Among the neurophysiologic factors, transcranial magnetic stimulation (TMS)–related measures were found to be the most commonly used to examine upper extremity motor function after stroke (Table 4). They were used in 27% (15 of 56) of the studies reviewed. The predictors of physical factors included visual functions, speech functions, upper extremity sensorimotor functions, and lower extremity motor functions (Table 5). Not surprisingly, the most popular predictor measures were tests of motor impairment, sensory impairment, and arm and hand function. However, only three studies53,55,65 examined hand dexterity, which is very important for upper extremity function in daily life. Incorporating the contralesional arm into life activities is a realistic and important goal for poststroke persons.6 All sociocognitive factors fell into the body functions/structures category. The defining feature of each, including perceptions, expectations, and emotion-related measures, is that they reside in the body/mind-body of the individual; most could be sequelae of the neurologic insult or be premorbidly present but impairments all the same.86 Predictors that capture sociocognitive factors such as self-efficacy may also provide important insight into the recovery of voluntary arm use in daily life.87–89 However, we did not find any studies using self-efficacy as a predictor measure in their models. Cognition, memory, emotion, and motivation were the sociocognitive factors that were observed and used to predict upper extremity outcomes at follow-up (Table 6).
At follow-up, most outcome measures were found to be in the domain of body functions/structure. Motor capability of the contralesional limb in the domain of body functions/structure was described with measures of range of motion, muscle strength, arm movement-related functions, and kinematic analysis (Table 7). Muscle strength was found to be the most popular outcome measure in this review. Twenty-two studies (39%) considered hand or arm muscle strength using the manual muscle test,39,58 hand-held dynamometry,67,70,90 the Medical Research Council guidelines,40,43–45,52,59,80,81 the Motricity Index,22,41,46,47,66,76,85 the Canadian Neurological Scale (distal arm),48 or the NIH Stroke Scale (arm).57 Although the kinematic measures are not as convenient for clinical assessments, they provide specific information about qualitative features of upper extremity movements, such as accuracy, efficiency, and speed79 and may be sensitive to motor capacity changes.
Few outcome measures were found to be in the domains of activities and participation. Unlike the muscle strength measures, the Fugl-Meyer Assessment (FMA) upper extremity motor score includes both body functions/structures and activities domains. The FMA was widely used in the studies (n = 14) reviewed here.19,42,49–51,54,60,61,67,68,75,76,83,84 However, none of the measures were considered representative of the participation domain. In the context of activities, the MAL is the only measure useful to quantify how much and how well the contralesional arm is used voluntarily in daily life activities. However, the three studies that used the MAL were ranked weak in methodological quality evaluation.67,71,82
Across the 56 studies, the time points of capturing outcomes varied from a few weeks45,82 to more than a year (Table 8).49,81 A six-month observation period was considered sufficient for determination of functional outcomes.91 Approximately 41% (23 of 56) of the selected studies had chosen a six-month period for capturing outcomes.17,19,22,48,50,51,53,56,60,62–64,67–69,70,71,73,76–78,85,92 The quality evaluation of internal, statistical, and external validity is summarized in Table 8.
In the 56 included studies, more than 95% used reliable and valid instruments for predictors and outcome measures (54 and 56 studies, respectively). Approximately 35% (19 of 56) used raters who were unaware of individuals' pathologic information and treatment program arrangement. Use of blinded raters is intended to decrease potential observational bias in data collection.36 In 98% (55 of 56) of the sample, participant dropout information (eg, withdrawal because of death or migration) was provided.
