Probability of Regaining Dexterity in the Flaccid Upper Limb
Impact of Severity of Paresis and Time Since Onset in Acute Stroke
Background and Purpose— To improve the accuracy of early postonset prediction of motor recovery in the flaccid hemiplegic arm, the effects of change in motor function over time on the accuracy of prediction were evaluated, and a prediction model for the probability of regaining dexterity at 6 months was developed.
Methods— In 102 stroke patients, dexterity and paresis were measured with the Action Research Arm Test, Motricity Index, and Fugl-Meyer motor evaluation. For model development, 23 candidate determinants were selected. Logistic regression analysis was used for prognostic factors and model development.
Results— At 6 months, some dexterity in the paretic arm was found in 38%, and complete functional recovery was seen in 11.6% of the patients. Total anterior circulation infarcts, right hemisphere strokes, homonymous hemianopia, visual gaze deficit, visual inattention, and paresis were statistically significant related to a poor arm function. Motricity Index leg scores of at least 25 points in the first week and Fugl-Meyer arm scores of 11 points in the second week increasing to 19 points in the fourth week raised the probability of developing some dexterity (Action Research Arm Test ≥10 points) from 74% (positive predictive value [PPV], 0.74; 95% confidence interval [CI], 0.63 to 0.86) to 94% (PPV, 0.83; 95% CI, 0.76 to 0.91) at 6 months. No change in probabilities of prediction dexterity was found after 4 weeks.
Conclusions— Based on the Fugl-Meyer scores of the flaccid arm, optimal prediction of arm function outcome at 6 months can be made within 4 weeks after onset. Lack of voluntary motor control of the leg in the first week with no emergence of arm synergies at 4 weeks is associated with poor outcome at 6 months.
Although prospective epidemiological studies are lacking, findings of a number of longitudinal studies indicate that, in 30%1 to 66%2,3 of hemiplegic stroke patients, the paretic arm remains without function when measured 6 months after stroke, whereas only 5% to 20% demonstrate complete functional recovery.1,4 To date, most studies showed that type and localization of stroke and initial severity of paresis of the upper limb are some of the best predictors for outcome at 6 months.2–7 The findings from all longitudinal studies with repeated measurements in time indicate that recovery of neurological impairment and disability shows a nonlinear pattern as a function of time,1–6 but only few patients show additional improvement after 3 months after stroke. In addition, most studies found that the optimal prediction of outcome can be made within 4 to 5 weeks after stroke onset.1–3,6 The absence of a measurable grip function at ≈1 month after stroke was found to be indicative of a poor functional recovery of the hemiplegic arm,1–3 whereas early return of voluntary motion of the paretic arm within the first weeks after stroke is considered to be a good prognostic sign.2,3,7 Most likely, the length of time during which one finds a lack of improvement reflects the intrinsic cerebral damage and should be seen as an important predictor of poor outcome.7 Knowledge on outcome of the upper limb is of paramount interest to clinicians to optimize their treatment goals and to inform patients properly. In those cases in which some return of dexterity is expected, training the paretic arm is justified. However, if the prognosis is poor, teaching the patient to deal with existing deficits may be more realistic, thus allowing for the use of compensating strategies. The first aim of the present study was to develop a prediction model for estimating the probability of obtaining dexterity of the paretic arm at 6 months in patients with a severe middle cerebral artery (MCA) stroke. The second objective was to investigate the effects of poststroke time on probabilities for developing dexterity at 6 months after stroke.
Subjects and Methods
Over a period of 32 months, 102 stroke patients were recruited from 7 hospitals to participate in this prospective cohort study. All patients except 1 participated in a randomized controlled trial on the effects of intensive rehabilitation in acute MCA stroke.8 The original study incorporated 3 treatment arms, all of which received a basic rehabilitation program formulated on evidence-based guidelines and consisting of an eclectic approach to neurofacilitation techniques with emphasis on task-specific goals for the arm and leg. Arm rehabilitation included functional exercises that facilitated arm and hand activity such as leaning, punching a ball, grasping, and moving objects. The key elements in leg rehabilitation were sitting, standing, and performing weight-bearing exercises during standing and walking, with an emphasis on achieving stability and improving gait velocity. If treatment at the disability level was not possible, strengthening exercises for arms and legs were promoted. Each of the 3 arms received additional therapy, consisting of either extra arm or leg exercises or air splint immobilization (ie, control group). All therapy was based on 1-to-1 contact between therapist and patient. In total, this contact amounted to 1 daily hour of physiotherapeutic and occupational therapeutic intervention during 5 days a week over a 20-week period. After this period, decisions regarding type of treatment were made by the relevant stroke management team. The rehabilitation program can be characterized as intensive, fine-tuned toward individual patient needs, and representative of today’s approach to care in many of the stroke service facilities around the world.
