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Home > RNJ > 2006 > September/October > Fatigue After Stroke: Relationship to Mobility, Fitness, Ambulatory Activity, Social Support, and Falls Efficacy

Fatigue After Stroke: Relationship to Mobility, Fitness, Ambulatory Activity, Social Support, and Falls Efficacy
Kathleen M. Michael, PhD RN CRRN • Jerilyn K. Allen, ScD RN FAAN • Richard F. Macko, MD

Fatigue is common and persistent in stroke survivors, yet it is not known how mobility deficits, fitness, or other factors, such as social support, relate to fatigue severity, or whether subjective fatigue contributes to reduced ambulatory activity. The severity of fatigue in a sample of 53 community-dwelling subjects with chronic hemiparetic stroke was examined, and relationships among fatigue and mobility deficit severity, cardiovascular-metabolic fitness, ambulatory activity, social support, and self-efficacy for falls were identified. Measures included the Fatigue Severity Scale, timed 10-meter walks, the Berg Balance Scale, submaximal and peak VO2, total daily step activity derived from microprocessor-linked Step Activity Monitors, the Medical Outcomes Study Social Support Survey, and the Falls Efficacy Scale. Forty-six percent of the sample had severe fatigue. Fatigue showed no relationship to ambulatory activity. Fatigue severity was associated with the Berg Balance Scale (p < .01) and falls efficacy (p < .01), but not with cardiovascular fitness variables. Patients with elevated fatigue severity scores had lower social support (p < .05) and poorer falls efficacy scores (p < .05) than patients reporting less fatigue. Only falls efficacy was predictive of fatigue severity (r2 = 0.216, p < .01). Further studies are needed to evaluate whether rehabilitation strategies that include not only fitness and mobility interventions, but also social/behavioral and self-efficacy components, are associated with reduced fatigue and increased ambulation.

Fatigue occurs frequently, is often severe, and is experienced months and years after stroke (Glader, Stegmayr, & Asplund, 2002). The frequency of self-reported fatigue is roughly twice as high in persons with stroke as in matched controls and is not related to time post stroke, stroke severity, or lesion location (Ingles, Eskes, & Phillips, 1999). Significant numbers of persons report that fatigue is either the worst or one of the worst symptoms of stroke (Glader et al., 2002). Ingles and colleagues found that individuals with stroke attributed more functional limitations to their fatigue than did control subjects with fatigue. Fatigue is also known to persist over time. Stein, Sliwinski, Gordon, and Hibbard (1996) showed that 76% of patients at 8 months post stroke complained of fatigue. At 2 years post stroke, 40% of patients reported that they are “always” or “often” fatigued (Glader et al.; Ingles et al.; van der Werf, van den Broek, Anten, & Bleijenberg, 2001).

The definition of fatigue developed by Aaronson and colleagues (1999) fits the chronic stroke experience especially well. Fatigue is “the awareness of a decreased capacity for physical or mental activity due to an imbalance in the availability, utilization, or restoration of resources needed to perform activity.”(p. 46). This definition affirms that fatigue occurs when systems are out of balance, and there are insufficient resources, either because of excess demand or deficient supply. Fatigue is a symptom of imbalance. Stroke imposes serious restrictions on the ability to activate, use, and restore physiologic and psychosocial resources, thereby promoting the imbalance that results in subjective fatigue. For example, the increased energy expenditure of hemiparetic gait results from the inability to activate normal movement patterns. There is disproportionately large use of cardiovascular and metabolic capacity to produce ambulation (Macko et al., 2001), often compounded by the existence of deconditioning, underlying disease, and aging. Because individuals with hemiparetic stroke have little margin of unexpended reserves, their ability to restore physiologic resources is diminished.

