Rationale: Defining lung recruitability is needed for safe positive end-expiratory pressure (PEEP) selection in mechanically ventilated patients. However, there is no simple bedside method including both assessment of recruitability and risks of overdistension as well as personalized PEEP titration. Objectives: To describe the range of recruitability using electrical impedance tomography (EIT), effects of PEEP on recruitability, respiratory mechanics and gas exchange, and a method to select optimal EIT-based PEEP. Methods: This is the analysis of patients with coronavirus disease (COVID-19) from an ongoing multicenter prospective physiological study including patients with moderate-severe acute respiratory distress syndrome of different causes. EIT, ventilator data, hemodynamics, and arterial blood gases were obtained during PEEP titration maneuvers. EIT-based optimal PEEP was defined as the crossing point of the overdistension and collapse curves during a decremental PEEP trial. Recruitability was defined as the amount of modifiable collapse when increasing PEEP from 6 to 24 cm H2O (ΔCollapse24–6). Patients were classified as low, medium, or high recruiters on the basis of tertiles of ΔCollapse24–6. Measurements and Main Results: In 108 patients with COVID-19, recruitability varied from 0.3% to 66.9% and was unrelated to acute respiratory distress syndrome severity. Median EIT-based PEEP differed between groups: 10 versus 13.5 versus 15.5 cm H2O for low versus medium versus high recruitability (P < 0.05). This approach assigned a different PEEP level from the highest compliance approach in 81% of patients. The protocol was well tolerated; in four patients, the PEEP level did not reach 24 cm H2O because of hemodynamic instability. Conclusions: Recruitability varies widely among patients with COVID-19. EIT allows personalizing PEEP setting as a compromise between recruitability and overdistension. Clinical trial registered with www.clinicaltrials.gov (NCT04460859).

Assessing alveolar recruitment at different positive end-expiratory pressure (PEEP) levels is a major clinical and research interest because protective ventilation implies opening the lung without inducing overdistention. The pressure-volume (P-V) curve is a validated method of assessing recruitment but reflects global characteristics, and changes at the regional level may remain undetected. The aim of the present study was to compare, in intubated patients with acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS), lung recruitment measured by P-V curve analysis, with dynamic changes in poorly ventilated units of the dorsal lung (dependent silent spaces [DSSs]) assessed by electrical impedance tomography (EIT). We hypothesized that DSSs might represent a dynamic bedside measure of recruitment. We carried out a prospective interventional study of 14 patients with AHRF and ARDS admitted to the intensive care unit undergoing mechanical ventilation. Each patient underwent an incremental/decremental PEEP trial that included five consecutive phases: PEEP 5 and 10 cmH2O, recruitment maneuver + PEEP 15 cmH2O, then PEEP 10 and 5 cmH2O again. We measured, at the end of each phase, recruitment from previous PEEP using the P-V curve method, and changes in DSS were continuously monitored by EIT. PEEP changes induced alveolar recruitment as assessed by the P-V curve method and changes in the amount of DSS (p < 0.001). Recruited volume measured by the P-V curves significantly correlated with the change in DSS (rs = 0.734, p < 0.001). Regional compliance of the dependent lung increased significantly with rising PEEP (median PEEP 5 cmH2O = 11.9 [IQR 10.4–16.7] ml/cmH2O, PEEP 15 cmH2O = 19.1 [14.2–21.3] ml/cmH2O; p < 0.001), whereas regional compliance of the nondependent lung decreased from PEEP 5 cmH2O to PEEP 15 cmH2O (PEEP 5 cmH2O = 25.3 [21.3–30.4] ml/cmH2O, PEEP 15 cmH2O = 20.0 [16.6–22.8] ml/cmH2O; p <0.001). By increasing the PEEP level, the center of ventilation moved toward the dependent lung, returning to the nondependent lung during the decremental PEEP steps. The variation of DSSs dynamically measured by EIT correlates well with lung recruitment measured using the P-V curve technique. EIT might provide useful information to titrate personalized PEEP. ClinicalTrials.gov, NCT02907840 . Registered on 20 September 2016.

