Effectiveness of Active Cycling in Subacute Stroke Rehabilitation: A Randomized Controlled Trial.

OBJECTIVE: To examine the effects of 3 months of aerobic training (AT) followed by coaching on aerobic capacity, strength, and gait speed after subacute stroke. DESIGN: Randomized controlled trial. SETTING: Inpatient rehabilitation center. PARTICIPANTS: Patients (N=59; mean age ± SD, 65.4±10.3y; 21 women (36%); Barthel Index ≤50 in 64% of patients) with first stroke and able to cycle at 50 revolutions/min were enrolled in the study 3 to 10 weeks after stroke onset. INTERVENTIONS: Patients were randomly allocated to a 3-month active cycling group (ACG, n=33) and education, or to a control group (CG, n=26). Afterward, patients in the ACG were randomly assigned either to a coaching (n=15) or to a noncoaching group (n=16) for 9 months. MAIN OUTCOME MEASURES: Aerobic capacity, isometric knee extension strength, and gait ability and speed were measured before and after intervention and during follow-up at 6 and 12 months. RESULTS: A nonsignificant difference was found in workload (Wattpeak) (P=.078) between ACG and CG after 3 months. Furthermore, after 3 months of cycling and after 9 months of coaching, all groups showed significant changes over time (P≤.027) in peak oxygen consumption, Wattpeak, leg strength, and gait speed. Also, significant changes over time (P<.001) were found in the ACG and the CG in patients with walking inability at baseline. CONCLUSIONS: No significant differences between training groups were found over time. Although our study did not have objective exercise data from the training device during follow-up, the 3-month active cycling (AC) program combined with education sessions seemed an applicable method in subacute stroke rehabilitation. New long-term AT interventions should focus on coaching approaches to facilitate training after a supervised AC program.

Physical activity in chronic home-living and sub-acute hospitalized stroke patients using objective and self-reported measures.

BACKGROUND: Despite confirmed reduced physical activity (PA) after stroke in various stages of recovery, the type of activities stroke patients executed and the time spent at different activity levels have not been sufficiently verified with stroke-validated assessment tools. DESIGN: Observational study. OBJECTIVE: To determine PA of sub-acute stroke patients hospitalized in a rehabilitation centre (HOS) compared to chronic home-living stroke patients (HOM) using objective and self-reported measures during 2 weekdays and 1 weekend day. METHODS: Fifteen HOS and 15 HOM patients wore a Sense Wear Pro 2 accelerometer (METs*minutes/24 h) and a knee-worn pedometer Yamax Digi Walker SW 200 (steps) and filled in a coded activity diary (kcal/24 h; METs*minutes/24 h) during three consecutive days. RESULTS: In HOM significantly more steps (stepstotal HOM = 18722.6 ± 10063.6; stepstotal HOS = 7097.8 ± 5850.5) and higher energy expenditure (EE) levels (EEtotal HOM = 7759.34 ± 2243.04; EEtotal HOS = 5860.15 ± 1412.78) were measured. In this group less moderate activity (≥3-6 ≤ METs) was performed on a weekday (pday1 = 0.006; pday2 = 0.027) and in total (p = 0.037). Few therapy hours (physical, occupational and speech therapy, and psychological support) were provided in HOM compared to HOS (p < 0.001). Vigorous activities were only seen in HOM. In both groups few patients executed sport activities. CONCLUSIONS: In HOM significantly more steps were performed and higher EE values were measured. However, participation in moderate activities and time spent on therapy were less in HOM. Evaluating PA with quantitative measures is feasible in both chronic home-living and sub-acute hospitalized patients with stroke.

Evolution of cardiorespiratory fitness after stroke: a 1-year follow-up study. Influence of prestroke patients' characteristics and stroke-related factors.