Stroke diagnoses were based on the World Health Organization definitions.9 The research protocol was approved by the ethics committees of each participating facility.
Stroke patients met the following admission criteria. Subjects (1) suffered a primary ischemic MCA stroke as revealed by CAT or MRI scan; (2) were 30 to 80 years of age; (3) presented with an impaired motor function of the upper and lower extremities; (4) lacked a complicating medical history that may be restrictive to activities of daily living (ADL); and (5) demonstrated no severe deficits in communication, memory, or understanding. A speech therapist assessed the ability to communicate and accepted a cutoff point of the 50th percentile corrected for age on the Dutch Foundation Aphasia test (SAN).10 The Mini-Mental State Examination (MMSE) was applied to screen for cognitive impairment.11 Patients with an MMSE score of ≥24 points were included in the trial.11 Within 24 hours after stroke onset, all patients were assessed by a neurologist. After the diagnosis was confirmed and the clinical symptoms such as level of consciousness (Glasgow Coma Scale [GCS])12 were recorded, the neurologist then referred the stroke patient complying with the selection criteria to the observer (G.K.) for recruitment and further assessment, which occurred within the initial 2 poststroke weeks.
The outcome of hemiplegic arm function was assessed with the Action Research Arm test (ARAT).13 This unidimensional hierarchical scale14 consists of 19 functional movement tasks that are divided into 4 domains: grasp, grip, pinch, and gross movement.13 Patients with scores of ≤9 points are not able to perform more than gross movements such as grasp, grip, and pinch. Therefore, any ARAT score of at least 10 points indicates some functional ability of the paretic hand and scored a 1 in the prediction model, whereas patients who failed to regain some dexterity (ie, ARAT score of ≤9 points) scored a 0.
Candidate determinants for development of a prediction model included the following: (1) age; (2) sex; (3) localization of stroke; (4) type of stroke (ie, according to the Bamford Oxford Community Stroke Project [OCSP] classification);15 (5) days between stroke and first assessment; (6) cognitive impairment (MMSE, 0 to 30 points);11 (7) consciousness during initial 24 hours after stroke onset (GCS, 0 to 15 points);12 (8) sitting balance (score 25 points on sitting balance item of Trunk Control Test);8 (9) ADL score (Barthel Index [BI], 0 to 20 points);16 (10) urinary incontinence (scores 0 or 1 on the BI);16 (11) sensory deficit in the arm as determined by the Thumb-Finding Test (0 to 3 points);17 (12) Orpington Prognostic Score (1.6 to 6.8 points); (13) homonymous hemianopia18 (no=0/yes=1); (14) inattention (1 if >2 omissions on the letter-cancellation test);18 (15) conjugate gaze19 (no=0/yes=1); (16) social support (no=0/yes=1); (17) type of (additional) therapy (air splint, arm, or leg training; 0 to 2)8; and (18) severity and extent of paresis of upper and lower extremity motor function in arm and leg as assessed by the Motricity Index (MI)20 and motor parts of the Fugl-Meyer (FM) score.21 In the MI, muscle strength was measured for upper extremity (MI arm, 0 to 100) in which 100 points represents normal strength and lower extremity (MI leg, 0 to 100) separately, whereas FM motor scores were subdivided into FM arm score (including wrist, 0 to 52), FM hand score (0 to 14 points), and FM leg score (0 to 34 points) in which the maximum score represents no synergism.
The research protocol started within 14 days after stroke onset. Clinical outcome parameters such as motor function tests (FM and MI), Thumb-Finding Test, inattention, ARAT, and ADLs were measured weekly during the first 10 weeks of the study. Final outcome was defined at 6 months after stroke. With the exception of the GCS and SAN tests, all measurements were performed by 1 independent investigator (G.K.).
