Sharon Kramer

Measuring Activity Levels at an Acute Stroke Ward: Comparing Observations to a Device

Background. If a simple system of instrumented monitoring was possible early after stroke, therapists may be able to more readily gather information about activity and monitor progress over time. Our aim was to establish whether a device containing a dual-axis accelerometer provides similar information to behavioural mapping on physical activity patterns early after stroke. Methods. Twenty participants with recent stroke ≤2 weeks and aged >18 were recruited and monitored at an acute stroke ward. The monitoring device (attached to the unaffected leg) and behavioural mapping (observation) were simultaneously applied from 8 a.m. to 5 p.m. Both methods recorded the time participants spent lying, sitting, and upright. Results. The median percentage and interquartile range (IQR) of time spent lying, sitting, and upright recorded by the device were 36% (15–68), 51% (28–72), and 2% (1–5), respectively. Agreement between the methods was substantial: Intraclass Correlation Coefficient (95% CI): lying 0.74 (0.46–0.89), sitting 0.68 (0.36–0.86), and upright 0.72 (0.43–0.88). Conclusion. Patients are inactive in an acute stroke setting. In acute stroke, estimates of time spent lying, sitting, and upright measured by a device are valid.

Energy Expenditure and Cost During Walking After Stroke: A Systematic Review

OBJECTIVES To systematically review the evidence to determine energy expenditure (EE) in volume of oxygen uptake (V̇O2) (mL/kg/min) and energy cost in oxygen uptake per meter walked (V̇O2/walking speed; mL/kg/m) during walking poststroke and how it compares with healthy controls; and to determine how applicable current exercise prescription guidelines are to stroke survivors. DATA SOURCES Cochrane Central Register of Controlled Trials, MEDLINE, Embase, and CINAHL were searched on October 9, 2014, using search terms related to stroke and EE. Additionally, we screened reference lists of eligible studies. STUDY SELECTION Two independent reviewers screened titles and abstracts of 2115 identified references. After screening the full text of 144 potentially eligible studies, we included 29 studies (stroke survivors: n=501, healthy controls: n=123), including participants with confirmed stroke and a measure of V̇O2 during walking using breath-by-breath analysis. Studies with (9 studies) and without (20 studies) a healthy control group were included. DATA EXTRACTION Two reviewers independently extracted data using a standard template, including patient characteristics, outcome data, and study methods. DATA SYNTHESIS Mean age of stroke survivors was 57 years (range, 40-67y). Poststroke EE was highly variable across studies and could not be pooled because of high heterogeneity. EE during steady-state overground walking at matched speeds was significantly higher in stroke survivors than healthy controls (mean difference in V̇O2, 4.06 mL/kg/min; 95% confidence interval [CI], 2.21-5.91; 1 study; n=26); there was no significant group difference at self-selected speeds. Energy cost during steady-state overground walking was higher in stroke survivors at both self-selected (mean difference, .47 mL/kg/m; 95% CI, .29-.66; 2 studies; n=38) and matched speeds compared with healthy controls (mean difference, .27 mL/kg/m; 95% CI, .03-.51; 1 study; n=26). CONCLUSIONS Stroke survivors expend more energy during walking than healthy controls. Low-intensity exercise as described in guidelines might be at a moderate intensity level for stroke survivors; there is a need for stroke-specific exercise guidelines.

