Cardiac Health Assessment Using a Wearable Device Before and After Transcatheter Aortic Valve Implantation: Prospective Study.


Journal

JMIR mHealth and uHealth
ISSN: 2291-5222
Titre abrégé: JMIR Mhealth Uhealth
Pays: Canada
ID NLM: 101624439

Informations de publication

Date de publication:
03 Jun 2024
Historique:
received: 25 10 2023
revised: 26 04 2024
accepted: 30 04 2024
medline: 4 6 2024
pubmed: 4 6 2024
entrez: 4 6 2024
Statut: epublish

Résumé

Due to aging of the population, the prevalence of aortic valve stenosis will increase drastically in upcoming years. Consequently, transcatheter aortic valve implantation (TAVI) procedures will also expand worldwide. Optimal selection of patients who benefit with improved symptoms and prognoses is key, since TAVI is not without its risks. Currently, we are not able to adequately predict functional outcomes after TAVI. Quality of life measurement tools and traditional functional assessment tests do not always agree and can depend on factors unrelated to heart disease. Activity tracking using wearable devices might provide a more comprehensive assessment. This study aimed to identify objective parameters (eg, change in heart rate) associated with improvement after TAVI for severe aortic stenosis from a wearable device. In total, 100 patients undergoing routine TAVI wore a Philips Health Watch device for 1 week before and after the procedure. Watch data were analyzed offline-before TAVI for 97 patients and after TAVI for 75 patients. Parameters such as the total number of steps and activity time did not change, in contrast to improvements in the 6-minute walking test (6MWT) and physical limitation domain of the transformed WHOQOL-BREF questionnaire. These findings, in an older TAVI population, show that watch-based parameters, such as the number of steps, do not change after TAVI, unlike traditional 6MWT and QoL assessments. Basic wearable device parameters might be less appropriate for measuring treatment effects from TAVI.

Sections du résumé

Background UNASSIGNED
Due to aging of the population, the prevalence of aortic valve stenosis will increase drastically in upcoming years. Consequently, transcatheter aortic valve implantation (TAVI) procedures will also expand worldwide. Optimal selection of patients who benefit with improved symptoms and prognoses is key, since TAVI is not without its risks. Currently, we are not able to adequately predict functional outcomes after TAVI. Quality of life measurement tools and traditional functional assessment tests do not always agree and can depend on factors unrelated to heart disease. Activity tracking using wearable devices might provide a more comprehensive assessment.
Objective UNASSIGNED
This study aimed to identify objective parameters (eg, change in heart rate) associated with improvement after TAVI for severe aortic stenosis from a wearable device.
Methods UNASSIGNED
In total, 100 patients undergoing routine TAVI wore a Philips Health Watch device for 1 week before and after the procedure. Watch data were analyzed offline-before TAVI for 97 patients and after TAVI for 75 patients.
Results UNASSIGNED
Parameters such as the total number of steps and activity time did not change, in contrast to improvements in the 6-minute walking test (6MWT) and physical limitation domain of the transformed WHOQOL-BREF questionnaire.
Conclusions UNASSIGNED
These findings, in an older TAVI population, show that watch-based parameters, such as the number of steps, do not change after TAVI, unlike traditional 6MWT and QoL assessments. Basic wearable device parameters might be less appropriate for measuring treatment effects from TAVI.

Identifiants

pubmed: 38832585
pii: v12i1e53964
doi: 10.2196/53964
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e53964

Informations de copyright

© Rob Eerdekens, Jo Zelis, Herman ter Horst, Caia Crooijmans, Marcel van 't Veer, Danielle Keulards, Marcus Kelm, Gareth Archer, Titus Kuehne, Guus Brueren, Inge Wijnbergen, Nils Johnson, Pim Tonino. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org).

Auteurs

Rob Eerdekens (R)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

Jo Zelis (J)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

Herman Ter Horst (H)

Philips Research Department, Eindhoven, Netherlands.

Caia Crooijmans (C)

Department of Cardiology, RadboudUMC, Nijmegen, Netherlands.

Marcel van 't Veer (M)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.
Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, Netherlands.

Danielle Keulards (D)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

Marcus Kelm (M)

Deutsches Herzzentrum der Charité, Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany.

Gareth Archer (G)

Department of Cardiology, Sheffield Teaching Hospital, Sheffield, United Kingdom.

Titus Kuehne (T)

Deutsches Herzzentrum der Charité, Institute of Computer-assisted Cardiovascular Medicine, Berlin, Germany.

Guus Brueren (G)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

Inge Wijnbergen (I)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

Nils Johnson (N)

Weatherhead PET Imaging Center for Preventing and Reversing Atherosclerosis, Houston, TX, United States.
Division of Cardiology, Department of Medicine, McGovern Medical School at UTHealth, Houston, TX, United States.

Pim Tonino (P)

Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, Netherlands.

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Classifications MeSH