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Subject-ventilator synchrony during neural vs. pneumatically triggered non-invasive helmet ventilation Onnen Moerer, Jennifer Beck, Lukas Brander, Roberta Costa, Michael Quintel, Arthur S. Slutsky, Fabrice Brunet, Christer Sinderby

Detailed description of catheter positioning: The EAdi signals are measured with an array of micro-electrodes sensitive to electrical activity, and are situated on a Levin type nasogastric tube (8F for healthy adult experiments). To allow for simple and maintained positioning, the length of the electrode array covers more than a quarter or more of the thorax (in this case 8x16 mm inter-electrode distance = 14.8 cm). The aim is to insert the catheter so the electrode array is positioned at level where the esophagus passes through the crural diaphragm.

The positioning is achieved in three steps. The first step is based on anatomical measurements[1]. The second step is to verify the position of the electrode array by visual inspection of the ECG signals. Normally, signals recorded with electrodes situated within the proximity of the atrium should show P and QRS waves, whereas signals obtained closer to the stomach would lose the P waves and have a weaker QRS complex. The goal therefore is to position the catheter such that P waves and QRS waves are visible on the upper electrode pairs, with a progressive loss in the P wave and QRS wave amplitude. The third step is to verify that there is a signal and if present that the signal coincides with a negative pressure deflection during an airflow occlusion. If the above steps have been fulfilled, and the signal is present, the electrode array can finally be centered over the diaphragm using a visual feedback based on a cross-correlation method [2].

Several physiological studies lasting several hours have been performed with the same methodology [2-6] without any indication of signal deterioration. Currently, commercial implementation of the same electrode design is approved for 5 days.

Detailed description of EAdi signal processing: The EAdi signals from each differential electrode pair were amplified (INA102, Burr-Brown) and high-pass filtered at 10 Hz (single-pole filter) with an antialiasing filter at 1 kHz (D70L8L-1.00 kHz, 8-pole Bessel filter, frequency Devices). Automated and standardized (ATS standardization document) computer algorithms are used to eliminate the influence of electrocardiogram (ECG), electrode motion artifacts, background noise, esophageal peristalsis, and disturbances from the mains. The methods used for EAdi signal processing have been described in detail previously [2,3,7-9]. With these methods, changes in muscle to electrode distance are accounted for [2,3]. Note that the catheter is fixed during this study, and every 16 ms, the most appropriate electrode pairs to be used for processing of EAdi are used. The root mean square value for sequential EAdi segments of 16-ms duration is calculated [4], and a processed EAdi waveform is generated, and used to control the mechanical ventilator. The processed EAdi waveform is also displayed on-line and stored for later analysis.

Determination of maximal EAdi and signal normalization: 1 Due to anatomical variations between subjects, e.g. different distances between the muscle and the electrodes and motor unit density [2] it is not possible to adequately compare absolute levels of EAdi between subjects. In subjects who are able to perform maneuvers following a command, such as healthy subjects, an inspiration to TLC is the most reproducible maneuver that provides the highest maximal voluntary RMS value, which can be used for normalization [8].

Adherence to target respiratory rate and low EAdi: Regarding the subject’s adherence to the experimental protocol, it is worth noting that the helmet does not interrupt flow, and hence it is less disturbing to experience asynchrony in the helmet than with other devices. In the present study, the subjects had a visual display of a time bar indicating the duration of one breathing cycle (Ttot, including both inspiratory and expiratory period) on a computer monitor. The subjects were allowed to choose their Ti/Ttot freely.

On a separate monitor that the subjects could not see, the investigators could observe the subject’s flow pattern, volume, airway pressure, esophageal pressure, as well as the EAdi and the abdominal muscle EMG (See Figure E1). The investigators could also observe the display of the subject’s breathing target, such that in the case where the subject did not follow the target, the investigator could verbally coach the subject. This type of experiment, i.e. targeting a breathing pattern and inspiratory effort, has been frequently practiced in physiology research and is, if properly prepared and supervised, well within the limits of what a healthy volunteer can perform after a short period of training. Evidence for this is the fact that each subject was able to keep the respiratory rate and maintain EAdi at the low level.