The prevalence of fatigue after stroke: A systematic review and meta-analysis:

Background Fatigue is a common and debilitating symptom after stroke. The last decade has seen rapid expansion of the research literature on post-stroke fatigue, but prevalence remains unclear. Aims To estimate post-stroke fatigue prevalence and to identify the contributing factors to fatigue, by conducting a systematic review and meta-analysis. Summary of review We included all studies of adult stroke survivors that used a recognized assessment scale for fatigue (search date September 2014). Two reviewers independently reviewed all full texts for inclusion. Data were extracted by one reviewer and independently cross-checked by a second. Risk of bias was evaluated using a critical appraisal tool. From an overall yield of 921 studies, 101 full text papers were screened, and 49 of these met inclusion criteria. The most widely used measure of fatigue was the Fatigue Severity Scale (n = 24 studies). Prevalence estimates at a cut-off score of > or ≥ 4 were available for 22 of these 24 studies (total n = 3491), and ranged from 25 to 85%. In random effects meta-analysis, the pooled prevalence estimate was 50% (95% CI 43–57%), with substantial heterogeneity (I2 = 94%). Neither depression status nor time point post-stroke explained the heterogeneity between studies. In post-hoc analysis, fatigue prevalence was found to be lower in the four Asian studies (35%; 95% CI 20–50; I2 = 96%). Conclusions Our results confirm that fatigue is a widespread issue for stroke survivors, although it may be less prevalent in Asia. Further research is needed to explain the wide variability in prevalence estimates between studies.

Reducing Sitting Time After Stroke: A Phase II Safety and Feasibility Randomized Controlled Trial

OBJECTIVE To test the safety, feasibility, and effectiveness of reducing sitting time in stroke survivors. DESIGN Randomized controlled trial with attention-matched controls and blinded assessments. SETTING Community. PARTICIPANTS Stroke survivors (N=35; 22 men; mean age, 66.9±12.7y). INTERVENTIONS Four counseling sessions over 7 weeks with a message of sit less and move more (intervention group) or calcium for bone health (attention-matched control group). MAIN OUTCOME MEASURES Measures included safety (adverse events, increases in pain, spasticity, or fatigue) and feasibility (adherence to trial protocol). Secondary measures included time spent sitting (including in prolonged bouts ≥30min), standing, and stepping as measured by the thigh-worn inclinometer (7d, 24h/d protocol) and time spent in physical activity of at least moderate intensity as measured by a triaxial accelerometer. The Multimedia Activity Recall for Children and Adults was used to describe changes in use of time. RESULTS Thirty-three participants completed the full protocol. Four participants reported falls during the intervention period with no other adverse events. From a baseline average of 640.7±99.6min/d, daily sitting time reduced on average by 30±50.6min/d (95% confidence interval [CI], 5.8-54.6) in the intervention group and 40.4±92.5min/d in the control group (95% CI, 13.0-93.8). Participants in both groups also reduced their time spent in prolonged sitting bouts (≥30min) and increased time spent standing and stepping. CONCLUSIONS Our protocol was both safe and feasible. Participants in both groups spent less time sitting and more time standing and stepping postintervention, but outcomes were not superior for intervention participants. Attention matching is desirable in clinical trials and may have contributed to the positive outcomes for control participants.

Changes in Activity Levels in the First Month after Stroke

[Purpose] To quantify the activity levels of individuals in an acute stroke ward, and to determine if their activity levels change within the first month after stroke. [Methods] In this pilot study, participant activity was monitored prospectively over a single day from 8 a.m. to 5 p.m. on two separate occasions. Individuals with confirmed stroke > 18 years of age and less than 15 days post-stroke at the time of recruitment were eligible for inclusion in this study. Activity was recorded using an electronic device. The first day was scheduled within 15 days and the second at four weeks post-stroke. We looked at the following activity categories: number of transitions, and the times spent lying, sitting and in dynamic activity. [Results] Sixteen individuals were included in this study with a median age of 79.5 years (interquartile range 62.5 to 85). Fifty-six % of the participants had mild, 31% had moderate and 13% had severe stroke, according to the NIHSS score. There were no significant changes in number of transitions, or times spent in dynamic activity and lying and sitting. [Conclusion] Activity levels were low at an acute stroke ward and did not significantly change within the first month.