In 45 of the 56 studies, the time point of first obtaining predictor measures was within three months of stroke onset. The timing of this initial evaluation varied from several days (17 studies)7,39,40,43–45,49,50–53,57,58,64,66,68,76 to several months or years (7 studies).17,62,67,69,71,72,74,82,92 Of the studies in which predictor measures were obtained during the first few days after stroke onset, 53% (9 of 17) used TMS-related measures,39,40,43–45,49–52 24% (4 of 17) used imaging-related measures,53,57,58,68 and 24% (4 of 17) employed functional examinations.7,64,66,76 In studies in which the first time predictor measures were obtained more than three months after stroke onset, the study population was likely in the subacute/chronic stage of recovery, and the primary study purpose was to measure responsiveness to various interventions.17,62,67,71,82,92
Eighty-four percent (47 of 56) of the studies provided rationales for the statistical methods of detecting the relationship strength between predictor and outcome measures. The remaining 16% limited analysis to descriptive plots of predictor-outcome relationships. Thirty-four percent (19 of 56) of the studies did not have a sample size sufficient to provide a valid test of the prediction model. Forty-eight percent (27 of 56) of the studies used regression analysis. A control for multicollinearity was observed in only 9 studies of the subgroup of the studies that established the regression models (33%, 9 of 27 studies).44,56,60,62,69,71,74,79,83
Twenty-eight studies provided information about stroke pathology. The inclusion and exclusion criteria were specified in most of the studies (47 of 56). Sixty-eight percent (38 of 56) reported additional medical or paramedical interventions during the period of study. Only one study used cross-validation to establish a prediction model in a second group of poststroke participants.72 Similarly, only one study provided information about the clinical meaningfulness of the predictor and outcome measures.69
Using the best evidence criteria, 20 studies (36%) were retained for further analysis of significant predictors.21,44–47,50,51,53,54,56,60,62,63,69,74,75,79–81,83 The best predictors of arm-specific outcome measures were the initial neurophysiologic factors44–47,50,51,53,54,80,81 and initial motor capability.44,53,56,60,62,63,69,74,75,79,83 Among the neurophysiologic factors, the presence of a motor evoked potential (MEP), MEP amplitude, and MEP latency were the most frequently used variables. All were TMS-related measures.44–47,50,51,84 Lesion location in the brain and neuronal activation in the motor cortex were the predictor measures captured by imaging techniques.53,54,80,81 The most commonly used predictor measures of initial motor capability were deep sensation,60 muscle tone,60,79 active range of motion,62,79 muscle strength,44,56,79 and performance-based measures (eg, the FMA).53,56,60,63,69,74,75,83
Fifty-six of 935 studies met criteria for inclusion in this systematic review. Between 1979 and April 2008, there was a 317% increase in the frequency of published studies designed to determine the critical predictors of voluntary arm recovery after stroke. The frequency of such studies rose from 1.05 per year before 2000 to nearly 4.38 per year after 2000. There has been a profound increase in the prevalence of this kind of clinical research during the last eight years. This increase may be due in part to recent developments of valid and reliable predictor measures of poststroke upper extremity motor function that should prove useful to inform appropriate therapeutic programs. However, it should be noted that for the most part, this review was based primarily on prognostic studies rather than clinical intervention studies. In addition the included research studies were selected from a limited set of databases that did not include dissertations, theses, or conference proceedings, and further, the citations from selected articles were not checked for inclusion. Although clinical practice in neurologic physical therapy is becoming more evidence-based, it is far from routine use of prognostic tests and indicators to prescribe therapeutic programs.
To optimize the predictive value of arm-specific outcomes, 90% of the stroke participants from the selected studies were investigated in the acute/subacute stage. This is likely the case because assessments conducted in later stages of recovery may not provide sufficient predictive value for functional outcomes.56 Most of the studies of stroke rehabilitation recruit persons with either ischemic or hemorrhagic stroke because the outcome response to intervention is somewhat different between these two groups.93 For the purpose of this review, we included both types of stroke as long as the primary lesion was isolated to one hemisphere and resulted in a hemiparetic syndrome. This approach would have been appropriate to test the hypothesis that predictors of upper extremity motor function recovery are different between these two stroke etiologies. However, it is not possible to separate the results by stroke pathology because 54% (30 of 56) of the studies did not report stroke pathology. Only three studies reported inclusion of people with hemorrhagic stroke. Although we did not obtain complete information about the prevalence of each stroke type, it is reasonable to estimate that those with an infarction are much more numerous than those with hemorrhage (approximately 70% and 30%, respectively). According to statistics published by the American Stroke Association in 2008, approximately 10% of ischemic strokes and 40% of hemorrhagic strokes result in death within one month after stroke onset among persons aged 45 to 64 years,94 indicating that a greater number of individuals with infarct strokes than those with hemorrhagic strokes survive the acute phase. Because the clinical symptoms and recovery time course between infarct and hemorrhagic-type strokes are different,27 this information is most helpful here and for future prognostic studies.
This review focused on measurement used to capture voluntary arm use. To better understand arm-specific functional recovery, the ICF was used to categorize both predictors and outcome measures because it has been used widely to characterize health and disability in clinical practice and research through a framework for delivering goal-oriented rehabilitation.4 Recently, Salter et al95–97 selected 20 popular outcome measures with acceptable reliability and validity and further classified them using the ICF. Based on whether these outcomes captured the context of body functions/structures, activities, or participation, they were categorized into only one ICF domain. However, a number of stroke-related measures are designed to capture basic motor capacity and/or general functional recovery. Therefore, to classify a given measure into a single ICF category may be insufficient for fully characterizing the measure. In addition, there are other limitations to this kind of single-domain approach. First, the boundaries between ICF levels are not clear-cut.28 Second, the testing items of an instrument may be used to measure motor capabilities at different ICF levels. For example, the FMA includes items both at the levels of body functions/structures (eg, reflex) and activities (eg, grasp). Therefore, for this review, we allowed a measure to be classified in more than one ICF level. In this way, it provides a more comprehensive analysis of the various measurement instruments used for prognostication of functional upper extremity motor recovery after stroke.
