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Title: Reduced Unloading in NAVA Improves distribution of Ventilation in ICU patients.
Objectives:
Study Design: Randomised Crossover of Pressure Support and NAVA at different levels of unloading.
Population: Adult Intubated patients at the Neurosurgical ICU, ventilated for more than 48h, in weaning phase from mechanical ventilation.
Study duration: 2,5h Number of subjects: 12
Full description
Critically ill patients on mechanical ventilation are at risk for developing respiratory muscle atrophy. Partial Assist modes such Pressure Support (PS) and Neurally Adjusted Ventilatory Assist (NAVA) are developed to maintain patients´own effort in breathing. However there are no recommendations on how to set the optimal ventilator support in NAVA to avoid over- or underassistance.
A previous Electrical Impedance Thomography (EIT) study has shown a redistribution of ventilation towards the dorsal regions of the lung in acute lung injury patients ventilated with NAVA, compared to PS.
In the present study, the assist is targeted to different respiratory muscle unloading, predefined and based on the Neuro-Ventilatory Efficiency (NVE). The NVE will be measured at 10min intervals and NAVA level adjusted if needed, to keep constant the level of unloading in each study step.
Protocol: Once enrolled, the patients are ventilated in PS (PScli1) as set by the clinician. They are then ventilated in NAVA at 3 different levels of muscle unloading in randomized order. At NAVAcli, the assist level matches to PScli1 in terms of muscle unloading. With NAVA40% and NAVA60%, the patients have 40% and 60% unloading, respectively. In the last study step the patients are back to PS (PScli2). Each patient is his/her own control and goes through the 5 ventilation periods, of 30min each. In the last 5 min of each study step, the CoV (obtained through the EIT data), blood gas samples (for oxygenation and ventilation) and ventilatory parameters are obtained and analyzed.
The investigators hypothesize that
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12 participants in 5 patient groups
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Francesca Campoccia Jalde, MD; Peter V Sackey, MD, PhD
Data sourced from clinicaltrials.gov
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