Validity of Multisensor Array for Measuring Energy Expenditure of an Activity Bout in Early Stroke Survivors

Introduction. Stroke survivors use more energy than healthy people during activities such as walking, which has consequences for the way exercise is prescribed for stroke survivors. There is a need for wearable device that can validly measure energy expenditure (EE) of activity to inform exercise prescription early after stroke. We aimed to determine the validity and reliability of the SenseWear-Armband (SWA) to measure EE and step-counts during activity <1 month after stroke. Materials and Methods. EE was measured using the SWA and metabolic cart and steps-counts were measured using the SWA and direct observation. Based on walking ability, participants performed 2x six-minute walks or repeated sit-to-stands. Concurrent validity and test-retest reliability were determined by calculating intraclass and concordance correlation coefficients. Results and Discussion. Thirteen participants walked; nine performed sit-to-stands. Validity of the SWA measuring EE for both activities was poor (ICC/CCC < 0.40). The SWA overestimates EE during walking and underestimated EE during sit-to-stands. Test-retest agreement showed an ICC/CCC of <0.40 and >0.75 for walking and sit-to-stand, respectively. However, agreement levels changed with increasing EE levels (i.e., proportional bias). The SWA did not accurately measure step-counts. Conclusion. The SWA should be used with caution to measure EE of activity of mild to moderate stroke survivors <1 month after stroke.

The Energy Cost of Steady State Physical Activity in Acute Stroke

OBJECTIVE Cardiorespiratory fitness levels are very low after stroke, indicating that the majority of stroke survivors are unable to independently perform daily activities. Physical fitness training improves exercise capacity poststroke; however, the optimal timing and intensity of training is unclear. Understanding the energy cost of steady-state activity is necessary to guide training prescription early poststroke. We aimed to determine if acute stroke survivors can reach steady state (oxygen-uptake variability ≤2.0 mL O2/kg/min) during physical activity and if the energy cost of steady state activity differs from healthy controls. MATERIAL AND METHODS We recruited 23 stroke survivors less than 2 weeks poststroke. Thirteen were able to walk independently and performed a 6-minute walk (median age 78 years, interquartile range [IQR] 70-85), and 7 who were unable to walk independently performed 6 minutes of continuous sit-to-stands (median age 78 years, IQR 74-79) and we recruited 10 healthy controls (median age 73 years, IQR 70-77) who performed both 6 minutes of walking and sit-to-stands. Our primary outcome was energy cost (oxygen-uptake) during steady state activity (i.e., walking and continuous) sit-to-stands, measured by a mobile metabolic cart. RESULTS All stroke survivors were able to reach steady state. Energy costs of walking was higher in stroke than in controls (mean difference .10 mL O2/kg/m, P = .02); the difference in energy costs during sit-to-stands was not significant (mean difference .11 mL O2/kg/sts, P = .45). CONCLUSIONS Acute stroke survivors can reach a steady state during activity, indicating they are able to perform cardiorespiratory exercise. Acute stroke survivors require more energy per meter walked than controls.

Accelerometer use in young people with Down syndrome: A preliminary cross-validation and reliability study

ABSTRACT Background Inadequate physical activity is a problem for people with Down syndrome and objective monitoring using accelerometers may be inaccurate in this population. Method This was a cross-validation and reliability study comparing two triaxial accelerometers (the SenseWear and RT3) to a criterion measure (the OxyCon Mobile) in 10 young people (M age = 20 ± 2) with Down syndrome. A ROC curve analysis was conducted to determine intensity thresholds from RT3 activity counts. Results During self-selected pace walking, the accelerometers overestimated energy expenditure and had large limits of agreement (SenseWear: −0.5–3.6 METs; RT3: −0.2–2.7 METs). At this pace, SenseWear armband step counts were highly correlated with observed steps (r = .98) but underestimated steps by up to 12%. We developed RT3 thresholds that demonstrated good to excellent sensitivity and specificity in classifying physical activity intensity. Conclusions SenseWear steps and RT3 activity count thresholds can be used to monitor physical activity in young people with Down syndrome, although energy expenditure estimates should be used with caution in this population.