Evidence map›Paper›PMID 40416999›Full record

ArticleDigital biomarkers

Real-World Postural Transitions as Biomarkers of Functional Impairment in Duchenne Muscular Dystrophy.

Cailin J Gramling, Dheeraj Dhanvee Kairamkonda, Jamie L Marshall, Carl Morris, Jennifer Marlowe, Brett M Meyer, Paolo DePetrillo, Jaime Franco Betegon, Ellen W McGinnis, Donna M Rizzo and 2 more

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Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Cailin J GramlingVermont Complex System Center, University of Vermont, Burlington, VT, USA.
Dheeraj Dhanvee KairamkondaCenter for Remote Health Monitoring, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Jamie L MarshallSolid Biosciences Inc., Charlestown, MA, USA.
Carl MorrisSomite Therapeutics, Boston, MA, USA.
Jennifer MarlowenChroma Bio, Boston, MA, USA.
Brett M MeyerMedidata Systems, New York, NY, USA.
Paolo DePetrilloMedidata Systems, New York, NY, USA.
Jaime Franco BetegonMedidata Systems, New York, NY, USA.
Ellen W McGinnisCenter for Remote Health Monitoring, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Donna M RizzoVermont Complex System Center, University of Vermont, Burlington, VT, USA.
Reed D GurchiekDepartment of Bioengineering, Clemson University, Clemson, SC, USA.
Ryan S McGinnisCenter for Remote Health Monitoring, Wake Forest School of Medicine, Winston-Salem, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Duchenne muscular dystrophy (DMD) is a progressive neuromuscular disorder that impairs daily functioning and results in premature death. Current clinical assessments are widely used for characterizing functional impairment but have limitations due to their subjective and effort-based nature and because they only capture a snapshot of symptoms at a single point in time. Digital health technologies, such as wearable devices, allow continuous collection of movement and physiological data during daily life and could provide objective measures of the impact of DMD symptoms on daily functioning. For example, measurement of the 95th centile of stride velocity has recently gained endorsement by European regulators as an endpoint for evaluating functional changes in DMD, but the use of wearables for this purpose is just beginning. In this study, we present preliminary investigations of candidate digital biomarkers of functional impairment using real-world data and further explore the relationships between these parameters and established clinical assessments. We found nine candidate biomarkers for detecting DMD-related functional impairment, all exhibiting large to very large effect sizes in our sample of 14 boys with DMD and matched controls (9 DMDs, 5 controls, age 4-12 years). Each candidate biomarker was moderately or strongly associated with clinical measures of function in DMD. Six of the biomarkers are novel and/or understudied in DMD including objective measures of gait acceleration and variability; postural control immediately before and after a postural transition; and the smoothness of postural transitions. Notably, postural transition measures were more sensitive to DMD-related impairment than gait, activity, and cardiac measures. These results suggest that the quality of postural transitions could serve as a sensitive and objective measure of functional impairment in DMD and point toward the need for further exploration of these measures.

Indexed as

Digital biomarkersGaitHeart rateTransitionsWearables

Identifiers

PMID40416999
PMCPMC12101821

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.