Thus, fatigue may be an important clinical determinant of a progressively disabling pattern of reduced physical activity. Though studies of fatigue after stroke have been limited, fatigue research in other neurological conditions affirms the relationship of fatigue to function. For example, in patients with Parkinson’s disease, fatigue relates strongly to deficit severity and functional capacity (Garber & Friedman, 2003; Herlofson & Larsen, 2002; Krupp, LaRocca, Muir-Nash, & Steinberg, 1989). With multiple sclerosis, fatigue has a deleterious effect on the performance of activities of daily living (ADLs; Krupp et al., 1989). Patients with heart and lung disease report a significant effect of fatigue on cognitive and psychosocial function, as well as physical function (Theander & Unosson, 2004). In one of the few studies to examine fatigue in large numbers of persons with stroke (Glader et al., 2002), self-reported fatigue was identified as an independent predictor for dependency in primary ADLs, and for moving into an institutional setting after stroke. As these examples suggest, fatigue is associated with disability, and affects physical, psychosocial, behavioral, and self-care functions.

In patients with chronic stroke, fatigue is related to mobility deficit severity and cardiovascular deconditioning and results in reduced ambulatory activity in home and community. But the effects of fatigue could not be fully evaluated without also considering some key psychosocial and behavioral determinants of functional activity, specifically social support, and falls efficacy. Social support was selected because of the power of peer influence on activities and behaviors. Social networks may subtly or directly encourage physical activity. Social networks can also promote a sense of belonging, purpose, and self-worth, promoting mental health that may be reflected in low self-perceived fatigue and positive activity levels (Glass, Matchar, Belyea, & Feussner, 1993). Falls efficacy was important because ambulatory activity could be a reflection of confidence in performing daily mobility tasks without falling (Hellstrom, Lindmark, Wahlberg, & Fugl-Meyer, 2003; Tinetti, Richman, & Powell, 1990a) and needed to be differentiated from mobility deficit severity, fitness, and fatigue. Thus, the study objective was to quantify fatigue in a sample of individuals with chronic hemiparetic stroke and to explore the relationships of fatigue to cardiovascular fitness, mobility deficit severity, ambulatory activity patterns, social support, and self-efficacy for falls.

Methods

Community-dwelling men and women between 45 and 84 years of age with mild to moderate hemiparetic gait deficits after ischemic strokes were recruited from the greater Baltimore area to participate in ongoing randomized exercise intervention studies. Mild to moderate hemiparetic gait was defined as observable asymmetry of gait that included reduced stance time, or reduced stance time and increased swing time in the affected limb (Macko et al., 2001a). Participants had some preserved capacity for ambulation, albeit with an assistive device (e.g., cane, walker) or standby assistance, and could ambulate for a sufficient duration to allow treadmill testing at a minimal speed of 0.2 mph (0.42 mps). The volunteer convenience sample was selected at the baseline of a larger exercise intervention study conducted at the Claude D. Pepper Older Americans Independence Center at the University of Maryland and Baltimore Veterans Administration Medical Center. All participants were at least 6 months post stroke, having completed traditional rehabilitation therapies. This time frame was selected to reflect a stable period in stroke recovery, at which time patients have assumed routine activity patterns.

Exclusion criteria were defined to protect patient safety and to control for factors other than hemiparetic stroke that might affect subjective fatigue and free-living ambulatory activity profiles. Participants were excluded from the sample if they had congestive heart failure (New York Heart Association class ≥ II), unstable angina, peripheral arterial occlusive disease (Fontaine class ≥ II), global or major receptive aphasia, screening criteria consistent with dementia (Mini-Mental Status Exam ≤ 23), current untreated major depression, or other major medical, neurological, orthopedic, or chronic pain conditions precluding participation in study activities. Because this study was conducted at the baseline of an exercise intervention study, patients who were already performing regular aerobic exercise were excluded to avoid bias from a prior training effect.

Participants provided informed consent in accordance with the approved institutional review board procedures of the University of Maryland. Baseline evaluation for eligibility entailed a comprehensive history, physical and neurological exam by an experienced clinician, cardiovascular assessment, and functional testing. Timed 10-m walks were obtained during the initial visit to evaluate gait and to set parameters for subsequent treadmill testing. All data were collected during baseline visits for the exercise-intervention development study.

