Continuous Digital Monitoring of Walking Speed in Frail Elderly Patients: Noninterventional Validation Study and Longitudinal Clinical Trial.


Journal

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

Informations de publication

Date de publication:
27 11 2019
Historique:
received: 26 06 2019
accepted: 24 09 2019
revised: 09 09 2019
entrez: 28 11 2019
pubmed: 28 11 2019
medline: 17 9 2020
Statut: epublish

Résumé

Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health-relevant data from patients. However, only limited data and results have been published that demonstrate accuracy in target indications, real-world feasibility, or the validity and value of these novel approaches. This study aimed to establish accuracy, feasibility, and validity of continuous digital monitoring of walking speed in frail, elderly patients with sarcopenia and to create an open source repository of raw, derived, and reference data as a resource for the community. Data described here were collected as a part of 2 clinical studies: an independent, noninterventional validation study and a phase 2b interventional clinical trial in older adults with sarcopenia. In both studies, participants were monitored by using a waist-worn inertial sensor. The cross-sectional, independent validation study collected data at a single site from 26 naturally slow-walking elderly subjects during a parcours course through the clinic, designed to simulate a real-world environment. In the phase 2b interventional clinical trial, 217 patients with sarcopenia were recruited across 32 sites globally, where patients were monitored over 25 weeks, both during and between visits. We have demonstrated that our approach can capture in-clinic gait speed in frail slow-walking adults with a residual standard error of 0.08 m per second in the independent validation study and 0.08, 0.09, and 0.07 m per second for the 4 m walk test (4mWT), 6-min walk test (6MWT), and 400 m walk test (400mWT) standard gait speed assessments, respectively, in the interventional clinical trial. We demonstrated the feasibility of our approach by capturing 9668 patient-days of real-world data from 192 patients and 32 sites, as part of the interventional clinical trial. We derived inferred contextual information describing the length of a given walking bout and uncovered positive associations between the short 4mWT gait speed assessment and gait speed in bouts between 5 and 20 steps (correlation of 0.23) and longer 6MWT and 400mWT assessments with bouts of 80 to 640 steps (correlations of 0.48 and 0.59, respectively). This study showed, for the first time, accurate capture of real-world gait speed in slow-walking older adults with sarcopenia. We demonstrated the feasibility of long-term digital monitoring of mobility in geriatric populations, establishing that sufficient data can be collected to allow robust monitoring of gait behaviors outside the clinic, even in the absence of feedback or incentives. Using inferred context, we demonstrated the ecological validity of in-clinic gait assessments, describing positive associations between in-clinic performance and real-world walking behavior. We make all data available as an open source resource for the community, providing a basis for further study of the relationship between standardized physical performance assessment and real-world behavior and independence.

Sections du résumé

BACKGROUND
Digital technologies and advanced analytics have drastically improved our ability to capture and interpret health-relevant data from patients. However, only limited data and results have been published that demonstrate accuracy in target indications, real-world feasibility, or the validity and value of these novel approaches.
OBJECTIVE
This study aimed to establish accuracy, feasibility, and validity of continuous digital monitoring of walking speed in frail, elderly patients with sarcopenia and to create an open source repository of raw, derived, and reference data as a resource for the community.
METHODS
Data described here were collected as a part of 2 clinical studies: an independent, noninterventional validation study and a phase 2b interventional clinical trial in older adults with sarcopenia. In both studies, participants were monitored by using a waist-worn inertial sensor. The cross-sectional, independent validation study collected data at a single site from 26 naturally slow-walking elderly subjects during a parcours course through the clinic, designed to simulate a real-world environment. In the phase 2b interventional clinical trial, 217 patients with sarcopenia were recruited across 32 sites globally, where patients were monitored over 25 weeks, both during and between visits.
RESULTS
We have demonstrated that our approach can capture in-clinic gait speed in frail slow-walking adults with a residual standard error of 0.08 m per second in the independent validation study and 0.08, 0.09, and 0.07 m per second for the 4 m walk test (4mWT), 6-min walk test (6MWT), and 400 m walk test (400mWT) standard gait speed assessments, respectively, in the interventional clinical trial. We demonstrated the feasibility of our approach by capturing 9668 patient-days of real-world data from 192 patients and 32 sites, as part of the interventional clinical trial. We derived inferred contextual information describing the length of a given walking bout and uncovered positive associations between the short 4mWT gait speed assessment and gait speed in bouts between 5 and 20 steps (correlation of 0.23) and longer 6MWT and 400mWT assessments with bouts of 80 to 640 steps (correlations of 0.48 and 0.59, respectively).
CONCLUSIONS
This study showed, for the first time, accurate capture of real-world gait speed in slow-walking older adults with sarcopenia. We demonstrated the feasibility of long-term digital monitoring of mobility in geriatric populations, establishing that sufficient data can be collected to allow robust monitoring of gait behaviors outside the clinic, even in the absence of feedback or incentives. Using inferred context, we demonstrated the ecological validity of in-clinic gait assessments, describing positive associations between in-clinic performance and real-world walking behavior. We make all data available as an open source resource for the community, providing a basis for further study of the relationship between standardized physical performance assessment and real-world behavior and independence.

