONS: We implemented an automatic ventilation therapy using ARDSNet protocol with seven pigs. All positive outcomes were obtained by the closed-loop ventilation therapy, which can offer a continuous standard protocol-driven algorithm to ARDS subjects.

A mathematical model for carbon dioxide elimination: an insight for tuning mechanical ventilation.

PURPOSE: The aim is to provide better understanding of carbon dioxide (CO2) elimination during ventilation for both the healthy and atelectatic condition, derived in a pressure-controlled mode. Therefore, we present a theoretical analysis of CO2 elimination of healthy and diseased lungs. METHODS: Based on a single-compartment model, CO2 elimination is mathematically modeled and its contours were plotted as a function of temporal settings and driving pressure. The model was validated within some level of tolerance on an average of 4.9% using porcine dynamics. RESULTS: CO2 elimination is affected by various factors, including driving pressure, temporal variables from mechanical ventilator settings, lung mechanics and metabolic rate. CONCLUSION: During respiratory care, CO2 elimination is a key parameter for bedside monitoring, especially for patients with pulmonary disease. This parameter provides valuable insight into the status of an atelectatic lung and of cardiopulmonary pathophysiology. Therefore, control of CO2 elimination should be based on the fine tuning of the driving pressure and temporal ventilator settings. However, for critical condition of hypercapnia, airway resistance during inspiration and expiration should be additionally measured to determine the optimal percent inspiratory time (%TI) to maximize CO2 elimination for treating patients with hypercapnia.