Advice

Clinical and technical evidence

Clinical and technical evidence

A literature search was carried out for this briefing in accordance with the interim process and methods statement for medtech innovation briefings. This briefing includes the most relevant or best available published evidence relating to the clinical effectiveness of the technology. Further information about how the evidence for this briefing was selected is available on request by contacting mibs@nice.org.uk.

Published evidence

There are 3 studies summarised in this briefing, including a total of 106 people. The evidence includes 1 retrospective observational study and 2 validation studies.

In addition, there are further abstracts evaluating the accuracy and acceptability of RespiraSense in a bariatric setting (Albom et al. 2019 and Albom 2022) and a cost–utility analysis comparing the technology with intermittent nurse-led monitoring for pneumonia (Javanbakht et al. 2021) that are not included in this briefing.

The clinical evidence and its strengths and limitations is summarised in the overall assessment of the evidence.

Overall assessment of the evidence

The evidence base for RespiraSense is limited and comes from single-centre observational studies that involve a relatively small number of people. Two studies are validation studies comparing RespiraSense with the industry standard (nurse-led manual counting). Only 1 of these compared the technology with the 'gold standard' capnography. Only 1 study included clinically relevant outcomes and only 1 study was done in the UK. The evidence suggests that RespiraSense can be used to continuously measure respiratory rate in an acute hospital setting and may be able to predict hypoxic and pyrexic events. One study reported that it was also easy to use and well tolerated. Further evidence would benefit from larger multicentre randomised controlled trials looking at the clinical significance of early detection of changes in respiratory rate and how this influences escalation or de-escalation of treatment for acutely ill adults.

McCartan et al. (2021)

Intervention and comparator

Electronically measured respiratory rate (EMRR) using RespiraSense compared with visually measured respiratory rate (VMRR).

Key outcomes

A total of 3,445 visual and 729,117 electronic respiratory rate measurements were recorded from 34 people. The distribution characteristics of VMRR compared with EMRR were significantly different in Wilcoxon signed-rank test (p<0.0001; z=6.001). Of all measurements taken at the same time, 37.7% of VMRR were above the corresponding EMRR value, 12.2% were the same and 52.1% were below. The mean difference between EMRR and VMRR was 1.3 (standard deviation [SD] 4.6), with EMRR being larger on average. The dataset contained 59 hypoxic events affecting 14 people, and 27 pyrexic events affecting 10 people. An elevated EMRR was predictive of hypoxic (hazard ratio 1.8 [1.05 to 3.07]) and pyrexic (hazard ratio 9.7 [3.8 to 25]) episodes over the following 12 hours. A total of 70.6% of people would have had a change of treatment during their admission based on the UK's National Early Warning System if EMRR was used in place of VMRR.

Strengths and limitations

This study was done retrospectively and had a small sample size. Some comorbidity data was collected, but there was not enough to establish the effect that comorbidities may have on electronic respiratory rate measurements. Healthcare professionals taking visual measurements of respiratory rate were unaware that their measurements would be studied, reducing the chance of observer bias.

Lee (2016)

Intervention and comparator

RespiraSense compared with electrocardiogram (ECG), and manual observation by nursing staff.

Key outcomes

Out of a total of 144 recorded data points, 115 time points were available for analysis. The remaining 29 time points were lost because of delays in connecting the ECG monitor, laptop shutdown, disconnection of the RespiraSense device and failure of ECG to generate meaningful respiratory rate data. The mean difference for average respiratory rate between RespiraSense and ECG was less than 1 beat per minute (bpm), mean (SD) was -0.41 (1.79). The 95% confidence interval for the difference in average was -3.9 to 3.1, which did not exclude the clinically relevant difference of 3 bpm. The difference was greater than 3 bpm for 9 intervals (7.8%). The mean difference for average respiratory rate between RespiraSense and the nurse evaluation was less than 1 bpm, mean (SD) was -0.58 (2.50). The 95% confidence interval for the difference in average respiratory rate was -5.5 to 4.3, which does not exclude the clinically relevant difference of 3 bpm. The difference was greater than 3 bpm for 23 intervals (20%). Only 3 of the 23 intervals also showed a difference of greater than 3 bpm in average respiratory rate for RespiraSense compared with ECG. RespiraSense and ECG had a Pearson product-moment correlation coefficient of 0.84, and RespiraSense and nurse evaluation had a Pearson product-moment correlation coefficient of 0.78. Using a verbal rating scale, all patients rated RespiraSense as 10 out of 10 for comfort, and all nurses rated it 10 out of 10 for ease of use.

Strengths and limitations

This study suggests that RespiraSense measures respiratory rates with clinically relevant agreement with those from ECG and manual measurements taken by nursing staff. Limitations of the study include lack of blinding, and lack of comparison to a 'gold standard' for respiratory rate monitoring.

Subbe and Kinsella (2018)

Intervention and comparator

RespiraSense compared with capnography, and manual counting of respiratory rate.

Key outcomes

Data from 17 out of 24 people was included in the study analysis. There were 62 data points available from the primary end point. At rest, RespiraSense had a mean respiratory rate of 19.8 (SD 4.52), compared with 20.2 (SD 4.54) for capnography and 19.3 (SD 4.89) for manual counting. At rest, RespiraSense had a bias of 0.38 and limits of agreement of 1.0 to 1.8 bpm when compared with capnography (R2=0.99), and a bias of -0.70 and limits of agreement of -4.9 to 3.5 bpm when compared with manual counting (R2=0.90). Agreement of measurements was within pre-defined limits for capnography compared with RespiraSense. Respiratory rate was also measured during a period with permission of movement. During this period, RespiraSense had a mean respiratory rate of 21.1 (SD 4.15) compared with 19.34 (SD 4.61) for manual counting. With movement, RespiraSense had a bias of -1.72 and limits of agreement of -6.8 to 3.3 bpm when compared with manual counting (R2=0.83).

Strengths and limitations

This study suggests that RespiraSense delivers measurement of respiratory rate comparable to capnography and manual counting at rest. The main limitation of this study is the lack of randomisation, which increases the risk of selection bias. The study was funded by PMD Solutions.

Sustainability

The company claims that the technology could reduce the number of care miles travelled when used in a community setting. There is no published evidence to support these claims.

Recent and ongoing studies