Testing Procedures and Measurements

Fatigue

Fatigue was measured using the Fatigue Severity Scale (FSS) paired with a visual analogue scale (VAS; Krupp et al., 1989). The dual measurement quantified patients’ perceptions about the effect of fatigue on defined functional activities over the previous week and captured self-perceived level of fatigue on the day of encounter. The FSS was selected because of its focus on the functional and role-performance effect of fatigue and its established application in other populations with neurological impairments (Garber & Friedman, 2003; Herlofson & Larsen, 2002, 2003; Kleinman et al., 2000; Krupp, LaRocca, Muir, & Steinberg, 1990; Krupp et al., 1989; Packer, Sauriol, & Brouwer, 1994).

The FSS consists of nine statements that are rated by degree of agreement across a seven point Likert-type scale, with scores ranging from one to seven. Patients with a mean score of four or more are identified as experiencing fatigue (Herlofson & Larsen, 2002). The FSS is complemented by a VAS, consisting of a 100-mm horizontal line anchored at no fatigue and fatigue as bad as it could be that is marked by the participant to provide a real-time, single-item measure of overall fatigue severity.

Mobility-Deficit Severity

Mobility-deficit severity was determined by two measures: self-selected floor walking velocity (SSFWV), and balance. SSFWV is recognized as a criterion standard index of hemiplegic motor recovery. The timed 10-m walk is a simple and robust technique to evaluate ambulatory function in a variety of neurological conditions (Cunha et al., 2002). Participants walked a measured course using their usual assistive devices or orthoses. Four walks at normal pace were timed and averaged.

Impairment of balance was measured because of its contribution to energy expenditure and its effect on the physiologic and functional workload of walking. The Berg Balance Scale consists of task performance of 14 actions that are common in everyday life (Berg, Wood-Dauphinee, & Williams, 1995). Test items evaluate the individual’s ability to maintain positions or movements of increasing difficulty by diminishing the base of support.

Fitness

Cardiovascular fitness was reflected in measurements of economy of gait and VO2 peak. Participants initially underwent physician-supervised screening treadmill tests to ascertain safety and tolerance of graded exercise testing. On a subsequent visit, participants completed treadmill testing at submax-imal effort with open circuit spirometry to measure economy of gait as described by Macko et al. (1997). After a 15-min rest, peak exercise capacity (VO2 peak) was measured by open circuit spirometry during a constant velocity, progressively graded treadmill test to the point of volitional fatigue. The described treadmill exercise testing protocol has reliability coefficients between r = 0.80 and r = 0.93 in individuals with chronic hemiparetic stroke (Dobrovolny, Ivey, Rogers, Sorkin, & Macko, 2003).

Ambulatory Activity

Ambulatory activity was quantified by stride counts obtained from Step Activity Monitors (SAMs). SAMs were programmed with an initial generic calibration and a 12-s recording epoch (Macko et al., 2002). SAM counts of strides were compared with visual counts made with a hand-tally counter. Adjustments were made to the calibration setting and the timed walks were repeated to ensure higher than 94% accuracy against visual counts. Then the SAM was programmed and applied to the nonparetic ankle with two adjustable straps. Participants wore the SAMs for a period of 48 hr, throughout their ADLs, removing them only to bathe or sleep. Participants also kept a written log of activities during the monitored period.

On completion of a 48-hr monitoring period, SAM data were downloaded using an infrared docking port (SAM Dock Program 1.6. L). Data were expressed as total stride counts per 48 hr, from which daily step counts were calculated and activity profiles generated. Test-retest reliability of the SAM is high (r = 0.97), even in patients with hemiparetic gait (Macko et al., 2002).

Social Support

The Medical Outcomes Study Social Support Survey incorporates four functional support scales (emotional/informational, tangible, affectionate, and positive social interaction) and constructs an overall functional social support index (Sherbourne & Stewart, 1991). These scales are reliable (alphas greater than 0.91) and are stable over time.

Falls Efficacy

The falls efficacy scale (FES) is closely associated with other measures of physical function and is a more powerful predictor of ADLs than observer-based measures of balance (Hellstrom, Lindmark, & Fugl-Meyer, 2002; Tinetti, Mendes de Leon, Doucette, & Baker, 1994). The FES is a 10-item rating scale to assess confidence in performing ADLs without falling. Each item is rated from 1 (extreme confidence) to 10 (no confidence at all). Test-retest reliability has been established (r = 0.71), and the FES is strongly related to anxiety and to several measures of gait and balance (Tinetti, Richman, & Powell, 1990b).

