Towards respiratory muscle-protective mechanical ventilation in the critically ill: technology to monitor and assist physiology

Inadequate delivery of ventilatory assist and unphysiological respiratory drive may severely worsen respiratory muscle function in mechanically ventilated critically ill patients. Diaphragm weakness in these patients is exceedingly common (>60% of patients) and associated with poor clinical outcomes, including difficult ventilator liberation, increased risks of intensive care unit (ICU) and hospital readmission, and mortality. The underlying mechanisms of diaphragm dysfunction were extensively discussed in this thesis. Pathways primarily include the development of diaphragm disuse atrophy due to muscle inactivity or low respiratory drive (strong clinical evidence), and diaphragm injury as a result of excessive breathing effort due to insufficient ventilator assist or excessive respiratory drive (moderate evidence, mostly from experimental work). Excessive breathing effort may also worsen lung injury through pathways that include high lung stress and strain, pendelluft, increased lung perfusion, and patient-ventilator dyssynchrony. Relatively little attention has been paid to the effects of critical illness and mechanical ventilation on the expiratory muscles; however, dysfunction of these muscles has been linked to inadequate central airway clearance and extubation failure. The motivation for performing the work presented in this thesis was the hypothesis that maintaining physiological levels of respiratory muscle activity under mechanical ventilation could prevent or attenuate the development respiratory muscle weakness, and hence, improve patient outcomes. This strategy, integrated with lung-protective ventilation, was recently proposed by international experts from different professional societies (this thesis), and is referred to as a combined lung and diaphragm-protective ventilation approach. Today, an important barrier for implementing and evaluating such an approach is the lack of feasible, reliable and well-understood modalities to assess breathing effort at the bedside, as well as strategies for assisting and restoring respiratory muscle function during mechanical ventilation. Furthermore, monitoring breathing effort is crucial to identify potential relationships between patient management and detrimental respiratory (muscle) function that can be targeted to improve clinical outcomes. In this thesis we identified and improved monitoring modalities for the diaphragm (Part I), we investigated the impact of mechanical ventilation on the respiratory pump, especially the diaphragm (Part II), and we evaluated a novel strategy for maintaining expiratory muscle activity under mechanical ventilation (Part III)

Monitoring patient-ventilator breath contribution in the critically ill during neurally adjusted ventilatory assist: Reliability and improved algorithms for bedside use

The patient-ventilator breath contribution (PVBC) index estimates the relative contribution of the patient to total tidal volume (VTinsp) during mechanical ventilation in neurally adjusted ventilator assist mode and has been used to titrate ventilator support. The reliability of this index in ventilated patients is unknown and was investigated in this study. PVBC was calculated by comparing tidal volume (VTinsp) and diaphragm electrical activity (EAdi) during assisted breaths (VTinsp/EAdi)assist and during unassisted breaths (VTinsp/EAdi)no-assist. VTinsp was normalized to peak EAdi (EAdipeak) using 1) one assisted breath, 2) five consecutive assisted breaths, or 3) five assisted breaths with matching EAdi preceding the unassisted breath ( N1PVBC 2 X5PVBC 2, and X5PVBC EAdi-matching 2 , respectively). In addition, PVBC was calculated by comparing only VTinsp for breaths with matching EAdi (PVBC 2). Test-retest reliability of the different PVBC calculation methods was evaluated with the intraclass correlation coefficient (ICC) using five repeated PVBC maneuvers performed with a 1-min interval. In total, 125 PVBC maneuvers were analyzed in 25 patients. ICC [95% confidence interval] values were 0.46 [0.23– 0.66], 0.51 [0.33– 0.70], and 0.42 [0.14 – 0.69] for N1PVBC 2 X5PVBC 2 X5PVBC EAdi-matching 2 , respectively. Complex waveform analyses showed that insufficient EAdi filtering by the ventilator software affects reliability of PVBC calculation. With our new EAdi-matching techniques reliability improved (PVBC 2 ICC: 0.78 [0.60 – 0.90]). We conclude that current techniques to calculate PVBC exhibit low reliability and that our newly developed criteria and estimation of PVBC— using VT insp of assisted breaths and unassisted breaths with matching EAdi—improves reliability. This may help implementation of PVBC in clinical practice