Complete description of the protocol: After instrumentation, all subjects were studied in sitting position. The maximum EAdi (EAdimax) was obtained by asking the subject to perform a maximal inspiratory maneuver [8]. A practice period was then performed during which subjects were instructed to follow a specific respiratory rate with a predetermined rate displayed as a time-line on a computer screen. No restrictions were imposed for inspiratory and expiratory times. Subjects were allowed to practice until they were able to maintain the predetermined respiratory rate (RR). During this practice period and maximal inspiratory maneuver, subjects did not receive assist from the ventilator. Following the practice period, the subjects had to repeat periods of breathing on the ventilator with RR of 10, 20, or 30 breaths per minute [bpm]), at pressure support (PS) levels of 5, 10, or 20 cmH2O above PEEP (5 cmH2O) during either neurally (Ntr and Noff) or pneumatically (Ptr and Poff) triggered and cycled off NIPSV. A total of 18 combinations, each 2 minutes in duration, were performed in random order using ballots. Before the 2 minute period of data recording, each subject breathed until the new target respiratory rate and assist level were reached. Each measurement period was followed by two minutes of rest with CPAP of 5 cmH2O. Subjects were not informed about the PS level, and trigger type that was applied. To limit the subjects’ breathing efforts, the inspiratory effort was monitored by the investigators throughout the protocol, and subjects were instructed to lower their inspiratory effort if EAdi exceeded 20% of the voluntary maximum EAdi. Subjects were also instructed to not use expiratory muscles and this was supervised by monitoring the abdominal EMG. Subject comfort of breathing was assessed by a visual analogue scale (VAS) (0 mm = maximal comfort to 100 mm = unbearable) and marked by the subjects themselves at the end of each study period.

2 Complete description of Off-Line Data Analysis: Ntr and Ptr delays were determined by measuring the time between the onset of EAdi and the onset of ventilatory assist using the internal signal of the ventilator. It should be noted that due to periods of ECG replacements and variability in the rate of rise in EAdi, that trigger delays during neurally triggered NIPSV could vary. Noff and Poff were determined by measuring the time between the point where EAdi was reduced to 60% of its peak value and the onset of expiratory flow. To further ensure that efforts were inspiratory, it was verified that each EAdi effort was accompanied by a negative Pes deflection. Mean EAdi was calculated for the unassisted period of inspiration preceding the ventilator’s triggering (EAdiTr) as well as for the entire neural inspiration, i.e. between Ntr and Noff (EAdiinsp). The peak EAdi was calculated for each breath and expressed as a percentage of the maximum EAdi obtained during the maximum inspiratory maneuvers. Mean tidal excursion of Pes (ΔPes) and the pressure time product for the Pes (PTPes) were calculated for the unassisted pre-trigger inspiratory phase (Pestr and PTPestr) and for the entire neural inspiratory period (Pestot and PTPestot). The number of wasted inspiratory efforts, i.e. failure to initiate PSV in the presence of a neural inspiratory effort, was determined by counting all detected increases in EAdi accompanied by negative deflections in Pes that did not trigger the ventilator, and was expressed as percentage of all neural efforts within the same time period. For successfully triggered breaths, asynchrony was calculated over the whole breathing cycle on a breath by breath basis [10,11] and is presented as a percentage of the duration of the neural breath (neuralTtot): (ventilator trigger delay [Delay-on] plus cycling-off delay [Delay- off] divided by neural Ttot x 100). Because it was not possible to match ventilator timing with neural timing in the absence of ventilator assist, wasted inspiratory efforts were counted as 100% asynchrony.