Data Analysis

Data were analyzed using SPSS version 10.0. Descriptive statistics were generated using the descriptive and frequency subroutines for interval and ordinal data. Pearson product moment correlations were run to discern associations among fatigue, ambulatory activity, SSFWV, balance, economy of gait, VO2 peak, social support, and falls efficacy. Reliability of questionnaire scales was tested. Stepwise linear regression analyses were performed to determine which variables were independently associated with fatigue and ambulatory activity.

Results

Screening included 127 individuals with chronic hemiparetic stroke, of which 60 participants were enrolled, and 53 completed the study. Reasons for exclusion included cardiovascular or medical instability (n = 21), dementia (n = 8), depression (n = 2), hemorr-hagic stroke (n = 3), inability to walk on treadmill (n = 6), no measurable hemiparetic deficits (n =14), orthopedic conditions (n = 2), communication deficit (n = 3), and participant choice (n = 6). Two patients were excluded because of concurrent participation in regular aerobic exercise programs that could potentially introduce bias into the subsequent exercise intervention study. Reasons for not completing the study included medical problems (n = 5) and inability to perform treadmill testing (n = 2).

Clinical and demographic characteristics of the sample are summarized in Table 1. Prevalent medical problems included hypertension (n = 46, 87%), coronary artery disease (n = 30, 57%), dyslipidemia (n = 26, 49%), and diabetes (n = 16, 30%), congruent with what is known in the general stroke population. National Institutes of Health Stroke Scale scores indicated mild to moderate stroke severity. Half of the sample could be characterized as having mild mobility deficits, as indicated by the use of either no assistive device for ambulation (n = 5) or a single point cane (n = 25). Of those with moderate deficits, using quad canes (n = 13), walkers (n = 7), or wheelchairs (n = 3), all were able to walk enough for testing activities. The sample also had extremely low cardiovascular fitness, as indicated by a mean VO2 peak of 11.46 ml/kg/min.

Mean item scores for the FSS are shown in Table 2, where the scores are compared with those of patients with Parkinson’s disease, coxarthrosis who were awaiting hip replacement, and randomly selected controls published in Herlofson and Larsen, 2002, used here with permission. The mean total FSS score was 3.9, with 46% of the sample falling into the range that defines fatigue (mean scores > 4). Individuals with stroke scored highest on the following statements: “my motivation is lower when I am fatigued” (5.42), “exercise brings on my fatigue” (4.2), and “fatigue interferes with my physical functioning” (4.32).

Table 3 shows descriptive data for the total sample that is divided into patients with and without fatigue. Twenty-two patients had a mean FSS score of 4 or higher and were defined as having fatigue. The remaining 26 were not fatigued according to this definition. Missing data from 5 patients were handled by pairwise exclusion. There were no significant differences between fatigued and non-fatigued groups in SSFWV, Berg Balance, or the fitness measures of economy of gait and VO2 peak, and ambulatory activity. However, fatigued individuals with stroke reported significantly less social support (p < .05), and higher FES (p < .05), indicating less confidence in the performance of daily activities without falling.

Pearson product moment correlations showed that fatigue severity was correlated with Berg Balance (r = – 0.442, p = .004), and FES (r = 0.538, p = .001), but not with the fitness variables or ambulatory activity as had been hypothesized. The VAS, although well correlated with the FSS (r = 0.414, p = .006), did not show the same relationship to social support as the FSS.

Stepwise linear regression analyses were performed to determine the predictors of fatigue and ambulatory activity. Variables entered into the regression models included FES, SSFWV, Berg Balance, economy of gait, VO2 peak, social support, and ambulatory activity. Only falls efficacy was predictive of fatigue severity, with an adjusted r2 of .216 and p < .01 (Table 4). Fatigue severity was not predictive of ambulatory activity, but rather Berg Balance emerged as the main determinant of ambulatory activity with an adjusted r2 of 0.161, p = .02.

