The power of automated ventilation

Mechanical ventilation is an often–needed and sometimes even life–saving intervention in critically ill patients, but has a strong potential to harm the lung. Lung–protective ventilation could prevent ventilator–induced lung injury (VILI), but its use has challenges. Lung–protective ventilation includes the use of a low tidal volume (VT) and a low driving pressure (ΔP), which is a measure for VT in relation to the respiratory system compliance (CRS). One recent ventilation parameter that receives increasing attention is the mechanical power of ventilation (MP). MP is a summary variable and reflects the amount of energy used to ventilate a patient and the substantial dissipation of energy during invasive ventilation, probably resulting in ‘heat’ or inflammation and therefore potentially leading to VILI. MP has associations with outcome in patients with and without acute respiratory distress syndrome (ARDS). With so many ventilation variables that must be adjusted to achieve lung–protective ventilation, with opposite or non–intuitive effects on MP, it could be difficult to set the ventilator correctly. This could be solved by introducing ‘automated’ or ‘closed–loop’ ventilation modes. One sophisticated mode of closed–loop ventilation is INTELLiVENT–Adaptive Support Ventilation (ASV). This thesis contains studies of closed–loop ventilation and the mechanical power of ventilation (MP). The first part focuses on practical aspects of use of closed–loop ventilation, the second part compares closed–loop ventilation with conventional ventilation with regard to key ventilation parameters and MP and the third part explores which ventilation parameters are needed to prioritize when targeting a low MP

The power of automated ventilation

Mechanical ventilation is an often–needed and sometimes even life–saving intervention in critically ill patients, but has a strong potential to harm the lung. Lung–protective ventilation could prevent ventilator–induced lung injury (VILI), but its use has challenges. Lung–protective ventilation includes the use of a low tidal volume (VT) and a low driving pressure (ΔP), which is a measure for VT in relation to the respiratory system compliance (CRS). One recent ventilation parameter that receives increasing attention is the mechanical power of ventilation (MP). MP is a summary variable and reflects the amount of energy used to ventilate a patient and the substantial dissipation of energy during invasive ventilation, probably resulting in ‘heat’ or inflammation and therefore potentially leading to VILI. MP has associations with outcome in patients with and without acute respiratory distress syndrome (ARDS). With so many ventilation variables that must be adjusted to achieve lung–protective ventilation, with opposite or non–intuitive effects on MP, it could be difficult to set the ventilator correctly. This could be solved by introducing ‘automated’ or ‘closed–loop’ ventilation modes. One sophisticated mode of closed–loop ventilation is INTELLiVENT–Adaptive Support Ventilation (ASV). This thesis contains studies of closed–loop ventilation and the mechanical power of ventilation (MP). The first part focuses on practical aspects of use of closed–loop ventilation, the second part compares closed–loop ventilation with conventional ventilation with regard to key ventilation parameters and MP and the third part explores which ventilation parameters are needed to prioritize when targeting a low MP

Effectiveness, safety and efficacy of INTELLiVENT–adaptive support ventilation, a closed–loop ventilation mode for use in ICU patients–a systematic review

Introduction: INTELLiVENT–Adaptive Support Ventilation (INTELLiVENT–ASV), an advanced closed–loop ventilation mode for use in intensive care unit (ICU) patients, is equipped with algorithms that automatically adjust settings on the basis of physiologic signals and patient’s activity. Here we describe its effectiveness, safety, and efficacy in various types of ICU patients. Areas covered: A systematic search conducted in MEDLINE, EMBASE, the Cochrane Central register of Controlled Trials (CENTRAL), and in Google Scholar identified 10 randomized clinical trials. Expert opinion: Studies suggest INTELLiVENT–ASV to be an effective automated mode with regard to the titrations of tidal volume, airway pressure, and oxygen. INTELLiVENT–ASV is as safe as conventional modes. However, thus far studies have not shown INTELLiVENT–ASV to be superior to conventional modes with regard to duration of ventilation and other patient–centered outcomes. Future studies are needed to test its efficacy

Prognostication using SpO(2)/FiO(2) in invasively ventilated ICU patients with ARDS due to COVID-19-Insights from the PRoVENT-COVID study

Background: The SpO(2)/FiO(2) is a useful oxygenation parameter with prognostic capacity in patients with ARDS. We investigated the prognostic capacity of SpO(2)/FiO(2) for mortality in patients with ARDS due to COVID-19.Methods: This was a post-hoc analysis of a national multicenter cohort study in invasively ventilated patients with ARDS due to COVID-19. The primary endpoint was 28-day mortality.Results: In 869 invasively ventilated patients, 28-day mortality was 30.1%. The SpO(2)/FiO(2) on day 1 had no prognostic value. The SpO(2)/FiO(2) on day 2 and day 3 had prognostic capacity for death, with the best cut-offs being 179 and 199, respectively. Both SpO(2)/FiO(2) on day 2 (OR, 0.66 [95%-CI 0.46-0.96]) and on day 3 (OR, 0.70 [95%-CI 0.51-0.96]) were associated with 28-day mortality in a model corrected for age, pH, lactate levels and kidney dysfunction (AUROC 0.78 [0.76-0.79]). The measured PaO2/FiO(2) and the PaO2/FiO(2) calculated from SpO(2)/FiO(2) were strongly correlated (Spearman's r = 0.79).Conclusions: In this cohort of patients with ARDS due to COVID-19, the SpO(2)/FiO(2) on day 2 and day 3 are independently associated with and have prognostic capacity for 28-day mortality. The SpO(2)/FiO(2) is a useful metric for risk stratification in invasively ventilated COVID-19 patients. (C) 2021 The Authors. Published by Elsevier Inc