Dataset Information

Movement behavior remains stable in stroke survivors within the first two months after returning home.

ABSTRACT:

Background and purpose

The aim of this study is to investigate changes in movement behaviors, sedentary behavior and physical activity, and to identify potential movement behavior trajectory subgroups within the first two months after discharge from the hospital to the home setting in first-time stroke patients.

Methods

A total of 140 participants were included. Within three weeks after discharge, participants received an accelerometer, which they wore continuously for five weeks to objectively measure movement behavior outcomes. The movement behavior outcomes of interest were the mean time spent in sedentary behavior (SB), light physical activity (LPA) and moderate to vigorous physical activity (MVPA); the mean time spent in MVPA bouts ? 10 minutes; and the weighted median sedentary bout. Generalized estimation equation analyses were performed to investigate overall changes in movement behavior outcomes. Latent class growth analyses were performed to identify patient subgroups of movement behavior outcome trajectories.

Results

In the first week, the participants spent an average, of 9.22 hours (67.03%) per day in SB, 3.87 hours (27.95%) per day in LPA and 0.70 hours (5.02%) per day in MVPA. Within the entire sample, a small but significant decrease in SB and increase in LPA were found in the first weeks in the home setting. For each movement behavior outcome variable, two or three distinctive subgroup trajectories were found. Although subgroup trajectories for each movement behavior outcome were identified, no relevant changes over time were found.

Conclusion

Overall, the majority of stroke survivors are highly sedentary and a substantial part is inactive in the period immediately after discharge from hospital care. Movement behavior outcomes remain fairly stable during this period, although distinctive subgroup trajectories were found for each movement behavior outcome. Future research should investigate whether movement behavior outcomes cluster in patterns.

SUBMITTER: Wondergem R

PROVIDER: S-EPMC7098564 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Movement behavior remains stable in stroke survivors within the first two months after returning home.

Wondergem Roderick R Pisters Martijn F MF Heijmans Martijn W MW Wouters Eveline J M EJM de Bie Rob A RA Veenhof Cindy C Visser-Meily Johanna M A JMA

PloS one 20200326 3

<h4>Background and purpose</h4>The aim of this study is to investigate changes in movement behaviors, sedentary behavior and physical activity, and to identify potential movement behavior trajectory subgroups within the first two months after discharge from the hospital to the home setting in first-time stroke patients.<h4>Methods</h4>A total of 140 participants were included. Within three weeks after discharge, participants received an accelerometer, which they wore continuously for five weeks ...[more]

PMID: 32214319

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Project description:IntroductionPost-stroke depression is a disabling condition that occurs in approximately one-third of stroke survivors. There is limited information on changes in depressive symptoms shortly after stroke survivors return home. To identify factors associated with changes in post-stroke depressive symptoms during the early recovery period, we conducted a secondary analysis of patients enrolled in a clinical trial conducted during the transition period shortly after patients returned home (MISTT).MethodsThe Michigan Stroke Transitions Trial (MISTT) tested the efficacy of social worker case management and access to online information to improve patient-reported outcomes following an acute stroke. Patient Health Questionnaire-9 (PHQ-9) scores were collected via telephone interviews conducted at 7 and 90 days post-discharge; higher scores indicate more depressive symptoms. Generalized estimating equations were used to identify independent predictors of baseline PHQ-9 score at 7 days and of changes over time to 90 days.ResultsOf 265 patients, 193 and 185 completed the PHQ-9 survey at 7 and 90 days, respectively. The mean PHQ-9 score was 5.9 at 7 days and 5.1 at 90 days. Older age, being unmarried, and having moderate stroke severity (versus mild) were significantly associated with lower 7-day PHQ-9 scores (indicating fewer depressive symptoms). However, at 90 days, both unmarried patients and those with moderate or high stroke severity had significant increases in depressive symptoms over time.ConclusionsIn stroke patients who recently returned home, both marital status and stroke severity were associated with depressive symptom scores; however, the relationships were complex. Being unmarried and having higher stroke severity was associated with fewer depressive symptoms at baseline, but both factors were associated with worsening depressive symptoms over time. Identifying risk factors for changes in depressive symptoms may help guide effective management strategies during the early recovery period.