To investigate the possible association between return of dexterity on ARAT (ie, >9 points) and independent variables, univariate logistic regression analysis was applied, and odds ratios and 95% confidence intervals (CIs) were calculated. Although Van der Lee et al14 used 6 points as the cutoff, a more conservative approach was used in this study to ensure the exclusion of possible false positives. With this in mind, ordinal scaled determinants were dichotomized (0/1) on the basis of clinical grounds; otherwise, the optimal cutoff point for each determinant was determined by applying a receiver-operating characteristic. This area under the curve can be interpreted as the probability of correctly predicting patients on ARAT. On the basis of sensitivity/1−specificity and maximal area under the curve for each cutoff score, the optimal dichotomization was estimated for each candidate determinant separately. Finally, to control for change in the optimal cutoff points as a result of functional recovery, the receiver-operating characteristic curves for each candidate determinant were recalculated weekly until the 10th week after stroke.
Based on univariate logistic regression analysis, significant determinants were selected for the subsequent development of a multivariate logistic model necessary for the prediction of the return of some (ie, ARAT ≥10 points) or no (ie, ARAT ≤9) dexterity 6 months after stroke. Because of the large number of variables with respect to number of patients involved, the maximum likelihood estimation of parameters in the multivariate model was conditional on the basis of a forward, stepwise approach.22 Collinearity between included determinants was removed if correlation coefficients of the correlation matrix in the model were ≥0.7. Finally, probabilities of developing dexterity at 6 months after stroke and their 95% CIs were calculated from the derived multivariate models for each week using the constants and regression coefficients of the predictor variables in the following equation:
Each hypothesis was tested 2 tailed with a level of significance of 0.05.
Table 1 presents the main patient characteristics. On the first assessment, all patients showed a BI of ≤45% (≤9 points), which corresponds to (very) severely disabled.22 None of the patients demonstrated some dexterity or were able to walk independently at the end of the first week (ie, week 1). Two patients died within 6 months after stroke as a result of a recurrent stroke or oncological comorbidity. At 6 months after stroke, 33% of the patients were classified as independent (BI, 19 or 20 points). Approximately 38% showed some recovery in dexterity of the hemiplegic arm (ARAT ≥10 points). From these patients, 11.6% reached a complete functional recovery in dexterity of the paretic arm (ie, 57 points on ARAT) at 6 months.
Univariate Associations Between Dependent and Independent Variables
Table 2 shows odds ratios and their 95% CIs as determined by univariate logistic regression analysis for the second week after stroke. Of 23 variables, 18 were significantly related to the probability of the return of dexterity on ARAT obtained 6 months after stroke. The highest odds were found for the total scores of FM motor scores of upper extremity (UE) (ie, hand and arm scores together), their subscores (ie, FM hand and arm score separately), and the MI arm and leg scores.
Table 3 shows the variables included in the prediction model at their optimal cutoff points and the probabilities of achieving dexterity 6 months after stroke. Depending on the poststroke week of assessment, FM UE alone and MI leg were included in the multivariate model. The correlation between the determinants MI leg and FM UE varied from 0.33 for week 2 to 0.37 for week 3, indicating no problems with near collinearity.
As shown in Table 3, in the first week after stroke onset, only MI leg was included into the model. On the basis of regression coefficients and constants, the probability of achieving some dexterity was estimated at 0.74 if the patient reached an MI leg score of ≥25 points at stroke onset and 0.14 if the MI leg score was <25 points.
After the FM UE scores were included, the model performance in weeks 2 and 3 showed an increase in probabilities for achieving dexterity of 0.89 (95% CI, 0.71 to 0.97) and 0.90 (95% CI, 0.74 to 0.96), respectively.
From week 4 on, the model was based on FM UE scores alone, without MI leg scores. A maximal probability of 0.94 (95% CI, 0.74 to 0.99) was achieved in week 4 in those patients who reached an FM UE score of ≥19 points), whereas a probability of 0.09 (95% CI, 0.04 to 0.19) was found for those patients who did not reach this level at week 4 after stroke.
In addition, it was found that the optimal cutoff point for FM UE, which changed from 11 points at week 2 to 19 points at week 4, was highly associated with motor control of the paretic hand and the ability to move in postsynergic patterns. Further analysis showed that the FM UE scores for each week were strongly associated with the FM hand scores. Correlation coefficients between FM arm and FM hand scores increased from 0.58 (P<0.001) in week 1 to 0.93 (P<0.001) in week 4 on.
Recalculating the probabilities from 5 weeks on showed no significant change in time.