OBJECTIVES: To examine changes in cardiorespiratory fitness over the first year poststroke and explore the effect of prestroke patients' characteristics and stroke-related factors on this evolution. DESIGN: Descriptive, longitudinal study with repeated measures of exercise capacity at 3, 6, and 12 months poststroke. SETTING: Rehabilitation center and exercise testing laboratory. PARTICIPANTS: Consecutive sample of patients with stroke (N=33; mean age ± SD, 59.0±11.3 y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Peak oxygen consumption (VO(2)peak) and oxygen uptake efficiency slope (OUES) were determined during a symptom-limited graded cycle ergometer test at 3, 6, and 12 months poststroke. Age, sex, premorbid physical activity level, clinical history (smoking, diabetes mellitus, chronic pulmonary diseases, cardiovascular diseases, overweight, and hypertension), stroke type and area, side of lesion, and assessments of stroke severity were evaluated at intake. RESULTS: Mean VO(2)peak ± SD was 18.1±6.6 mL·kg(-1)·min(-1), 19.8±8.0 mL·kg(-1)·min(-1), and 19.7±8.4 mL·kg(-1)·min(-1) at 3, 6, and 12 months poststroke. Values for OUES were 1575.3±638.3, 1710.7±710.3, and 1687.2±777.5, respectively. Mixed models showed no significant difference over time for VO(2)peak (P=.10), nor for the logarithm of OUES (P=.09). Stroke survivors at risk of deconditioning were premorbidly less active at work or in sport activities, diabetic, or initially more severely impaired. Combination of factors revealed that older patients with stroke and diabetes were less likely to improve on VO(2)peak and that older, women, diabetic nonsmokers improved less on log OUES. CONCLUSIONS: Cardiorespiratory fitness was reduced from 3 to 12 months poststroke and on average did not significantly change over time. Further studies should elucidate methods of increasing cardiorespiratory fitness during stay in the rehabilitation center and how community-based aerobic exercise training postrehabilitation can be organized.

Monitoring of physical activity after stroke: a systematic review of accelerometry-based measures.

OBJECTIVE: To assess the clinimetric properties and clinical applicability of different accelerometry-based measurement techniques in persons with stroke. DATA SOURCES: A systematic search of literature was performed using a specific search strategy by means of different electronic databases until October 2008 (PubMed, EMBASE, CINAHL, Cochrane Library of Clinical Trials). STUDY SELECTION: A first selection was made by means of title and abstract. A second selection was performed by means of predefined inclusion criteria: (1) accelerometry in stroke population, (2) application of accelerometry in patients with stroke including clinimetric properties. The exclusion criteria were (1) dysphagia, (2) new engineering techniques or software alterations, (3) secondary sources, and (4) Case studies. DATA EXTRACTION: The clinimetric properties and applicability of accelerometry were described based on the included publications. DATA SYNTHESIS: Twenty-five articles (4 randomized controlled trials) were included. The information of the publications was divided into (1) gait, cadence, and ambulatory activity; (2) upper-extremity activity; and (3) topics related to stroke other than upper or lower extremity. Accelerometry was shown to be valid and had good test-retest reliability in a large number of settings. Numerous studies demonstrated correlations between accelerometry and common stroke scales. Trunk movements were measured as an outcome of disturbed gait. The vertical asymmetry index especially was able to differentiate between persons with stroke and healthy controls. Persons with stroke showed less ambulatory activity, measured as steps per day, than sedentary controls. Triaxial accelerometry was able to distinguish between varying activity levels. Upper-extremity use was lesser in persons with stroke. It was impossible to calculate a minimal clinical difference for arm use by a uniaxial accelerometer. Evidence was presented that finger-tapping and sit-to-stand measured by accelerometers could be used to define recovery from stroke. CONCLUSIONS: The literature concerning accelerometry incorporated into stroke research is young, limiting the ability to draw consistent conclusions. Nonetheless, the available evidence suggests that accelerometers yield valid and reliable data about the physical activity of patients with stroke. Future research is necessary to investigate clinimetric properties like predictive value and responsiveness further before implementing accelerometry in clinical trials as an outcome for change.

Does a cycling program combined with education and followed by coaching promote physical activity in subacute stroke patients? A randomized controlled trial.

