Impact of ventilatory modes on the breathing variability in mechanically ventilated infants

Reduction of breathing variability is associated with adverse outcome. During mechanical ventilation, the variability of ventilatory pressure is dependent on the ventilatory mode. During neurally adjusted ventilatory assist (NAVA), the support is proportional to electrical activity of the diaphragm (EAdi), which reflects the respiratory center output. The variability of EAdi is, therefore, translated into a similar variability in pressures. Contrastingly, conventional ventilatory modes deliver less variable pressures. The impact of the mode on the patient's own respiratory drive is less clear. This study aims to compare the impact of NAVA, pressure-controlled ventilation (PCV), and pressure support ventilation (PSV) on the respiratory drive patterns in infants. We hypothesized that on NAVA, EAdi variability resembles most of the endogenous respiratory drive pattern seen in a control group.

Electrical activity of the diaphragm was continuously recorded in 10 infants ventilated successively on NAVA (5 h), PCV (30 min), and PSV (30 min). During the last 10 min of each period, the EAdi variability pattern was assessed using non-rhythmic to rhythmic (NRR) index. These variability profiles were compared to the pattern of a control group of 11 spontaneously breathing and non-intubated infants.

In control infants, NRR was higher as compared to mechanically ventilated infants (p < 0.001), and NRR pattern was relatively stable over time. While the temporal stability of NRR was similar in NAVA and controls, the NRR profile was less stable during PCV. PSV exhibited an intermediary pattern.

Mechanical ventilation impacts the breathing variability in infants. NAVA produces EAdi pattern resembling most that of control infants. NRR can be used to characterize respiratory variability in infants. Larger prospective studies are necessary to understand the differential impact of the ventilatory modes on the cardio-respiratory variability and to study their impact on clinical outcomes.