Together, neurophysiologic measures43–47,50,51,53,54,80,81 and initial sensorimotor abilities44,53,56,60,62,63,74,75,79,83 have been shown to be the best predictors of arm-specific outcomes. The neurophysiologic measures provide a useful metric of the integrity of motor pathways, which is a viable index of functional motor performance.42 Additionally, neurophysiologic measures can be gathered in the early poststroke stage and require minimal participant cooperation.98 Measures of initial sensorimotor function provide a direct evaluation of motor behavior and reveal fundamental motor capability consequent to the stroke. These sensorimotor measures may be more sensitive to the effects of specific interventions than the neurophysiologic measures.60 However, it is also the case that a majority of the voluntary sensorimotor function measures are more vulnerable to associated neurologic impairments such as aphasia, apraxia, and neglect than direct neurophysiologic measures. Although the majority of the predictor models tested included a number of predictor variables, only five of 26 included neuroimaging and clinical variables together in their models.42,44,53,61,68 In all cases, the combined predictor variables resulted in a higher percentage of the outcome variance explained.
Unfortunately, there is still considerable controversy pertaining to the magnitude of a clinically meaningful change in the majority of upper extremity motor ability outcome measures. This highlights the importance of MCID determination for studies related to stroke interventions, particularly those pertaining to upper extremity recovery. It is of special note that only one study reviewed here provided information about MCID.69
The general definition of participation in the ICF is “the involvement of an individual in a life situation.”96 More specifically, the participation level of functional upper extremity motor recovery is defined as the involvement of the arms in life situations. In this review, very few predictor or outcome measures were classified at the participation level. Most of the measures pertained to the body functions/structures level. Using measures at the body functions/structures level may gather sufficient information to examine predictors, but does not provide significant information to examine outcome measures. Because voluntary arm use in daily activities is the primary objective for poststroke individuals,5,6 outcome measures classified at the participation level would be expected to provide information about how individuals incorporate their paretic arms in life situations at home or in the community.
Other than outcome measures that capture motor capability level of arm-specific function in daily life,7,20,21,75 the MAL is a useful measure to quantify how much and how well the contralesional arm is used in daily life activities. The MAL has been shown to have high internal consistency (Cronbach α ≥ 0.88) and moderate construct validity (Spearman ρ = 0.63) in persons with chronic stroke.12 In addition, the MAL has good interrater reliability (interclass correlation coefficient = 0.90–0.94).12 This review identified three studies that used either raw or change scores for the MAL posttreatment as an outcome measure to investigate the predictors of functional upper extremity motor recovery after Constraint-induced movement therapy in individuals more than six months poststroke.67,71,82 The potential predictors investigated in these three studies were individual/stroke characteristics (eg, side of stroke location, time since stroke, hand dominance, age, sex, and ambulatory status);71 persons' cognitive functions (measured by the Mini-Mental State Examination, the short-form Token Test, the Sustained Attention to Response Task, Logical Memory and Visual Reproduction subtests from the Wechsler Memory Scale, and the Trail Making Test Form B);82 and upper extremity motor severity (measured by the FMA).67
Interestingly, measures of individual/stroke characteristics and cognitive functions did not reach significance when examining the prediction model of actual arm use measured by the MAL.71,82 However, motor severity classified by the FMA was correlated with the changed MAL score after a community-based upper extremity group exercise among individuals with chronic stroke (mean poststroke duration 5.1 years).67 Persons in the mildly impaired group gained 1 point on the MAL, whereas persons in the moderately/severely impaired groups gained 0.2 to 0.5 points on the MAL.67 It seems that motor severity classified by the FMA is a better discriminator than the MAL in predicting which person might benefit the most from the community-based group exercise. Yet it is not clear whether motor severity captured in the acute stroke stage has good predictive value in relation to outcome measures of voluntary arm use. More studies using measures at the activities and participation level are needed to establish cause-and-effect relationships between predictors and outcome measures of voluntary arm use in real-life situations.
This is the first systematic review focused on critical predictors of arm-specific motor recovery that incorporated the ICF for meaningful outcomes of voluntary arm recovery in hemiparetic stroke. Until recently, clinical research has paid little attention to the more distal outcomes represented by the activities and participation categories in the ICF. Not surprisingly, initial measures that capture the integrity of neural connections (eg, in the corticospinal tract) and voluntary motor behavior were the best predictors of functional arm recovery at follow-up. This finding supports the usefulness of a top-down approach in which task-oriented training programs are developed and aimed at reducing the functional limitations apparent in contralesional limb use.99 The fact that few outcome measures for voluntary arm use exist at the participation level of the ICF underscores the need to develop reliable and valid measures of arm use in real-life environments.
The authors thank Pamela Corley for her help in developing the keywords/databases search and Dr. Sharon Myers, Jill Stewart, and Hsiu-Chen Lin for their suggestions or comments on the preparation of the manuscript.
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Keywords:© 2009 Neurology Section, APTA
voluntary arm use; prediction; clinical meaningfulness