Statistical analysis: Data are presented as median and 25 and 75 percentiles if not stated otherwise. Percentiles were calculated as the weighted average at X(n+1)p. Triggering and cycling-off delays, PTPestot, PTPestr, percentage of wasted inspiratory efforts and comfort of breathing were analyzed for differences between Ptr and Ntr, respiratory rate, and PS-levels, using nonparametric repeated measures analysis [12], corrected for multiple testing by Bonferroni correction. In cases where a significant interaction between the used trigger and pressure support settings was found and for overall comparison between neurally and conventional triggered NIPSV, pair wise comparisons using Wilcoxon test were performed. A p-level < 0.05 was considered to be significant. Correlation between comfort of breathing and the percentage of asynchrony was calculated using the Spearman’s R statistic.

3 Figure E1: Representative tracings monitored on-line in one healthy subject during PSV with the helmet interface with pneumatic triggering (respiratory rate 30, pressure support level 20 cm H2O). From top to bottom, tracings include diaphragm electrical activity (EAdi), surface EMG recording of abdominal muscles (AbdominalEMG), flow, volume, airway opening (Pao), esophageal (Pes), gastric (Pga) and transdiaphragmatic (Pdi) pressures. Note that increases in Pao, Pes, and Pga occur in absence of AbdominalEMG at the same time as the EAdi and Pdi are decreasing. This demonstrates that expiratory muscles are not active but that the ventilator assist and asynchrony cause Pga to increase during expiration.

4 Reference List

1. Ellett ML, Beckstrand J, Flueckiger S, Perkins M, Johnson CS (2005) Predicting the insertion distance for placing gastric tubes 1. Clin Nurs Res 14:11-27-

2. Beck J, Sinderby C, Lindstrom L, Grassino A (1996) Influence of bipolar esophageal electrode positioning on measurements of human crural diaphragm electromyogram. Journal of Applied Physiology 81:1434-1449

3. Beck J, Sinderby C, Weinberg J, Grassino A (1995) Effects of muscle-to-electrode distance on the human diaphragm electromyogram. Journal of Applied Physiology 79:975-985

4. Beck J, Sinderby C, Lindstrom L, Grassino A (1998) Effects of lung volume on diaphragm EMG signal strength during voluntary contractions. J Appl Physiol 85:1123- 1134

5. Beck J, Sinderby C, Lindstrom L, Grassino A (1998) Crural diaphragm activation during dynamic contractions at various inspiratory flow rates. Journal of Applied Physiology 85:451-458

6. Sinderby C, Beck J, Spahija J, de Marchie M, Lacroix J, Navalesi P, Slutsky AS (2007) Inspiratory muscle unloading by neurally adjusted ventilatory assist during maximal inspiratory efforts in healthy subjects. Chest 131:711-717

7. Sinderby CA, Beck JC, Lindstrom LH, Grassino AE (1997) Enhancement of signal quality in esophageal recordings of diaphragm EMG. J Appl Physiol 82:1370-1377

8. Sinderby C, Beck J, Spahija J, Weinberg J, Grassino A (1998) Voluntary activation of the human diaphragm in health and disease. J Appl Physiol 85:2146-2158

9. Sinderby C, Spahija J, Beck J, Kaminski D, Yan S, Comtois N, Sliwinski P (2001) Diaphragm activation during exercise in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 163:1637-1641

10. Beck J, Tucci M, Emeriaud G, Lacroix J, Sinderby C (2004) Prolonged neural expiratory time induced by mechanical ventilation in infants. Pediatr Res 55:747-754

11. Beck J, Campoccia F, Allo JC, Brander L, Brunet F, Slutsky AS, Sinderby C (2007) Improved Synchrony and Respiratory Unloading by Neurally Adjusted Ventilatory Assist (NAVA) in Lung-Injured Rabbits. Pediatr Res 61:289-294

12. Brunner E, Domhof S, Langer F Nonparametric Analysis of Longitudinal Data in Factorial Experiments. John Wiley & Sohns, Inc. New York

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