An automated and standardized neural index to quantify patient-ventilator interaction

Abstract

Introduction: The aim of this study was to validate an automated, objective and standardized algorithm for quantifying and displaying patient-ventilator interaction.

Methods: Using a new method to detect patient-ventilator synchrony, the present study re-analyzed previously acquired and published data from 24 mechanically ventilated adult patients (Colombo et al., Crit Care Med. 2011 Nov;39(11):2452-7). Patient-ventilator interactions were evaluated by comparing ventilator pressure and diaphragm electrical activity (EAdi) waveforms, recorded during pressure support ventilation. The EAdi and ventilator pressure waveforms were analyzed for their timings (manually and automatically determined), and the error between the two waveforms was quantified. A new index of patient-ventilator interaction (NeuroSync index), which is standardized and automated, was validated and compared to manual analysis and previously published indices of asynchrony.

Results: The comparison of manual and automated detection methods produced high test-retest and inter-rater reliability (Intraclass correlation coefficient = 0.95). The NeuroSync index increased the sensitivity of detecting dyssynchronies, compared to previously published indices, which were found to only detect asynchronies.

Conclusion: The present study introduces an automated method and the NeuroSync index to determine patient-ventilator interaction with a more sensitive analysis method than those previously described. A dashboard-style of graphical display allows a rapid overview of patient-ventilator interaction and breathing pattern at the bedside.

Figures

Figure 1

Schematic description of the NeuroSync index and graphical display. (A) Time tracing of a schematic electrical activity of the diaphragm (EAdi) signal. Indicators for onset (EAdiON) and termination (EAdiOFF) are presented. Possible range of trigger error (range −100% to 100%, the neural inspiratory detection period) is indicated above the EAdi waveform. Possible range for cycle-off error (−100% to 100%, the neural expiratory detection period) is indicated below the EAdi waveform. (B) Time tracings of schematic ventilator pressure (PV) signals. Six examples of different PV time tracings demonstrate different types of synchronous or dyssynchronous signal (compared to EAdi time tracing in A). (C) Example of signals that are synchronous or dyssynchronous: graphical display. Example 1: a ventilator breath delivered in synchrony with EAdi: EAdiON and start of pressure delivery (PSON) as well as EAdiOFF and end of pressure delivery (PSOFF) occur simultaneously. This event has perfect synchrony (0% error) and is plotted in the center of the graphical display. Example 2: early triggering (PSON occurs at −40% relative to EAdiON) and early cycling-off (PSOFF at −40% relative to EAdiOFF). Events appear outside the box (dyssynchrony) in the lower left quadrant. Example 3: late triggering (PSON occurs at 40% relative to EAdiON) and early cycling-off (PSOFF at −40% relative to EAdiOFF). Events appear outside the box in the upper left quadrant. Example 4: late triggering (PSON occur at 40% relative to EAdiON) and late cycling-off (PSOFF at 40% relative to EAdiOFF). Events appear outside the box in the upper right quadrant. Example 5: early triggering (PSON occur at −40% relative to EAdiON) and late cycling-off (PSOFF at 40% relative to EAdiOFF). Events appear outside the box in the lower right quadrant. Example 6: multiple assist with EAdi (double triggering). First PS assist: early triggering (PSON occurs at −40% relative to EAdiON) and early cycling-off (PSOFF at −40% relative to EAdiOFF), land outside the box in the lower left quadrant (similar to example 2). Second PS assist: late triggering (PSON occurs at 40% relative to EAdiON) and late cycling-off (PSOFF at 40% relative to EAdiOFF) land outside the box in the upper right quadrant (similar to example 4). (D) Example of signals that are asynchronous (that is, 100% error). Example 7 exemplifies assist without EAdi (sometimes known as auto-triggering). Example 8 illustrates EAdi without assist (also known as wasted effort) and multiple EAdi with one assist.

Figure 2

NeuroSyncMANU index in relation to the asynchrony index based on the definition of Colombo et al[4] (AIColombo) and the index for patient-ventilator interaction based on automated algorithms with automated selection of timings (NeuroSyncAUTO). (A) Relationship between the the index for patient-ventilator interaction based on automated algorithms with manual selection of timings (NeuroSyncMANU) (x-axis) and the EAdi-verified asynchrony index (AIColombo) results published by Colombo et al. [4] (y-axis) for all events. Note that the first 40% increase in NeuroSyncMANU is not associated with any change in AIColombo. After about 40% increase in NeuroSyncMANU, the two increase in proportion. The intraclass correlation coefficient between AIColombo and NeuroSyncMANU for all data where the AIColombo exceeds 10% was 0.87. (B) Relationship between the percentage of events that were classified as asynchronous with NeuroSyncMANU (x-axis) and the electrical activity of the diaphragm (EAdi)-verified AIColombo (y-axis). Illustrated NeuroSyncMANU index and AIColombo results were obtained manually by expert analysts verifying onset and termination of inspiratory efforts by EAdi. (C) Relationship between NeuroSync Index calculated with either manual (x-axis) or automatic (y-axis) determination of onset and termination of EAdi.

Figure 3

Examples of patient-ventilator interaction and breathing pattern in three patients. (A-C), top (left) shows a raw tracing of electrical activity of the diaphragm (EAdi) and ventilator pressure (PV). Mid (left), pie-diagram shows the relative distribution of events. Bottom (left), intra-breath patient-ventilator interaction with synchrony (inside the box) and dyssynchrony (outside the box), expressed as percentage of the total number of events. Right, histograms of ventilator and neural respiratory frequency, tidal volume, PV (above positive end-expiratory pressure (PEEP)), and EAdi. (A) Raw tracings in the top panel show clearly distinguishable EAdi and PV waveforms. The pie-diagram shows that almost all breaths (close to 91%) are synchronous. It can be seen that the majority of signals appear inside the box in the upper right quadrant, indicating synchronized assist with a slightly delayed onset and termination of assist relative to the EAdi. The histograms (top to bottom on right side) show that frequency of ventilator-delivered breaths (FV) and of neural (patient) breaths (FN) are stable between 20 to 25 breaths/minute. Tidal volume was 0.4 to 0.5 l at an assist level of 12 to 14 cm H2O above PEEP. EAdi is concentrated in the range of 15 to 20 μV. (B) EAdi and PV waveforms are distinguishable, but it is clear that neural efforts occur more frequently than ventilator breaths. The pie-diagram reveals 50% of the EAdi breaths were not assisted, and 2% of assist occurred without EAdi; 48% of the signals appear in the upper left quadrant outside the box, indicating substantial delays for both onset and termination of assist relative to EAdi. The histograms show that FV occurs at 5 to 15 breaths/minute, whereas FN demonstrates two peaks at 10 and 35 breaths/minute. Tidal volume is 0.4 to 0.6 l at an assist level of 12 to 14 cm H2O above PEEP. EAdi ranges from 5 to 20 μV. (C) The waveforms show that EAdi is infrequent and almost non-distinguishable, whereas PV is clearly distinguishable and frequent. The pie-diagram indicates a 91% of assist without EAdi, 2% of EAdi without assist and only 7% of breaths land inside the box. The histograms show that FV is stable at 14 to 16 breaths/minute, whereas FN is either very low (few breaths) or very high (>60 breaths/minute). Tidal volume is 0.3 to 0.4 l at an assist level of 12 to 14 cm H2O above PEEP. EAdi shows that some breaths reach 12 to 14 μV, but the majority is lower than 2 μV.