Airwave oscillometry to measure lung function in children with Down syndrome

Vielkind, Monica; Hamlington, Katharine L.; Wolter‐Warmerdam, Kristine; Meier, Maxene; Liu, Andrew H.; Hickey, Francis; Brown, Mark A.; DeBoer, Emily M.

doi:10.1038/s41390-021-01664-7

Cited by 5 publications

(1 citation statement)

References 27 publications

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“…Oscillometry is practical because it is effortless and requires very little cooperation, making it easy to perform for both the subject and the operator. This also means that, in contrast to spirometry, it can be performed in a reliable fashion on infants and children (Gray et al, 2019;Lavizzari et al, 2021;Ducharme et al, 2022), as well as on patients who are very sick (i.e., weak) or afflicted by disabilities (Veldhoen et al, 2022;Vielkind et al, 2022) or other conditions where forced expiratory maneuvers are contraindicated (Jordon et al, 2022). Oscillometry is also useful for many reasons.…”

Section: Introductionmentioning

confidence: 99%

Understanding the fundamentals of oscillometry from a strip of lung tissue

Bossé

2022

Front. Physiol.

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Metrics used in spirometry caught on in respiratory medicine not only because they provide information of clinical importance but also because of a keen understanding of what is being measured. The forced expiratory volume in 1 s (FEV1), for example, is the maximal volume of air that can be expelled during the first second of a forced expiratory maneuver starting from a lung inflated to total lung capacity (TLC). Although it represents a very gross measurement of lung function, it is now used to guide the diagnosis and management of many lung disorders. Metrics used in oscillometry are not as concrete. Resistance, for example, has several connotations and its proper meaning in the context of a lung probed by an external device is not always intuitive. I think that the popularization of oscillometry and its firm implementation in respiratory guidelines starts with a keen understanding of what exactly is being measured. This review is an attempt to clearly explain the basic metrics of oscillometry. In my opinion, the fundamentals of oscillometry can be understood using a simple example of an excised strip of lung tissue subjected to a sinusoidal strain. The key notion is to divide the sinusoidal reacting force from the tissue strip into two sinusoids, one in phase with the strain and one preceding the strain by exactly a quarter of a cycle. Similar notions can then be applied to a whole lung subjected to a sinusoidal flow imposed at the mouth by an external device to understand basic metrics of oscillometry, including resistance, elastance, impedance, inertance, reactance and resonant frequency.

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Section: Introductionmentioning

confidence: 99%

Understanding the fundamentals of oscillometry from a strip of lung tissue

Bossé

2022

Front. Physiol.

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Comparison of home‐based spirometry and oscillometry measurements in school‐age children with bronchopulmonary dysplasia

Lee,

Ryan,

Mukharesh

et al. 2024

Pediatric Pulmonology

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IntroductionThis study compares home‐based oscillometry and spirometry for characterizing respiratory system disease in school‐aged children with bronchopulmonary dysplasia (BPD) in clinical research. We hypothesized higher rates of successful completion and abnormal cases identified through oscillometry, with correlations between device measurements.MethodsParticipants 6–12 years old with BPD in the ongoing Air Quality, Environment and Respiratory Outcomes in BPD (AERO‐BPD) study performed oscillometry followed by spirometry at two separate home visits. Parameters measured included airway resistance at 5 Hz(R5), resistance from 5 to 19 Hz(R5‐19), resonance frequency(Fres), reactance at 5 Hz(X5), area under the curve between Fres and X5(AX), forced expiratory volume in 1 second(FEV1), forced vital capacity(FVC), and FEV1/FVC. Descriptive statistics identified the proportion of successful tests, correlation in measurements, and rate of lung disease for each device.ResultsAmong 76 subjects with 120 paired observations, 95% and 71% of participants successfully performed oscillometry and spirometry, respectively, at home visit one. 98% and 77% successfully performed oscillometry and spirometry, respectively, at home visit two. Odds ratios favored oscillometry (range 5.31–10.13, p < 0.01). FEV1 correlated with AX (correlation coefficient r = −0.27, p = 0.03); FEV1/FVC with AX (r = −0.32, p = 0.02); and FEV1/FVC with R5 (r = −0.37, p = 0.01). AX exhibited the highest prevalence of abnormality at 25%; other oscillometry parameters ranged from 5%–22%. Forty‐five to sixty‐four percent of participants had abnormal spirometry. Oscillometry assessments had significantly lower odds of capturing lung disease (odds ratios 0.07–0.24, p < 0.0001).ConclusionsSchool‐aged children with BPD demonstrated higher success rates in field‐based oscillometry than spirometry. Spirometry exhibited higher rates of abnormality than oscillometry. Moderate correlation exists between device measurements.

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