Discussion

Nearly half the stroke survivors met the criteria for being fatigued at the time of the measure. Self-ratings of fatigue were most severe in the areas of physical function, exercise behavior, and motivation. FES was the strongest predictor of fatigue. Patients with the highest fatigue severity scores reported the least confidence in performing ADLs without falling. These findings suggest that fatigue may be symptomatic in patients who are experiencing the greatest degree of self-perceived disability, yet fatigue did not predict ambulatory activity.

Subjective fatigue may be a hidden clinical component of a progressively disabling pattern of reduced physical activity. Strong similarities in fatigue severity to that reported in Parkinson’s disease were found (Garber & Friedman, 2003; Herlofson & Larsen, 2002). Individuals with stroke, like the patients with Parkinson’s disease, averaged higher scores than patients with coxarthrosis awaiting hip replacement and randomly selected controls in every item on the FSS (Herlofson & Larsen, 2002). In neurological conditions other than stroke, evidence has been reported of a negative relationship between subjective fatigue severity and physical activity (Belza, 1995; Garber & Friedman, 2003; Krupp & Christodoulou, 2001; Krupp et al., 1989; Packer et al., 1994). Reduced activity in response to fatigue may be related to deconditioning, loss of strength, and deterioration of gait and balance, as indicated by the FSS item ratings related to physical function. Fatigue may also factor into motivation and performance of exercise behaviors, including daily ambulatory activity, which was extremely low in this sample. Individuals with stroke may diminish symptom distress associated with fatigue by reducing activity, and adjusting their behavior to physiologic cues.

Negative physiologic cues are certainly present in hemiparetic stroke survivors. This study confirms that chronic stroke patients have profound cardiovascular deconditioning. These patients have cardiovascular fitness levels below the functional aerobic capacity necessary for basic ADLs (Bruce, Kusumi, & Hosmer, 1973). VO2 peak values averaged 58% below the expected age-matched normal values (27–33 ml, kg-1, min-1), meeting the criteria for functional aerobic impairment. Persons with disabilities who are below the physiologic capacity necessary to manage basic ADLs are at particular risk for inactivity (Cooper et al., 1999).

The role of fatigue in the reduction of ambulatory activity may be explained by the middle range theory of unpleasant symptoms (Lenz, Suppe, Gift, Pugh, & Milligan, 1995), in which behavioral adaptations are made to avoid symptom distress, in this case the distress of fatigue resulting from insufficient fitness reserves and high energy costs for daily activity. The symptom of fatigue signals the body to rest, and may be alleviated when activity is reduced. Indeed, the ambulatory activity levels in individuals with stroke were below sedentary levels for healthy adults, and also below levels reported in persons living with chronic disease and disability (Tudor-Locke & Myers, 2001). Loss of confidence in activity performance, as indicated by falls efficacy, may actually reflect the cardiovascular and mobility deficit state, as individuals respond psychologically to reduced fitness and motor function. Ambulatory activity and cardiovascular fitness levels were extremely low, and though fatigue severity was not statistically correlated, these variables may be evidence of an adaptation.

Further support of the connection of physiologic burden to fatigue is the relationship of the Berg Balance Scale to fatigue severity (r = –0.422, p = .004). Gait and balance have long been recognized as important outcome measures in stroke motor recovery. In a previous investigation (Michael, Allen, & Mocko, 2005), we found that Berg Balance Scale scores strongly predict ambulatory activity levels. Balance was also highly correlated with fatigue severity. However, we also found strong relationships between VO2 peak and the Berg Balance Scale, suggesting that low cardiovascular fitness and increased physiologic workload in the presence of balance deficits (Corcoran, Jebson, Brengelmann, & Simons, 1970; Gersten & Orr, 1971; Macko et al., 2001b) may indirectly influence the outcome of fatigue severity. Although muscle weakness and loss of coordination are the primary impairments that affect gait after a stroke, impaired cardiovascular/metabolic fitness may secondarily affect gait performance by limiting walking endurance (Kelly, Kilbreath, Davis, Zeman, & Raymond, 2003), and result in self-perceived fatigue.

