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Clinical evaluation of a novel respiratory rate monitor

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Abstract

Respiratory rate has been shown to be an important predictor of cardiac arrest, respiratory adverse events and intensive care unit admission and has been designated a vital sign. However it is often inadequately monitored in hospitals. We test the hypothesis that RespiraSense, a piezoelectric-based novel respiratory rate (RR) monitor which measures the differential motion of the chest and abdomen during respiratory effort, is not inferior to commonly used methods of respiratory rate measurement. Respiratory rate was compared between the developed RespiraSense device and both electrocardiogram and direct observation by nursing staff. Data was collected from 48 patients admitted to the post-anaesthesia care unit in a tertiary level hospital. The primary outcome measure was difference in average RR calculated over a 15 min interval between (1) RespiraSense and ECG and (2) RespiraSense and nurses’ evaluation. The secondary outcome measure was the correlation between the respiratory rates measured using these three methods. The 95 % confidence interval for the difference in average RR between RespiraSense and ECG was calculated to be [−3.9, 3.1]. The 95 % confidence interval for the difference in average RR between RespiraSense and nurses’ evaluation was [−5.5, 4.3]. We demonstrate a clinically relevant agreement between RR monitored by the RespiraSense device with both ECG-derived and manually observed RR in 48 post-surgical patients in a PACU environment.

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Acknowledgments

The research project would not have occurred without the patient and professional assistance of the nursing staff in the post anaesthesia care unit of Cork University Hospital. This work was funded by PMD Solutions.

Conflict of interest

P.L. has no financial interest in the RespiraSense device or PMD Solutions.

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Correspondence to Peter J. Lee.

Appendix

Appendix

See Table 2.

Table 2 Respiratory rate data

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Lee, P.J. Clinical evaluation of a novel respiratory rate monitor. J Clin Monit Comput 30, 175–183 (2016). https://doi.org/10.1007/s10877-015-9697-4

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  • DOI: https://doi.org/10.1007/s10877-015-9697-4

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