Identification of adequate neurally adjusted ventilatory assist (NAVA) during systematic increases in the NAVA level

Neurally adjusted ventilatory assist (NAVA) delivers airway pressure (P _aw) in proportion to the electrical activity of the diaphragm (EAdi) using an adjustable proportionality constant (NAVA level, cm·H ₂OμV). During systematic increases in the NAVA level, feedback-controlled down-regulation of the EAdi results in a characteristic two-phased response in P _aw and tidal volume (Vt). The transition from the 1st to the 2nd response phase allows identification of adequate unloading of the respiratory muscles with NAVA (NAVA _AL). We aimed to develop and validate a mathematical algorithm to identify NAVA _AL. P _aw, Vt, and EAdi were recorded while systematically increasing the NAVA level in 19 adult patients. In a multistep approach, inspiratory P _aw peaks were first identified by dividing the EAdi into inspiratory portions using Gaussian mixture modeling. Two polynomials were then fitted onto the curves of both P _aw peaks and Vt. The beginning of the P _aw and Vt plateaus, and thus NAVA _AL, was identified at the minimum of squared polynomial derivative and polynomial fitting errors. A graphical user interface was developed in the Matlab computing environment. Median NAVA _AL visually estimated by 18 independent physicians was 2.7 (range 0.4 to 5.8) cm·H ₂OμV and identified by our model was 2.6 (range 0.6 to 5.0) cm·H ₂OμV. NAVA _AL identified by our model was below the range of visually estimated NAVA _AL in two instances and was above in one instance. We conclude that our model identifies NAVA _AL in most instances with acceptable accuracy for application in clinical routine and research.