Estimation of the diaphragm neuromuscular efficiency index in mechanically ventilated critically ill patients

Abstract

Background: Diaphragm dysfunction develops frequently in ventilated intensive care unit (ICU) patients. Both disuse atrophy (ventilator over-assist) and high respiratory muscle effort (ventilator under-assist) seem to be involved. A strong rationale exists to monitor diaphragm effort and titrate support to maintain respiratory muscle activity within physiological limits. Diaphragm electromyography is used to quantify breathing effort and has been correlated with transdiaphragmatic pressure and esophageal pressure. The neuromuscular efficiency index (NME) can be used to estimate inspiratory effort, however its repeatability has not been investigated yet. Our goal is to evaluate NME repeatability during an end-expiratory occlusion (NMEoccl) and its use to estimate the pressure generated by the inspiratory muscles (Pmus).

Methods: This is a prospective cohort study, performed in a medical-surgical ICU. A total of 31 adult patients were included, all ventilated in neurally adjusted ventilator assist (NAVA) mode with an electrical activity of the diaphragm (EAdi) catheter in situ. At four time points within 72 h five repeated end-expiratory occlusion maneuvers were performed. NMEoccl was calculated by delta airway pressure (ΔPaw)/ΔEAdi and was used to estimate Pmus. The repeatability coefficient (RC) was calculated to investigate the NMEoccl variability.

Results: A total number of 459 maneuvers were obtained. At time T = 0 mean NMEoccl was 1.22 ± 0.86 cmH₂O/μV with a RC of 82.6%. This implies that when NMEoccl is 1.22 cmH₂O/μV, it is expected with a probability of 95% that the subsequent measured NMEoccl will be between 2.22 and 0.22 cmH2O/μV. Additional EAdi waveform analysis to correct for non-physiological appearing waveforms, did not improve NMEoccl variability. Selecting three out of five occlusions with the lowest variability reduced the RC to 29.8%.

Conclusions: Repeated measurements of NMEoccl exhibit high variability, limiting the ability of a single NMEoccl maneuver to estimate neuromuscular efficiency and therefore the pressure generated by the inspiratory muscles based on EAdi.

Keywords: Diaphragm dysfunction; Diaphragm electromyography; Mechanical ventilation; Monitoring; Neuromuscular efficiency index; Partially supported mode.

Fig. 1

Example of a single neuromechanical efficiency index during an end-expiratory occlusion (NMEoccl) maneuver. The blue line represents the electrical activity of the diaphragm (EAdi) signal expressed in microvolts. The orange line represents the airway pressure (Paw) expressed in centimeters of water. As described above, the NMEoccl was calculated in three different ways, with the calculation based on (1) delta peak values of electrical activity of the diaphragm (EAdi) and Paw, shown as arrows; (2) area under the curve (AUC) of the EAdi and Paw signal, shown by diagonal lines and gray area, respectively; (3) using fixed points (steps of 3 μV) on the EAdi curve (during inspiration) and corresponding Paw, shown as black dots

Fig. 2

Overview of the correlation of airway pressure (Paw) peak and electrical activity of the diaphragm (EAdi) peak of all maneuvers at time T = 0. Each color represents an individual patient with five repeated measurements (dots) and the corresponding slope (line)

Fig. 3

Four examples of electrical activity of the diaphragm (EAdi) waveform irregularities during an end-expiratory occlusion. The blue line represents the EAdi signal expressed in microvolts. The orange line represent the airway pressure (Paw) expressed in centimeters of water. a Slope < 0 during the ascending part of the EAdi waveform. b Delay in start of EAdi peak. c EAdi peak cut off. d Split EAdi peak

Fig. 4

Overview of correlation between the tension-time index and inspiratory pressure (Pmus) in 15 patients in whom maximum inspiratory pressure was measured (dots). The dotted line represents the cut off for diaphragm fatigue [36]