Prediction model development of women's daily asthma control using fitness tracker sleep disruption.


Journal

Heart & lung : the journal of critical care
ISSN: 1527-3288
Titre abrégé: Heart Lung
Pays: United States
ID NLM: 0330057

Informations de publication

Date de publication:
Historique:
received: 09 04 2019
revised: 12 01 2020
accepted: 22 01 2020
pubmed: 25 2 2020
medline: 5 3 2021
entrez: 25 2 2020
Statut: ppublish

Résumé

Night-time wakening with asthma symptoms is an important indicator of disease control and severity, with no gold-standard objective measurement. The study objective was to use fitness tracker sleep data to develop predictive models of daily disease control-related asthma-specific wakening and FEV A repeated measures panel design included data from 43 women with poorly controlled asthma. Two components of asthma control were the primary outcomes, measured daily as (1) self-reported asthma-specific wakening and (2) self-administered spirometry to measure FEV Our models demonstrated predictive value (AUC=0.77) for asthma-specific night-time wakening and good predictive value (AUC=0.83) for daily FEV

Sections du résumé

BACKGROUND
Night-time wakening with asthma symptoms is an important indicator of disease control and severity, with no gold-standard objective measurement.
OBJECTIVE
The study objective was to use fitness tracker sleep data to develop predictive models of daily disease control-related asthma-specific wakening and FEV
METHODS
A repeated measures panel design included data from 43 women with poorly controlled asthma. Two components of asthma control were the primary outcomes, measured daily as (1) self-reported asthma-specific wakening and (2) self-administered spirometry to measure FEV
RESULTS
Our models demonstrated predictive value (AUC=0.77) for asthma-specific night-time wakening and good predictive value (AUC=0.83) for daily FEV

Identifiants

pubmed: 32089295
pii: S0147-9563(20)30017-0
doi: 10.1016/j.hrtlng.2020.01.013
pii:
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

548-555

Subventions

Organisme : NCATS NIH HHS
ID : UL1 TR001412
Pays : United States

Informations de copyright

Copyright © 2020 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest Dr. Castner was committed to receive salary and funding support from the University at Buffalo for this research. Dr. Castner is owner of Castner Incorporated. The remaining authors declare no conflict of interest.

Auteurs

Jessica Castner (J)

The Rockefeller Heilbrunn Family Center for Research Nursing Nurse Scholar, New York, NY, USA; University at Buffalo, Buffalo, NY, USA; Castner Incorporated, Grand Island, NY 14072, USA. Electronic address: jcastner@castnerincorp.com.

Carla R Jungquist (CR)

University at Buffalo School of Nursing, Buffalo, NY, USA.

Manoj J Mammen (MJ)

Department of Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.

John J Pender (JJ)

University at Buffalo School of Nursing Graduate, Buffalo, NY, USA.

Olivia Licata (O)

Department of Biomedical Engineering & Department of Materials Design and Innovation, University at Buffalo School of Engineering and Applied Sciences, Buffalo, NY, USA.

Sanjay Sethi (S)

Department of Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.

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Classifications MeSH