BACKGROUND: To investigate the effects of a three month active cycling program followed by coaching on physical activity in subacute stroke patients. METHODS: Patients (n = 59; mean age =65.4 ± 10.3) aged ≤80 years with first stroke and able to cycle at 50 revolutions/minute enrolled 3-10 weeks post stroke. Patients were randomly allocated to three month active cycling group (n = 33) or to a control group (n = 26), 3 x 30 minutes training/week. Afterwards, the active cycling group was randomized into a coaching (n = 15) versus non-coaching group (n = 16) for nine months. Physical activity was measured by objective and self-reported measures, which were taken before/after the active cycling program and during six and 12 months, except the Baecke-questionnaire, which was used at baseline and 12 months. RESULTS: A significant difference was found in Baecke/sport (95% confidence interval: 0.06, 2.24; p = 0.039) between the active cycling group and the control group, in patients with severe motor function deficits at baseline. Patients in the control group performed significant less sports at 12 months (mean Baecke/sportbaseline =3.07 ± 1.21, mean Baecke/sport12months = 1.43 ± 0.98; p = 0.01). Furthermore, all groups showed significant changes over time in all measures at three months (except: Physical Activity Scale for Individuals with Physical Disabilities, diary/Mets*minutes-moderate) and 12 month and additionally in a subgroup with severe motor function deficits (except diary Mets*minutes-sedentary). CONCLUSION: When active cycling combined with education is used in subacute patients with severe motor function deficits, more sport participation might be observed after one year. No other significant group differences were found over time. In all groups, however, patients showed significant improvement over time in physical activity measures. Future work is needed to explore the most effective coaching approach after an aerobic training program. Implications for Rehabilitation The active cycling program combined with education is applicable in subacute stroke patients as it required little stand-by assistance due to chip cards, the intensity was gradually built and the involvement of caregivers in the educational sessions. This training approach also revealed applicable in severely impaired stroke patients and might facilitate sport participation on the long-term. This randomized controlled study aims to quantify physical activity after stroke by using a combination of objective and self-report measures, which revealed detailed information about different aspects of physical activity levels. There is a need for coaching approaches that facilitate aerobic exercise after ending a supervised program. A coaching approach needs to guide patients in adopting aerobic exercise as a part of a lifestyle change and needs to be less time consuming.

An overview of the applied definitions and diagnostic methods to assess exercise oscillatory ventilation--a systematic review.

The variable "exercise oscillatory ventilation" (EOV), assessed during cardiopulmonary exercise test (CPET), recently became a fundamental prognostic parameter in patients with heart failure. In literature, various definitions are suggested, but an uniformly accepted description to identify EOV still lacks. We performed a systematic review of the literature in order to determine the different definitions and diagnostic techniques to assess EOV. A systematic search strategy was established and executed in seven databases (PubMed, Google Scholar, Cochrane Clinical Trials, Science Direct, Pedro, Web Of Science library and Medline (Ovid)) resulting in 605 citations after de-duplication. Full-text articles (n=124) were assessed for eligibility, resulting in 75 citations. The review accounted 17,440 patients of whom 4,638 subjects presented EOV. Seven studies described EOV in a non-heart failure population accounting 168 EOV subjects. The definitions could be categorized in nine subdivisions of which four (n=43) referred to an original description. The other subdivisions were combinations of the original definitions (n=11), quantifications (n=4), computational (n=3), vaguely described (n=8) or not defined (n=6). Symptom limited maximal exercise tests were conducted to assess EOV, however the modes, protocols, software and data sampling were divers. Heterogeneity in the numerous definitions to identify EOV and the vaguely described assessment methods are hindering the evolution to a standardized uniformly accepted definition and technique to identify this abnormal breathing pattern. Unity in definition and international adopted assessment is warranted to strengthen its validity as a prognostic marker and could promote communication. It may facilitate clinical trials on pathophysiology and origin of EOV.

Physical activity monitoring in stroke: SenseWear Pro2 activity accelerometer versus Yamax Digi-Walker SW-200 pedometer.