It is important to note that this study was restricted to a homogeneous group of patients participating in a 3-arm randomized intervention trial8 with first-ever severe stroke in the territory of the MCA resulting in complete hemiplegia. In most cases (76%), this hemiplegia incorporated a paralysis of the upper limb at onset. For this group of patients in particular, early, accurate prediction of dexterity is often perceived as difficult and unreliable. The present study shows that 62% failed to achieve some dexterity at 6 months, indicating that the prognosis for functional outcome in MCA stroke is poor.
The present study demonstrates some important clinical findings for the rehabilitation management of stroke patients with a virtual paralysis of the upper limb at onset. First, prediction in the first week after an MCA stroke leading to a flaccid arm can best be based on muscle strength of the hemiplegic leg. This finding suggests that patients who developed some voluntary movement over hip, knee, and/or foot (ie, ≥25 points on MI leg) in the first week after stroke had about a 74% chance of regaining some dexterity, whereas absence of voluntary leg movements reduced this probability to 14%. This finding is in agreement with the results of a prospective study from Wade and colleagues2 and indicates that severity and extent of infarction in the territory of the MCA in the acute phase correspond not only to the severity of paresis of the arm but also to the extent in which the lower limb is involved. Moreover, Shelton and Reding23 recently showed that stroke patients with an additional lower limb plegia within 2 weeks after MCA stroke had a highly predictable poor outcome for the return of isolated arm or hand movements after 6 months on the basis of the FM motor scores.
After the first week, however, the strongest clinical factor that predicts outcome of dexterity at 6 months is severity of paresis of the arm. In addition, it was found that the optimal prediction of outcome of dexterity can be made within the first month after stroke by measuring motor recovery of the upper limb. At the end of week 4, a probability of ≈94% was found in those patients who had an FM UE score of ≥19 points. In contrast, the chance to achieve some dexterity at 6 months dropped to only 9% in those patients who failed to achieve this level of motor performance within 4 weeks. Remarkably, no further improvement in accuracy of prediction was found after 4 weeks, suggesting that long-term outcome of dexterity can already be optimally predicted within this time frame. In agreement with previous reports,1–3,6 this latter finding suggests that the time window for predicting the return of dexterity is limited to only 1 month after onset.
It is important to note that the optimal cutoff point for FM UE and MI leg scores is not fixed in time but is dependent on the poststroke time of assessment. Apparently, a gradual improvement in motor function during the first 2 months after stroke onset is required to develop some dexterity at 6 months. This finding underscores that severity of hemiparesis and lack of substantial improvement of motor function in the first weeks are factors associated with poor outcome. Therefore, the amount of change in motor function, particularly within the first weeks, may be regarded as an independent factor for the probability of developing a long-term functional upper limb, reflecting the initial severity of intrinsic cerebral damage and the process of neurological recovery. Conversely, the above findings suggest that, in patients without some dexterity at onset in whom motor recovery is lacking in the first 4 weeks, the outcome of the upper limb is likely to be poor at 6 months.
Future studies should focus on understanding the mechanisms that define the critical time window of functional recovery after stroke. Better understanding of the different time frames for mechanisms that contribute to functional recovery such as plasticity, a gradual reversal of diaschisis,24 and behavioral mechanisms that allow compensation strategies25 may have a significant impact on rehabilitation management of patients.
The present study predicted dexterity established at 6 months after stroke by analyzing repeated measurements of the variables of interest at fixed times after stroke. This approach allows us to determine the impact of early change in determinants such as strength on the accuracy of outcome. In our opinion, this approach realistically reflects the clinical practice of repeated observations in time. Therefore, we recommend that in future studies repeated measurement designs be applied to such issues as the way in which recovery of clinically relevant determinants may independently affect the final recovery of outcome.
The present study had some limitations. Because of the homogeneous patient population used, external validity may have suffered. In addition, all subjects recruited to participate in this cohort also participated in a 3-group randomized controlled trial.8 The applied treatment is representative of today’s approach to care in many of the stroke service facilities around the world. Small differences were found in favor of a 20-week upper extremity training program.8 This finding is reflected in the significant odds found for the treatment arm in the univariate logistic regression analysis. However, the term “treatment type” as a candidate determinant was not included in the multivariate model for predicting functional outcome of the upper limb at 6 months, indicating that prediction results were not affected by the type of treatment to which patients were randomized. Obviously, the limited time window for the prediction of regaining dexterity compared with the effects of upper limb treatment beyond 1 month suggests that the differences in effects are restricted to those patients with some return of dexterity. This finding is in agreement with the results of several other randomized controlled trials.26,27 However, both limitations (ie, homogeneity and the intervention) may have resulted in an underestimation of the probabilities of predictions.
