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Monitoring the diaphragm in critically ill patients using electromyography : interpreting the EAdi signal and quantifying patient effort

Boer, E.C. de (2019) Monitoring the diaphragm in critically ill patients using electromyography : interpreting the EAdi signal and quantifying patient effort.

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Abstract:INTRODUCTION: Diaphragm protective ventilation requires monitoring of patient effort. Multiple techniques have been developed to do so, including diaphragmatic electromyography (EAdi) and oesophageal manometry. However, widespread adaptation of these techniques at the bedside is currently limited, due to for instance technical difficulties in signal filtering and complex interpretation of waveforms. In addition, EAdi does not provide a direct measure of breathing effort. Aims of this thesis were to improve understanding of the EAdi signal processing (study 1) and to translate this signal to a functional measure (study 2). At last, this thesis aims to improve the reliability of oesophageal pressure (Pes) measurements (study 3), which are validated using expiratory holds. METHODS: The three studies listed above are tested in mechanically ventilated patients (study 1, n=4 and study 3, n=10) or healthy subjects (study 2, n=15). Study 1 compared the EAdi signal on one hand to electromyograms (EMG) with cardiac artefacts and on the other hand to transdiaphragmatic pressure (Pdi) signals (or Pes if Pdi was not available). As such, it was investigated whether peaks with a small amplitude, that were seen in the EAdi signal, were functional diaphragmatic contractions. Study 2 correlated EAdi to the pressure generated by the respiratory muscles (Pmus), a measure for patient effort. Data were obtained by applying increasing levels of inspiratory threshold loading, ranging from 10% to 80% of maximal Pdi. The relationship was assessed using linear regression. In study 3 a continuous ratio of airway pressure (Paw) and Pes was calculated during patient effort under an expiratory hold. In doing so, the minimal duration of an expiratory hold sufficient to verify Pes measurements was determined. RESULTS: Analysis showed that the small amplitude peaks seen in the EAdi signal are no functional diaphragmatic contractions, but are rather disturbances caused by depolarisation of the heart. Using improved filtering techniques, we found that the correlation between EAdi and breathing effort varied among subjects and could not be predicted using physiological parameters. The correlations did not improve when correcting for flow. Regarding the Pes measurements, the Paw/Pes ratio became close to unity during an expiratory hold after a median of 198 ms [IQR 84-364 ms] after onset of patient effort. This yields a gain in time of 676 ms [IQR 392-828 ms] with regard to applying an expiratory hold until Pes and Paw reach a minimum. CONCLUSION: We conclude that (1) the algorithm of Maquet ventilators to compute EAdi is insufficient in filtering cardiac disturbances. Optimisation of the algorithm improves EAdi signal quality, increasing its reliability and possibly leading to clinical implementation of EAdi monitoring parameters. Furthermore, (2) the EAdi signal cannot yet be used to estimate patient effort at the bedside. Including factors that influence the relationship between EAdi and patient effort, such as thoracoabdominal configuration, might improve the correlation. Last, (3) the duration of an expiratory hold to verify Pes measurements can be reduced. The proposed method might be embedded in the ventilator software, allowing near continuous calculation of the Paw/Pes ratio in the future and hence, improving reliability of Pes measurements.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine, 50 technical science in general
Programme:Technical Medicine MSc (60033)
Link to this item:https://purl.utwente.nl/essays/79603
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