PURPOSE: Determine validity and reliability of SenseWear Pro2 Armband (SWP2A) and Yamax Digi-Walker SW-200 Pedometer (YDWP) in stroke and healthy adults. METHODS: Fifteen stroke patients and 15 healthy participants wore SWP2A on upper arm and YDWP at hip/knee. Different activities were performed: treadmill walking, walking up/down a step, cycling and walking on an even surface. Steps and Energy Expenditure (EE) were measured and compared to steps counted manually and indirect calorimetry. Repeated measurements were compared to determine reliability of both devices. RESULTS: Spearman correlation coefficients between knee-worn YDWP and counted steps while walking on an even surface was ≥0.89 in healthy and ≥0.95 in stroke. Treadmill walking revealed high Spearman correlation coefficients in healthy individuals (rs ≥ 0.90) and at 1.5 km/h in stroke (rs = 0.69). During other activities YDWP often underestimated steps. SWP2A data revealed inconsistent results in EE and steps. Reliability tested by repeated measurements varied between 0.66 and 0.98 for YDWP and 0.61 and 0.97 for SWP2A. CONCLUSION: YDWP and SWP2A are both reliable. Only knee-worn YDWP is a valid device to measure steps except high intensity walking in stroke. YDWP systematically undercounts steps during other activities of short duration. This study could not demonstrate valid measurement of steps/EE in stroke using SWP2A. Implications for Rehabilitation Stroke is a disabling disease with residual neurologic deficits, which impairs mobility and predisposes them to sedentary behavior. A Yamax Digi-Walker SW-200 knee-worn pedometer showed to be a valid and reliable technique to measure ambulatory activity in stroke. A valid instrument to measure energy expenditure in stroke needs to be explored.

Is a coded physical activity diary valid for assessing physical activity level and energy expenditure in stroke patients?

OBJECTIVES: to determine the concurrent validity of a physical activity diary for measuring physical activity level and total energy expenditure in hospitalized stroke patients. METHOD: Sixteen stroke patients kept coded activity diaries and wore SenseWear Pro2 multi-sensor activity monitors during daytime hours for one day. A researcher observed the patients and completed a diary. Data from the patients' diaries were compared with observed and measured data to determine total activity (METs*minutes), activity level and total energy expenditure. RESULTS: Spearman correlations between the patients' and researchers' diaries revealed a high correlation for total METs*minutes (rs = 0.75, p<0.01) for sedentary (rs = 0.74,p<0.01) and moderate activities (rs = 0.71,p<0.01) and a very high correlation (rs = 0.92, p<0.01) for the total energy expenditure. Comparisons between the patients' diaries and activity monitor data revealed a low correlation (rs 0.29) for total METs*minutes and energy expenditure. CONCLUSION: Coded self-monitoring activity diaries appear feasible as a low-tech alternative to labor-intensive observational diaries for determining sedentary, moderate, and total physical activity and for quantifying energy expenditure in hospitalized stroke patients. Given the poor correlation with objective measurements of physical activity, however, further research is needed to validate its use against a gold-standard measure of physical activity intensity and energy expenditure.

Metabolic syndrome in youth: a cross-sectional school-based survey.

AIM: To assess the prevalence of metabolic syndrome (MetS) among students attending vocational secondary school (VSE). VSE provides practice-oriented education in which young people learn a specific occupation. Previously we reported VSE to be the type of education with the highest prevalence of overweight and obesity. METHODS: All data were collected in a cross-sectional school-based survey. Subjects were recruited from a community sample of 869 adolescents in 14 secondary schools. In this total sample all components of the metabolic syndrome were assessed in a subgroup of 506 students. MetS was defined analogous to National Cholesterol Education Program: Adult Treatment Panel III criteria, with modifications for students under 19 years of age. RESULTS: In the subsample (n=506) 4.1% of the students had metabolic syndrome. There was a significant difference in the prevalence of metabolic syndrome among BMI categories (p<0.001). The prevalence of metabolic syndrome was higher in obese students (39.1%) than in overweight students (2.8%) and normal weight students (0.3%). CONCLUSION: Being overweight or obese substantially increases the risk for metabolic syndrome, even in an adolescent school population.