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Observational Study
. 2020 Aug 14;20(1):192.
doi: 10.1186/s12911-020-01210-1.

WEARCON: wearable home monitoring in children with asthma reveals a strong association with hospital based assessment of asthma control

M R van der Kamp  1   2   3 , E C Klaver  4 , B J Thio  4   5 , J M M Driessen  6   7 , F H C de Jongh  8   9 , M Tabak  10   11 , J van der Palen  5   12 , H J Hermens  10   11
Affiliations
Observational Study

WEARCON: wearable home monitoring in children with asthma reveals a strong association with hospital based assessment of asthma control

M R van der Kamp et al. BMC Med Inform Decis Mak. .

Abstract

Background: Asthma is one of the most common chronic diseases in childhood. Regular follow-up of physiological parameters in the home setting, in relation to asthma symptoms, can provide complementary quantitative insights into the dynamics of the asthma status. Despite considerable interest in asthma home-monitoring in children, there is a paucity of scientific evidence, especially on multi-parameter monitoring approaches. Therefore, the aim of this study is to investigate whether asthma control can be accurately assessed in the home situation by combining parameters from respiratory physiology sensors.

Methods: Sixty asthmatic and thirty non-asthmatic children were enrolled in the observational WEARCON-study. Asthma control was assessed according to GINA guidelines by the paediatrician. All children were also evaluated during a 2-week home-monitoring period with wearable devices; a physical activity tracker, a handheld spirometer, smart inhalers, and an ambulatory electrocardiography device to monitor heart and respiratory rate. Multiple logistic regression analysis was used to determine which diagnostic measures were associated with asthma control.

Results: 24 of the 27 uncontrolled asthmatic children and 29 of the 32 controlled asthmatic children could be accurately identified with this model. The final model showed that a larger variation in pre-exercise lung function (OR = 1.34 95%-CI 1.07-1.68), an earlier wake-up-time (OR = 1.05 95%-CI 1.01-1.10), more reliever use (OR = 1.11 95%-CI 1.03-1.19) and a longer respiratory rate recovery time (OR = 1.12 95%-CI 1.05-1.20) were significant contributors to the probability of having uncontrolled asthma.

Conclusions: Home-monitoring of physiological parameters correlates with paediatrician assessed asthma control. The constructed multivariate model identifies 88.9% of all uncontrolled asthmatic children, indicating a high potential for monitoring of asthma control. This may allow healthcare professionals to assess asthma control at home.

Trial registration: Netherlands Trail Register, NL6087 . Registered 14 February 2017.

Keywords: Ambulatory monitoring; Asthma control; Inhaler use; Multivariate analysis; Paediatrics; Physiology sensors; Telemedicine; Wearable electronic devices; eHealth; spirometry.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Schematic overview of the study design. Legend: Schematic overview of the study design; describing the process of recruitment, enrolment, home-monitoring, and grouping based on the outpatient-clinic evaluation
Fig. 2
Fig. 2
The smart monitoring devices. Legend: Smart devices from top-left to bottom-right: MIR spirobank II advanced, Actigraph wGT3X-BT, Cohero Health smart inhalers, eMotion Faros 180
Fig. 3
Fig. 3
Distribution of the monitoring parameters. Legend: The boxplots (median, IQR and extreme values) display the distribution of the four significant contributors (pre-exercise lung function variation, wake-up-time, reliever use and respiratory rate recovery) to the multivariate binary logistic regression model after Markov Chain Monte Carlo imputation. The asterisks indicate significance with p < 0.05, the diamonds indicate significance with p < 0.01
See this image and copyright information in PMC

References

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