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

M.R. van der Kamp; E.C. Klaver; B.J. Thio; J.M.M. Driessen; F.H.C. de Jongh; M. Tabak; J. van der Palen; H.J. Hermens

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, E.C. Klaver, B.J. Thio, J.M.M. Driessen, F.H.C. de Jongh, M. Tabak, J. van der Palen, H.J. Hermens

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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.

Original language	English
Article number	192
Number of pages	1
Journal	BMC medical informatics and decision making
Volume	20
Issue number	1
DOIs	https://doi.org/10.1186/s12911-020-01210-1
Publication status	Published - 14 Aug 2020

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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van der Kamp, M. R., Klaver, E. C., Thio, B. J., Driessen, J. M. M., de Jongh, F. H. C., Tabak, M., van der Palen, J., & Hermens, H. J. (2020). WEARCON: wearable home monitoring in children with asthma reveals a strong association with hospital based assessment of asthma control. BMC medical informatics and decision making, 20(1), Article 192. https://doi.org/10.1186/s12911-020-01210-1

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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, eHealth, Inhaler use, Multivariate analysis, Paediatrics, Physiology sensors, spirometry, Telemedicine, Wearable electronic devices",

author = "{van der Kamp}, M.R. and E.C. Klaver and B.J. Thio and J.M.M. Driessen and {de Jongh}, F.H.C. and M. Tabak and {van der Palen}, J. and H.J. Hermens",

note = "Funding Information: This study was funded by an unrestricted grant from the Stichting Pediatrisch Onderzoek Enschede (SPOE). The funder had no role in the design of the study or the collection, analysis and interpretation of the data. Publisher Copyright: {\textcopyright} 2020 The Author(s).",

year = "2020",

month = aug,

day = "14",

doi = "10.1186/s12911-020-01210-1",

language = "English",

volume = "20",

journal = "BMC medical informatics and decision making",

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T2 - wearable home monitoring in children with asthma reveals a strong association with hospital based assessment of asthma control

AU - van der Kamp, M.R.

AU - Klaver, E.C.

AU - Thio, B.J.

AU - Driessen, J.M.M.

AU - de Jongh, F.H.C.

AU - Tabak, M.

AU - van der Palen, J.

AU - Hermens, H.J.

N1 - Funding Information: This study was funded by an unrestricted grant from the Stichting Pediatrisch Onderzoek Enschede (SPOE). The funder had no role in the design of the study or the collection, analysis and interpretation of the data. Publisher Copyright: © 2020 The Author(s).

PY - 2020/8/14

Y1 - 2020/8/14

N2 - 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.

AB - 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.

KW - Ambulatory monitoring

KW - Asthma control

KW - eHealth

KW - Inhaler use

KW - Multivariate analysis

KW - Paediatrics

KW - Physiology sensors

KW - spirometry

KW - Telemedicine

KW - Wearable electronic devices

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U2 - 10.1186/s12911-020-01210-1

DO - 10.1186/s12911-020-01210-1

M3 - Article

C2 - 32795352

AN - SCOPUS:85089499075

SN - 1472-6947

VL - 20

JO - BMC medical informatics and decision making

JF - BMC medical informatics and decision making

IS - 1

M1 - 192

ER -

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

Abstract

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UN SDGs

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