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\begin{document}

\title{Counting: an imprecise reference standard for respiratory rate
measurement}



\author[1]{Mark Ansermino J}%
\author[2]{Amy Sarah Ginsburg}%
\author[1]{Dustin Dunsmuir}%
\author[3]{Walter Karlen}%
\author[4]{Heng Gan}%
\author[4]{Catherine Muthoni Njeru}%
\author[1]{Guy Dumont}%
\affil[1]{The University of British Columbia}%
\affil[2]{University of Washington}%
\affil[3]{Universitat Ulm}%
\affil[4]{BC Children's Hospital}%


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  \date{May 27, 2024}


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\begin{abstract}
In response to: Spurr R, Ng E, Onchiri FM, Rapha B, Nakatumba-Nabende J,
Rosenfeld M, Najjingo I, Stout J, Nantanda R, Ellington LE. Performance
and usability of a new mobile application for measuring respiratory rate
in young children with acute lower respiratory infections. Pediatr
Pulmonol. 2022 Aug 22. doi: 10.1002/ppul.26125.%
\end{abstract}%



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To the Editor,

In response to: Spurr R, Ng E, Onchiri FM, Rapha B, Nakatumba-Nabende J,
Rosenfeld M, Najjingo I, Stout J, Nantanda R, Ellington LE. Performance
and usability of a new mobile application for measuring respiratory rate
in young children with acute lower respiratory infections. Pediatr
Pulmonol. 2022 Aug 22. doi: 10.1002/ppul.26125.

Counting: an imprecise reference standard for respiratory rate
measurement

We applaud the authors for critically considering and quantifying
attributes that impact the measured performance characteristics of the
respiratory rate (RR) measurement applications (apps) they
evaluated.\textsuperscript{1} It was not surprising that most of the
variability was attributable to patient RR variability and observer
variability, and that given the accuracy of timing a tap on a smart
phone screen is likely to be within a few
milliseconds,\textsuperscript{2} the measurement apps themselves
contributed minimally (0.6\%) to overall variability. However, a
potential limitation in the comparisons made in this study and also in
some of our previous studies may be due to the variability in the
reference standard. While counting breaths to measure RR has been
practiced by clinicians for decades, this historical reference standard
is problematic. The issue with counting breaths to determine RR is that
the true underlying physiological RR is typically rounded down by the
observer to the nearest breath. As RR is usually distributed close to a
mean of 20 breaths per minute in children, this rounding alone can
result in an average error of 5\%. With an average RR of 55 breaths per
minute among the children in this study, this average error would be
even higher due to the difficulty of an observer counting at this rate.
To account for within-patient RR variability when evaluating the
performance of electronic RR apps, we suggest the inter-breath interval
be measured and summarized as the interval over more than one breath.

When using manual breath counts as the reference standard in their
study, Spurr et al. observed the correlation and proportion classified
as fast breathing with the ALRITE app to be higher in comparison to the
RRate app (Spearman's coefficient 0.83 vs 0.62). This is not unexpected
as the same rounding down was performed in the ALRITE app as with the
visual counting reference standard. In contrast, rather than counting
specific breaths, the RRate app is designed to measure a precise
inter-breath interval and to calculate a RR that represents the median
value of the measured breath intervals.\textsuperscript{3} Thus, this
value is likely to be different from a count over one specific time
interval. When measuring RR, if the intent is to measure the underlying
physiology that is triggering each breath, measuring a breath interval
is likely to be more precise than counting
breaths.\textsuperscript{4}Given that the RRate app's average number of
taps to measure RR in the study was 6, at a median RR of 55, the RRate
measured the RR in 6.5 seconds, and would not be equivalent to a RR
measured over 30 or 60 seconds, especially in infants in whom RR
variability is much higher at faster RRs.\textsuperscript{5} To
facilitate a more accurate comparison of the two RR apps and a more
precise estimate of the repeatability of breath count observations, the
authors could consider measuring the breath intervals by identifying a
specific video frame in the video recordings used in the study for each
breath. The RR could then be calculated using the average time interval
between these breaths. This could also be used to evaluate the precision
of breath counting. In summary, we support the authors in quantifying
attributes that impact the measured performance characteristics of RR
measurement apps and in promoting the simplicity and precision of
touching the screen of a phone to time breathing.

Correction: The RRate app has not been commercialized and the algorithms
are not proprietary and have been made free to everyone, including the
source code.

(https://github.com/part-cw/LNhealth).

\textbf{References}

1. Spurr R, Ng E, Onchiri FM, et al. Performance and usability of a new
mobile application for measuring respiratory rate in young children with
acute lower respiratory infections. \emph{Pediatr Pulmonol} 2022.

2. Ambritta NP, Damini, Bhandwalder HP. A Survey on Real-Time
Application Latency Based on Android OS. \emph{IEEE Xplore: 2018 Fourth
International Conference on Computing Communication Control and
Automation (ICCUBEA)~} 2019: 1-4.

3. Gan H, Karlen W, Dunsmuir D, et al. The Performance of a Mobile Phone
Respiratory Rate Counter Compared to the WHO ARI Timer. \emph{J Healthc
Eng} 2015; \textbf{6} (4): 691-703.

4. Coleman J, Ginsburg AS, Macharia WM, et al. Assessment of neonatal
respiratory rate variability. \emph{J Clin Monit Comput} 2022.

5. Njeru CM, Ansermino JM, Macharia WM, Dunsmuir DT. Variability of
respiratory rate measurements in neonates- every minute counts.\emph{BMC
Pediatr} 2022; \textbf{22} (1): 16.

J Mark Ansermino, MBBCh, The University of British Columbia, Room V364,
British Columbia Children's Hospital Research Institute, ;
anserminos@yahoo.ca

Amy Sarah Ginsburg, MD, MPH, Clinical Trials Center, University of
Washington, Seattle, Washington, United States; messageforamy@gmail.com

Dustin Dunsmuir, MSc, The University of British Columbia, Room V353,
British Columbia Children's Hospital Research Institute, ;
DDunsmuir@cw.bc.ca

Walter Karlen, PhD,, ; walter.karlen@

Heng Gan, MBBCh, Department of Anesthesia, British Columbia Children's
Hospital, Vancouver BC V6H 3V4, Canada; Heng.Gan@cw.bc.ca

Guy Dumont, PhD, The University of British Columbia, Rm V348, British
Columbia Children's Hospital Research Institute, 950 West 28th Ave.,
Vancouver, BC, Canada; guyd@ece.ubc.ca

The authors have no competing interests to declare.

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