Individuals with stroke with fatigue reported significantly lower levels of social support compared with non-fatigued patients. Fatigue coupled with physical impairments may render individuals with stroke less inclined to engage in social activities. Further, as shown in the FSS scores, the symptom of fatigue may link back to motivation, and may reflect a degree of social isolation. The directionality of the relationship of fatigue to social support is worthy of further exploration.

Fatigue in individuals with stroke carries significant clinical consequences. Even small reductions in motivation, exercise behavior, and physical function as shown in the symptom of fatigue can negatively affect ADLs. Loss of independence in such basic activities hampers personal freedom, reduces autonomy, and renders individuals with stroke vulnerable to the detrimental physical and psychosocial effects of physical inactivity (Cooper et al., 1999).

This study underscores the importance of recognizing fatigue after stroke, and the psychosocial, behavioral, and self-efficacy components that combine with the physiologic factors to threaten function and independence. Specifically, rehabilitation nurses should carefully evaluate the presence and severity of fatigue as it relates to activity and self-care in individuals with stroke, and differentiate fatigue from other conditions such as weakness or depression. Because of its association with falls efficacy, fatigue should be considered an additional contributing factor in the determination of fall risk. Promoting and reinforcing activities that increase fitness and promote motor learning to improve gait efficiency may be helpful in managing fatigue stemming from the imbalance of energy reserves, and may also enhance self-efficacy through repeated practice. Family and friends may play an important part in helping to identify and reinforce successful fatigue management strategies, and in providing ongoing social support. If rehabilitation nurses are to effect change in fatigue symptom distress and fatigue-related behaviors that contribute to progressive disability after stroke, they must focus not only on fitness and mobility, but also on factors such as social support, self-efficacy, and the reinforcement of daily activity.

These results must be interpreted with caution because of the small sample size and the collinearity of fitness and mobility variables that may have masked some associations. There is also the possibility of sample selection bias, as participants were community-dwelling volunteers, who had mild-to-moderate hemiparetic deficits and may have been at a higher functional level than the general chronic stroke population. It is also likely that medical comorbidities were underrepresented, as nearly half of the initial candidates were excluded from the sample for medical reasons. The concern is that we may underestimate the extent and consequences of fatigue relative to ambulatory activity, mobility deficits, and poor cardiovascular fitness in the general population of individuals with chronic hemiparetic stroke.

Conclusions

In summary, 46% of individuals with chronic hemiparetic stroke had fatigue, with greatest severity in the areas of motivation, exercise, and physical function. Although fatigue was not directly associated with fitness variables or ambulatory activity levels, our data suggest that the physiologic burden of mobility deficit may play a part in the expression of fatigue. Moreover, the association of falls efficacy and social support with fatigue severity suggests that perceptions about disability and social isolation contribute to the experience of fatigue. The extremely low ambulatory activity profiles seen in the stroke patients may be a response to symptom distress. A behavior pattern developed in part to alleviate subjective fatigue secondary to the deconditioning and mobility deficits. Further studies are needed to evaluate whether rehabilitation strategies that include not only fitness and mobility interventions, but also social/behavioral and self-efficacy components, are associated with reduced fatigue and increased activity patterns in the everyday lives of stroke survivors.

Acknowledgments

This study was supported in part by the University of Maryland Claude D. Pepper Older Americans Independence Center, National Institute on Aging grant number 5-P60-AG12583. Study activities were conducted at the Baltimore Veterans Affairs Medical Center Geriatric Research Education Clinical Center (GRECC), and the University of Maryland Department of Physical Therapy and Rehabilitation Science.

About the Authors

Kathleen M. Michael, PhD RN CRRN, is assistant professor at the University of Maryland Schools of Nursing and Medicine and is program manager for the University of Maryland Claude D. Pepper Older Americans Independence Center.

Jerilyn K. Allen, ScD RN FAAN, is professor and associate dean for research at the Johns Hopkins University School of Nursing.

Richard F. Macko, MD, is professor, neurology and medicine, University of Maryland Division of Rehabilitation Medicine and Gerontology; director, Academic Rehabilitation Program, University of Maryland, School of Medicine; and director, VA Center of Excellence in Exercise and Robotics and the VA Stroke Research Enhancement Program.

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