Purpose The European Society of Intensive Care Medicine (ESICM) Green Paper aims to address the challenge of environmental sustainability in intensive care and proposes actionable strategies for integrating sustainability into intensive care unit (ICU) stakeholder actions. Methods The ESICM Executive Committee appointed a task force of topic experts and ESICM committee representatives to develop the ESICM Green Paper. The task force convened biweekly from January to June 2024, identifying key domains for environmental sustainability and prioritizing actions. Drafts were iteratively refined and approved by the ESICM Executive Committee. Results Climate change will impact activities in intensive care in many ways, but also the impact of ICU activities on the environment is considerable; drivers for this include extensive resource use and waste generation in ICUs from energy consumption, use of disposable items, and advanced therapies for critically ill patients. The ESICM Green Paper outlines a structured approach for ICUs to reduce their environmental impact, emphasizing energy efficiency, waste reduction, and sustainable procurement. Furthermore, it endorses the need for awareness and education among healthcare professionals, integration of sustainability into research, and sustainable policies within scientific societies. Conclusions The ESICM Green Paper reviewed the relevance of climate change to intensive care and provided suggestions for clinical practice, research, education, and ESICM organizational domains. It underscores that reducing intensive care's ecological footprint can coexist with high-quality patient care. Promoting a resilient, responsible healthcare system is a joint responsibility of all ICU stakeholders.

Electrical impedance tomography (EIT) is a non-invasive radiation-free monitoring technique that provides images based on tissue electrical conductivity of the chest. Several investigations applied EIT in the context of perioperative medicine, which is not confined to the intraoperative period but begins with the preoperative assessment and extends to postoperative follow-up. EIT could provide careful respiratory monitoring in the preoperative assessment to improve preparation for surgery, during anaesthesia to guide optimal ventilation strategies and to monitor the hemodynamic status and in the postoperative period for early detection of respiratory complications. Moreover, EIT could further enhance care of patients undergoing perioperative diagnostic procedures. This narrative review summarizes the latest evidence on the application of this technique to the surgical patient, focusing also on possible future perspectives. EIT is a promising technique for the perioperative assessment of surgical patients, providing tailored adaptive respiratory and haemodynamic monitoring. Further studies are needed to address the current technological limitations, confirm the findings and evaluate which patients can benefit more from this technology.

The pressure-volume (P-V) curve has been suggested as a bedside tool to set mechanical ventilation; however, it reflects a global behavior of the lung without giving information on the regional mechanical properties. Regional P-V (PVr) curves derived from electrical impedance tomography (EIT) could provide valuable clinical information at bedside, being able to explore the regional mechanics of the lung. In the present study, we hypothesized that regional P-V curves would provide different information from those obtained from global P-V curves, both in terms of upper and lower inflection points. Therefore, we constructed pressure-volume curves for each pixel row from non-dependent to dependent lung regions of patients affected by acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS). We analyzed slow-inflation P-V maneuvers data from 12 mechanically ventilated patients. During the inflation, the pneumotachograph was used to record flow and airway pressure while the EIT signals were recorded digitally. From each maneuver, global respiratory system P-V curve (PVg) and PVr curves were obtained, each one corresponding to a pixel row within the EIT image. PVg and PVr curves were fitted using a sigmoidal equation, and the upper (UIP) and lower (LIP) inflection points for each curve were mathematically identified; LIP and UIP from PVg were respectively called LIPg and UIPg. From each measurement, the highest regional LIP (LIPrMAX) and the lowest regional UIP (UIPrMIN) were identified and the pressure difference between those two points was defined as linear driving pressure (ΔPLIN). A significant difference (p < 0.001) was found between LIPrMAX (15.8 [9.2–21.1] cmH2O) and LIPg (2.9 [2.2–8.9] cmH2O); in all measurements, the LIPrMAX was higher than the corresponding LIPg. We found a significant difference (p < 0.005) between UIPrMIN (30.1 [23.5–37.6] cmH2O) and UIPg (40.5 [34.2–45] cmH2O), the UIPrMIN always being lower than the corresponding UIPg. Median ΔPLIN was 12.6 [7.4–20.8] cmH2O and in 56% of cases was < 14 cmH2O. Regional inflection points derived by EIT show high variability reflecting lung heterogeneity. Regional P-V curves obtained by EIT could convey more sensitive information than global lung mechanics on the pressures within which all lung regions express linear compliance. Clinicaltrials.gov, NCT02907840 . Registered on 20 September 2016.