Abstract
BACKGROUND: In mechanically ventilated patients with acute respiratory distress syndrome (ARDS), electrical impedance tomography (EIT) provides information on alveolar cycling and overdistension as well as assessment of recruitability at the bedside. We developed a protocol for individualization of positive end-expiratory pressure (PEEP) and tidal volume (V(T)) utilizing EIT-derived information on recruitability, overdistension and alveolar cycling. The aim of this study was to assess whether the EIT-based protocol allows individualization of ventilator settings without causing lung overdistension, and to evaluate its effects on respiratory system compliance, oxygenation and alveolar cycling. METHODS: 20 patients with ARDS were included. Initially, patients were ventilated according to the recommendations of the ARDS Network with a V(T) of 6 ml per kg predicted body weight and PEEP adjusted according to the lower PEEP/FiO(2) table. Subsequently, ventilator settings were adjusted according to the EIT-based protocol once every 30 min for a duration of 4 h. To assess global overdistension, we determined whether lung stress and strain remained below 27 mbar and 2.0, respectively. RESULTS: Prospective optimization of mechanical ventilation with EIT led to higher PEEP levels (16.5 [14-18] mbar vs. 10 [8-10] mbar before optimization; p = 0.0001) and similar V(T) (5.7 ± 0.92 ml/kg vs. 5.8 ± 0.47 ml/kg before optimization; p = 0.96). Global lung stress remained below 27 mbar in all patients and global strain below 2.0 in 19 out of 20 patients. Compliance remained similar, while oxygenation was significantly improved and alveolar cycling was reduced after EIT-based optimization. CONCLUSIONS: Adjustment of PEEP and V(T) using the EIT-based protocol led to individualization of ventilator settings with improved oxygenation and reduced alveolar cycling without promoting global overdistension. Trial registrationThis study was registered at clinicaltrials.gov (NCT02703012) on March 9, 2016 before including the first patient.