American Journal of Respiratory and Critical Care Medicine

To the Editor:

Current World Health Organization Integrated Management of Childhood Illness guidelines rely on respiratory rate (RR) measurement for childhood pneumonia diagnosis (1). However, an increased RR is not specific to pneumonia and occurs with many different childhood respiratory and febrile conditions (2). Manual RR counting, although widely used, lacks reproducibility and accuracy compared with automated measurements, and can be significantly influenced by user bias (3). Given the increasing interest in automated RR technologies that provide continuous, convenient, noninvasive, and even noncontact estimates of RR, we recently reviewed the wide variety of RR measurement methodologies (4).

The lack of a reliable reference standard for RR measurement is a challenge. A number of reference standards have been proposed, including expert visual or auditory manual count, video recordings with manual or automated extraction of RR, and capnography, yet there is significant uncertainty in all these reference methods. Uncertainty is a characterization of the dispersion of the possible values of a measurement around some unmeasurable true value (5). A clear understanding of the causes and magnitude of uncertainties can ensure that the accuracy of new automated devices is appropriately measured, and that we do not prematurely reject a new device because of inappropriate comparisons to a reference device.

Although we often refer to the use of a “gold standard” when comparing performance of a device with a reference standard, the reality is that all reference device measurements include a degree of uncertainty. The inherent uncertainty resulting from the natural within-subject variation of RR within a measurement period cannot be reduced, but many other uncertainties such as changes in the state (e.g., core or environmental temperature, wakefulness, feeding, talking, or crying) or underlying clinical condition of the subject, human performance (e.g., lack of concentration or inability to clearly visualize breaths in a fast-breathing infant for the full recording period), and rounding of data (e.g., counting breaths for a minute) can be minimized. Uncertainty in reference RR measurement in children is further compounded by developmental changes seen in infancy (6).

In medicine, “agreement” typically describes the closeness between two measurements without designating one as the truth (7). Agreement between measurements includes both systematic and random differences. The tolerance level when comparing reference and investigational devices should be an order of magnitude greater than the random variation observed with the reference device. However, if the reference device is inaccurate, agreement may not guarantee accuracy. Also uncertain is the clinical diagnosis made on RR measurement. A threshold value for RR (per World Health Organization Integrated Management of Childhood Illness, 40 or 50 breaths/min, depending on the child’s age) condenses the clinical diagnosis to a binary outcome (i.e., disease or no disease), not accounting for the measurement or clinical uncertainty. Significant probability exists that a diagnosis based on the threshold is caused by chance alone.

In summary, RR measurement studies would benefit from an uncertainty (probabilistic) approach to the reference standard, including procedures to measure and reduce this uncertainty (5). Continuous RR measurements, rather than single-threshold values, should be used to assess clinical uncertainty and corrections considered for other known covariates such as core body temperature.

1. World Health Organization. Integrated management of childhood illness: chart booklet. Geneva, Switzerland: World Health Organization; 2014.
2. Young Infants Clinical Signs Study Group. Clinical signs that predict severe illness in children under age 2 months: a multicentre study. Lancet 2008;371:135142.
3. Simoes EA, Roark R, Berman S, Esler LL, Murphy J. Respiratory rate: measurement of variability over time and accuracy at different counting periods. Arch Dis Child 1991;66:11991203.
4. Ginsburg AS, Lenahan JL, Izadnegahdar R, Ansermino JM. A systematic review of tools to measure respiratory rate in order to identify childhood pneumonia. Am J Respir Crit Care Med 2018;197:11161127.
5. Joint Committee for Guides in Metrology. Guides to the expression of uncertainty in measurement (GUM) [accessed 2018 Dec 3]. Available from: https://www.iso.org/sites/JCGM/GUM-introduction.htm.
6. MacLean JE, Fitzgerald DA, Waters KA. Developmental changes in sleep and breathing across infancy and childhood. Paediatr Respir Rev 2015;16:276284.
7. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307310.
*Corresponding author (e-mail: ).

Originally Published in Press as DOI: 10.1164/rccm.201812-2266LE on January 23, 2019

Author disclosures are available with the text of this letter at www.atsjournals.org.

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