This study was a part of a research project supported by a grant from the Netherlands Heart Foundation (reference No. 93.134). We gratefully acknowledge J.W.R. Twisk, PhD (Institute for Research in Extramural Medicine, VU University Medical Centre), for providing statistical advice and Els van Deventer (Department of Neurology) for collecting and copying relevant references.
- Received December 30, 2002.
- Revision received May 9, 2003.
- Accepted May 23, 2003.
Heller A, Wade DT, Wood VA, Sunderland A, Langton Hewer RL. Arm function after stroke: measurement and recovery over the first three months. J Neurol Neurosurg Psychiatry. 1987; 50: 714–719.
Wade DT, Langton Hewer RL, Wood VA, Skilbeck CE, Ismail HM. The hemiplegic arm and recovery. J Neurol Neurosurg Psychiatry. 1983; 46: 521–524.
Sunderland A, Tinson DJ, Bradley L, Langton Hewer RL. Arm function after stroke: an evaluation of grip strength as a measure of recovery and prognostic indicator. J Neurol Neurosurg Psychiatry. 1989; 52: 1267–1272.
Loewen SC, Anderson BA. Predictors of stroke outcome using objective measurement scales. Stroke. 1990; 21: 78–81.
Duncan PW, Goldstein LB, Matchar D, Divine GW, Feussner J. Measurement of motor recovery after stroke: outcome assessment and sample size requirements. Stroke. 1992; 23: 1084–1089.
Twitchell TE. The restoration of motor function following hemiplegia in man. Brain. 1951; 75: 443–480.
WHO Special Report. Stroke-1989: recommendations on stroke patients: prevention, diagnosis, and therapy. Stroke. 1989; 20: 1407–1431.
Deelman BG, Liebrand WBG, Koning-Haanstra, van de Burg W. SAN test: an aphasia test for language comprehension and linguistic usage. In: Construction and Standards. Lisse, Netherlands: Swets and Zeitlinger BV; 1981.
Lyle RCA. Performance test for assessment of upper limb function in physical rehabilitated treatment and research. Int J Rehabil. 1981; 4: 483–492.
van der Lee JH, Roorda LD, Beckerman H, Lankhorst GJ, Bouter LM. Improving the Action Research Arm test: an unidimensional hierarchical scale. Clin Rehabil. 2002; 16: 646–653.
Presscott RJ, Garrway WM, Akthar AJ. Predicting functional outcome following acute stroke using a standard clinical examination. Stroke. 1982; 13: 641–647.
Lezak MD. Neurophysiological Assessment. 3rd ed. New York: Oxford University Press; 1995.
Kelley RE, Kovacs AG. Horizontal gaze paresis in hemispheric stroke. Stroke. 1986; 17: 1030–1032.
Collin C, Wade D. Assessing motor impairment after stroke: a pilot reliability study. J Neurol Neurosurg Psychiatry. 1990; 53: 576–570.
Sanford J, Moreland J, Swanson LR, Stratford PW, Gowland C. Reliability of the Fugl-Meyer assessment for testing motor performance in patients following stroke. Phys Ther. 1993; 73: 447–455.
Kleinbaum DG, Kupper, LL, Muller KE. Applied Regression Analysis and Other Multivariable Methods. Boston, Mass: PWS-KENT Publishing; 1988.
Shelton F, Reding MJ. Effect of lesion location on upper limb motor recovery after stroke. Stroke. 2001; 32: 107–112.
Cirstea MC, Levin MF. Compensatory strategies for reaching in stroke. Brain. 2000; 123: 940–953.
Sunderland A, Tinson DJ, Bradley EL, Fletcher D, Langton-Hewer R, Wade DT. Enhanced physical therapy improves recovery of arm function after stroke: a randomized controlled trial. J Neurol Neurosurg Psychiatry. 1992; 55: 530–535.
Lincoln NB, Parry RH, Vass CD. Randomized, controlled trial to evaluate increased intensity of physiotherapy treatment of arm function after stroke. Stroke. 1999; 30: 573–579.