Article: Upper limb sensorimotor recovery in Asian stroke survivors: a study protocol for the development and implementation of a Technology-Assisted dIgitaL biOmaRker (TAILOR) platform.
2023 Volume 14, Page(s) 1246888
Abstract: Background: Stroke is a leading cause of lifelong disability worldwide, partially driven by a reduced ability to use the upper limb in daily life causing increased dependence on caregivers. However, post-stroke functional impairments have only been ... ...
| Abstract | Background: Stroke is a leading cause of lifelong disability worldwide, partially driven by a reduced ability to use the upper limb in daily life causing increased dependence on caregivers. However, post-stroke functional impairments have only been investigated using limited clinical scores, during short-term longitudinal studies in relatively small patient cohorts. With the addition of technology-based assessments, we propose to complement clinical assessments with more sensitive and objective measures that could more holistically inform on upper limb impairment recovery after stroke, its impact on upper limb use in daily life, and on overall quality of life. This paper describes a pragmatic, longitudinal, observational study protocol aiming to gather a uniquely rich multimodal database to comprehensively describe the time course of upper limb recovery in a representative cohort of 400 Asian adults after stroke. Particularly, we will characterize the longitudinal relationship between upper limb recovery, common post-stroke impairments, functional independence and quality of life. Methods: Participants with stroke will be tested at up to eight time points, from within a month to 3 years post-stroke, to capture the influence of transitioning from hospital to community settings. We will perform a battery of established clinical assessments to describe the factors most likely to influence upper limb recovery. Further, we will gather digital health biomarkers from robotic or wearable sensing technology-assisted assessments to sensitively characterize motor and somatosensory impairments and upper limb use in daily life. We will also use both quantitative and qualitative measures to understand health-related quality of life. Lastly, we will describe neurophysiological motor status using transcranial magnetic stimulation. Statistics: Descriptive analyses will be first performed to understand post-stroke upper limb impairments and recovery at various time points. The relationships between digital biomarkers and various domains will be explored to inform key aspects of upper limb recovery and its dynamics using correlation matrices. Multiple statistical models will be constructed to characterize the time course of upper limb recovery post-stroke. Subgroups of stroke survivors exhibiting distinct recovery profiles will be identified. Conclusion: This is the first study complementing clinical assessments with technology-assisted digital biomarkers to investigate upper limb sensorimotor recovery in Asian stroke survivors. Overall, this study will yield a multimodal data set that longitudinally characterizes post-stroke upper limb recovery in functional impairments, daily-life upper limb use, and health-related quality of life in a large cohort of Asian stroke survivors. This data set generates valuable information on post-stroke upper limb recovery and potentially allows researchers to identify different recovery profiles of subgroups of Asian stroke survivors. This enables the comparisons between the characteristics and recovery profiles of stroke survivors in different regions. Thus, this study lays out the basis to identify early predictors for upper limb recovery, inform clinical decision-making in Asian stroke survivors and establish tailored therapy programs. Clinical trial registration: ClinicalTrials.gov, identifier: NCT05322837. |
|---|---|
| Language | English |
| Publishing date | 2023-11-30 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2564214-5 |
| ISSN | 1664-2295 |
| ISSN | 1664-2295 |
| DOI | 10.3389/fneur.2023.1246888 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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