Electrical impedance tomography during the extubation phase in very preterm born infants.

Neonatology Pub Date : 2025-03-03 DOI:10.1159/000544811
Jantine J Wisse, Tom G Goos, Diederik Gommers, Henrik Endeman, André Kroon, Irwin K M Reiss, Annemijn H Jonkman
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引用次数: 0

Abstract

Introduction Although many preterm born infants require invasive mechanical ventilation, it is also associated with detrimental effects. Early extubation should be pursued, but extubation failure is yet common. The critical transition to non-invasive ventilation is characterized by respiratory physiological changes, warranting non-invasive monitoring. We aimed to determine whether electrical impedance tomography (EIT) could provide insights into the respiratory mechanics of neonates around extubation, and if findings were different between successful and failed extubation. Methods Single-center observational study where EIT and transcutaneous CO2 measurements were performed in preterm born infants <32 weeks gestational age. Measurements were performed from 24 hours before up to 48 hours after extubation. EIT parameters extracted from the hour before and after extubation were analysed to evaluate the short-term physiological changes. Results Twenty-one patients were included and six (29%) were reintubated. End-expiratory lung impedance and tidal impedance variation were stable around extubation (p=0.86 and p=0.47, respectively). Compared to successfully extubated patients, reintubated patients showed more lung inhomogeneity (GI index) after extubation (0.75 vs 0.84, p=0.03). The percentage of non-dependent silent spaces decreased of after extubation in successfully extubated patients (p<0.001). Body position and ventilator mode influenced these findings. Conclusion EIT measurements in preterm neonates provide valuable insight into the respiratory physiology during the transition from invasive to non-invasive ventilation, with significant differences in ventilation distribution and lung homogeneity between successfully extubated and reintubated patients. EIT has the potential to guide personalized respiratory support by assessing ventilation distribution and quantifying inhomogeneity, aiding in the optimization of ventilation settings.

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