Abstract:
:Positive end-expiratory pressure (PEEP) can be titrated by electrical impedance tomography (EIT). The aim of the present study was to examine the performance of different EIT measures during PEEP trials with the aim of identifying "optimum" PEEP and to provide possible interpretations of largely diverging results. After recruitment (maximum plateau pressure 35 cmH2O), decremental PEEP trial with steps of 2 cmH2O and duration of 2 min per step was performed. Ventilation gain and loss, the global inhomogeneity (GI) index, trend of end-expiratory lung impedance (EELI) and regional compliance (Creg) for estimation of overdistension and collapse were calculated. Largely diverging results of PEEP selection among the measures were defined as differences ≥ 4 PEEP steps (i.e. ≥ 8 cmH2O). In 30 ARDS patients we examined so far, 3 patients showed significant differences in PEEP selections. Overdistension and collapse estimation based on Creg tended to select lower PEEP while the GI index and EELI trend suggested higher PEEP settings. Regional inspiration times were heterogeneous indicating that the assumption of a uniform driving pressure in the calculation of Creg may not be valid. Judging by the predominant ventilation distribution in the most dependent regions, these patients were non-recruitable with the applied recruitment method or pressure levels. The existence of differences in the recommended PEEP among the analyzed EIT measures might be an indicator of non-recruitable lungs and heterogeneous airway resistances. In these extreme cases, the largely diverging results may prompt the attending clinician to develop individual ventilation strategies.Clinical Trial Registration Registration number NCT03112512, https://clinicaltrials.gov/ Registered 13 April 2017.
journal_name
J Clin Monit Computjournal_title
Journal of clinical monitoring and computingauthors
Zhao Z,Lee LC,Chang MY,Frerichs I,Chang HT,Gow CH,Hsu YL,Möller Kdoi
10.1007/s10877-019-00396-8subject
Has Abstractpub_date
2020-10-01 00:00:00pages
1005-1013issue
5eissn
1387-1307issn
1573-2614pii
10.1007/s10877-019-00396-8journal_volume
34pub_type
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journal_title:Journal of clinical monitoring and computing
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