Bedside selection of positive end-expiratory pressure by electrical impedance tomography in hypoxemic patients: a feasibility study

Abstract

Background: Positive end-expiratory pressure (PEEP) is a key element of mechanical ventilation. It should optimize recruitment, without causing excessive overdistension, but controversy exists on the best method to set it. The purpose of the study was to test the feasibility of setting PEEP with electrical impedance tomography in order to prevent lung de-recruitment following a recruitment maneuver. We enrolled 16 patients undergoing mechanical ventilation with PaO₂/FiO₂ <300 mmHg. In all patients, under constant tidal volume (6-8 ml/kg) PEEP was set based on the PEEP/FiO₂ table proposed by the ARDS network (PEEP_ARDSnet). We performed a recruitment maneuver and monitored the end-expiratory lung impedance (EELI) over 10 min. If the EELI signal decreased during this period, the recruitment maneuver was repeated and PEEP increased by 2 cmH₂O. This procedure was repeated until the EELI maintained a stability over time (PEEP_EIT).

Results: The procedure was feasible in 87% patients. PEEP_EIT was higher than PEEP_ARDSnet (13 ± 3 vs. 9 ± 2 cmH₂O, p < 0.001). PaO₂/FiO₂ improved during PEEP_EIT and driving pressure decreased. Recruited volume correlated with the decrease in driving pressure but not with oxygenation improvement. Finally, regional alveolar hyperdistention and collapse was reduced in dependent lung layers and increased in non-dependent lung layers.

Conclusions: In hypoxemic patients, a PEEP selection strategy aimed at stabilizing alveolar recruitment guided by EIT at the bedside was feasible and safe. This strategy led, in comparison with the ARDSnet table, to higher PEEP, improved oxygenation and reduced driving pressure, allowing to estimate the relative weight of overdistension and recruitment.

Keywords: EIT; Overdistension; PEEP; Recruitment.

Fig. 1

PEEP selection by EIT (Panel A and B): After a baseline phase lasting 20 min (PEEP_ARDSnet), a RM was performed (whose duration is shortened in the image for clarity purposes); end-expiratory lung impedance variation (∆EELI) was measured after 30 s (∆EELIstart) and after 10 min (∆EELIend); if ∆EELIend decreased more than 10% of ∆EELIstart, a new RM was performed, and PEEP increased by 2 cmH₂O. This was repeated until ∆EELIend decreased less than 10% of ∆EELIstart, or up to maximum PEEP level of 18 cmH₂O (PEEP_EIT). A new RM was performed and PEEP increased by 2 cmH₂O from PEEP_EIT (PEEP_EIT+2). Unstable EELI track (Panel C): an example of unstable EELI track

Fig. 2

PaO₂/FiO₂ ratio in all study phases. It significantly improved in both PEEP_EIT and PEEP_EIT+2 phases compared with PEEP_ARDSnet. *p < 0.05 compared with PEEP_ARDSnet phase

Fig. 3

Correlation between PEEP and FiO₂ set according to ARDSnet and EIT: As expected, there was a strong correlation between PEEP_ARDSnet and FiO₂ set according to ARDSnet table (R ² = 0.80, p < 0.001); on the contrary, no significant association was observed between PEEP_EIT and predicted FiO₂ (R ² = 0.12, p = 0.217)

Fig. 4

Regional alveolar hyperdistension and collapse distribution in all study phases. Alveolar hyperdistension and collapse was significantly reduced in dependent lung layers and significantly increased in non-dependent lung layers compared with PEEP_ARDSnet in both PEEP_EIT and PEEP_EIT+2 phases. Furthermore, in middle-ventral lung layers alveolar hyperdistension and collapse was significantly higher in PEEP_EIT+2 phase compared with PEEP_ARDSnet, but did not change in PEEP_EIT step. *p < 0.05 compared with PEEP_ARDSnet phase

Fig. 5

Correlations between recruited volume, compliance and oxygenation. The amount of recruited volume did not correlate with oxygenation improvement (R ² = 0.04, p = 0.448), whereas it correlated with the improvement in respiratory system compliance (R ² = 0.50, p < 0.01)