Project description:The wide variation in upper extremity motor impairments among stroke survivors necessitates more intelligent methods of customized therapy. However, current strategies for characterizing individual motor impairments are limited by the use of traditional clinical assessments (e.g., Fugl-Meyer) and simple engineering metrics (e.g., goal-directed performance). Our overall approach is to statistically identify the range of volitional movement capabilities, and then apply a robot-applied force vector field intervention that encourages under-expressed movements. We investigated whether explorative training with such customized force fields would improve stroke survivors' (n = 11) movement patterns in comparison to a control group that trained without forces (n = 11). Force and control groups increased Fugl-Meyer UE scores (average of 1.0 and 1.1, respectively), which is not considered clinically meaningful. Interestingly, participants from both groups demonstrated dramatic increases in their range of velocity during exploration following only six days of training (average increase of 166.4% and 153.7% for the Force and Control group, respectively). While both groups showed evidence of improvement, we also found evidence that customized forces affected learning in a systematic way. When customized forces were active, we observed broader distributions of velocity that were not present in the controls. Second, we found that these changes led to specific changes in unassisted motion. In addition, while the shape of movement distributions changed significantly for both groups, detailed analysis of the velocity distributions revealed that customized forces promoted a greater proportion of favorable changes. Taken together, these results provide encouraging evidence that patient-specific force fields based on individuals' movement statistics can be used to create new movement patterns and shape them in a customized manner. To the best of our knowledge, this paper is the first to directly link engineering assessments of stroke survivors' exploration movement behaviors to the design of customized robot therapy.

Project description:BackgroundThe key for successful stroke upper-limb rehabilitation includes the personalization of therapeutic interventions based on patients' functional ability and performance level. However, therapists often encounter challenges in supporting personalized rehabilitation due to the lack of information about how stroke survivors use their stroke-affected arm outside the clinic. Wearable technologies have been considered as an effective, objective solution to monitor patients' arm use patterns in their naturalistic environments. However, these technologies have remained a proof of concept and have not been adopted as mainstream therapeutic products, and we lack understanding of how key stakeholders perceive the use of wearable technologies in their practice.ObjectiveWe aim to understand how stroke survivors and therapists perceive and envision the use of wearable sensors and arm activity data in practical settings and how we could design a wearable-based performance monitoring system to better support the needs of the stakeholders.MethodsWe conducted semi-structured interviews with four stroke survivors and 15 occupational therapists (OTs) based on real-world arm use data that we collected for contextualization. To situate our participants, we leveraged a pair of finger-worn accelerometers to collect stroke survivors' arm use data in real-world settings, which we used to create study probes for stroke survivors and OTs, respectively. The interview data was analyzed using the thematic approach.ResultsOur study unveiled a detailed account of (1) the receptiveness of stroke survivors and OTs for using wearable sensors in clinical practice, (2) OTs' envisioned strategies to utilize patient-generated sensor data in the light of providing patients with personalized therapy programs, and (3) practical challenges and design considerations to address for the accelerated integration of wearable systems into their practice.ConclusionsThese findings offer promising directions for the design of a wearable solution that supports OTs to develop individually-tailored therapy programs for stroke survivors to improve their affected arm use.

Project description:Background: Neurocognitive disorder (NCD) is common after stroke, with major NCD appearing in about 10% of survivors of a first-ever stroke. We aimed to classify clinical- and imaging factors related to rapid development of major NCD 3 months after a stroke, so as to examine the optimal composition of factors for predicting rapid development of the disorder. We hypothesized that the prediction would mainly be driven by neurodegenerative as opposed to vascular brain changes. Methods: Stroke survivors from five Norwegian hospitals were included from the "Norwegian COgnitive Impairment After STroke" (Nor-COAST) study. A support vector machine (SVM) classifier was trained to distinguish between patients who developed major NCD 3 months after the stroke and those who did not. Potential predictor factors were based on previous literature and included both vascular and neurodegenerative factors from clinical and structural magnetic resonance imaging findings. Cortical thickness was obtained via FreeSurfer segmentations, and volumes of white matter hyperintensities (WMH) and stroke lesions were semi-automatically gathered using FSL BIANCA and ITK-SNAP, respectively. The predictive value of the classifier was measured, compared between classifier models and cross-validated. Results: Findings from 227 stroke survivors [age = 71.7 (11.3), males = (56.4%), stroke severity NIHSS = 3.8 (4.8)] were included. The best predictive accuracy (AUC = 0.876) was achieved by an SVM classifier with 19 features. The model with the fewest number of features that achieved statistically comparable accuracy (AUC = 0.850) was the 8-feature model. These features ranked by their weighting were; stroke lesion volume, WMH volume, left occipital and temporal cortical thickness, right cingulate cortical thickness, stroke severity (NIHSS), antiplatelet medication intake, and education. Conclusion: The rapid (<3 months) development of major NCD after stroke is possible to predict with an 87.6% accuracy and seems dependent on both neurodegenerative and vascular factors, as well as aspects of the stroke itself. In contrast to previous literature, we also found that vascular changes are more important than neurodegenerative ones. Although possible to predict with relatively high accuracy, our findings indicate that the development of rapid onset post-stroke NCD may be more complex than earlier suggested.

Dataset Information

Movement behavior remains stable in stroke survivors within the first two months after returning home.

Background and purpose

Methods

Results

Conclusion

Publications

Movement behavior remains stable in stroke survivors within the first two months after returning home.

Similar Datasets

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