Identifiants

pubmed: 31774406
pii: v7i11e15191
doi: 10.2196/15191
pmc: PMC6906618
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e15191

Informations de copyright

©Arne Mueller, Holger Alfons Hoefling, Amir Muaremi, Jens Praestgaard, Lorcan C. Walsh, Ola Bunte, Roland Martin Huber, Julian  Fürmetz, Alexander Martin Keppler, Matthias Schieker, Wolfgang Böcker, Ronenn Roubenoff, Sophie Brachat, Daniel S. Rooks, Ieuan Clay. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 27.11.2019.

Références

JMIR Mhealth Uhealth. 2019 Nov 27;7(11):e15191
pubmed: 31774406
Maturitas. 2019 Mar;121:28-34
pubmed: 30704562
PLoS One. 2019 Aug 30;14(8):e0221732
pubmed: 31469864
J Am Med Dir Assoc. 2011 May;12(4):249-56
pubmed: 21527165
Physiol Meas. 2017 Jan;38(1):N1-N15
pubmed: 27941238
JAMA. 2011 Jan 5;305(1):50-8
pubmed: 21205966
Biomed Eng Online. 2015 Nov 23;14:106
pubmed: 26597696
Gait Posture. 2019 Feb;68:78-80
pubmed: 30465945
Neurosci Biobehav Rev. 2019 Feb;97:87-93
pubmed: 29940238
J Med Internet Res. 2018 Jun 08;20(6):e210
pubmed: 29884610
J Gerontol A Biol Sci Med Sci. 2016 Jan;71(1):63-71
pubmed: 26297942
J Am Geriatr Soc. 2017 Dec;65(12):2566-2571
pubmed: 28884789
PLoS One. 2011;6(8):e23299
pubmed: 21853107
Sensors (Basel). 2018 Jun 25;18(7):
pubmed: 29941804
Front Psychol. 2016 Jun 24;7:918
pubmed: 27445891
Arthritis Care Res (Hoboken). 2019 Feb;71(2):178-188
pubmed: 30346654
J Vis Exp. 2018 Jul 27;(137):
pubmed: 30102277
Gait Posture. 2012 Feb;35(2):192-6
pubmed: 21945386
PLoS One. 2015 Apr 16;10(4):e0123822
pubmed: 25879750
Clin Pharmacol Ther. 2017 Dec;102(6):912-913
pubmed: 29027665
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:2981-4
pubmed: 25570617
Digit Biomark. 2018 Aug 2;2(2):79-89
pubmed: 32095759
Am J Respir Crit Care Med. 2002 Jul 1;166(1):111-7
pubmed: 12091180
Aging Clin Exp Res. 2019 Oct;31(10):1435-1442
pubmed: 30515724
Int J Chron Obstruct Pulmon Dis. 2019 Sep 03;14:1979-1992
pubmed: 31564846
PLoS One. 2014 Dec 05;9(12):e114273
pubmed: 25479403
Age Ageing. 2010 Jul;39(4):412-23
pubmed: 20392703
J Am Geriatr Soc. 2017 Sep;65(9):1988-1995
pubmed: 28653345
Med Eng Phys. 2015 Apr;37(4):400-7
pubmed: 25749552

Auteurs

Arne Mueller (A)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Holger Alfons Hoefling (HA)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Amir Muaremi (A)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Jens Praestgaard (J)

Biostatistics and Pharmacometrics, Novartis Pharmaceuticals Corporation, East Hannover, NJ, United States.

Lorcan C Walsh (LC)

Novartis Business Services, Novartis Ireland Ltd, Dublin, Ireland.

Ola Bunte (O)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Roland Martin Huber (RM)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Julian Fürmetz (J)

University Hospital, Ludwigs-Maximillians Universität, Munich, Germany.

Alexander Martin Keppler (AM)

University Hospital, Ludwigs-Maximillians Universität, Munich, Germany.

Matthias Schieker (M)

Novartis Institutes for BioMedical Research, Basel, Switzerland.
University Hospital, Ludwigs-Maximillians Universität, Munich, Germany.

Wolfgang Böcker (W)

University Hospital, Ludwigs-Maximillians Universität, Munich, Germany.

Ronenn Roubenoff (R)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Sophie Brachat (S)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Daniel S Rooks (DS)

Novartis Institutes for BioMedical Research, Cambridge, MA, United States.

Ieuan Clay (I)

Novartis Institutes for BioMedical Research, Basel, Switzerland.

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female
Humans United States Aged Cross-Sectional Studies Medicare Part C
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH