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PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. http://hdl.handle.net/2066/23532 Please be advised that this information was generated on 2017-11-25 and may be subject to change.

Scand J Rehab Med 28: 3-7, 1996 A C R IT E R IO N FO R STABILITY O F TH E M O T O R F U N C T IO N OF TH E LO W ER EXTREM ITY IN STROKE P A T IE N T S U S IN G THE F U G L -M E Y E R A SSESSM E N T SC A LE H. Beckerman, MSc P T,1 T.W. Vogelaar, PT,1 G.J. Lankhorst, M D P h D 1 and A.L.M. Verbeek, M D PhD From the 1Department of Rehabilitation Medicine, A cade misch Ziekenhuis Vrije Universiteit Amsterdam, and "Department of Epidemiology, University of Nijmegen, The Nether!amis ABSTRACT. A test-retest reproducibility study was performed to define a criterion for stability as opposed designed to assess the recovery pattern of physical functions following stroke, was considered for digerito change of motor function of the lower extremity in mination of the stable and unstable group (6, 8, 9). stroke patients. Forty-nine patients with stroke were The Fugl-Meyer Assessment Scale consists of six examined twice by the same physiotherapist, using the separate scales to measure quantitatively motor func- Fugl-Meyer Assessment Scale. The interval between both measurements was three weeks. The mean diifertion o f the upper extremity and lower extremity respectively, balance, pain, range of motion, and enees between the first and the second measurement sensation. Nevertheless, it is unknown which criterwere small, with 0.04 points for the lower extremity ion, i.e. how many points of change during a followscale and 0.92 points for the balance scale, respectively. up period, has to be used in order to classify patients Intraclass correlation coefficient for the lower as neurologically stable or unstable. A quantification extremity scale was 0.86, and 0.34 for the balance of the magnitude of the measurement error in stable scale. The standard error of measurement for cach subjects could answer the question how much differscale was 1.76 and 1.17 points, respectively. The standard error of measurement can be transformed in an enee is due to real change, and how much is due to chance variation or measurement error. In the error threshold, which is a criterion to differentiate absence of real change it can be concluded that real changes from changes due to chance variation or there is a stable or stationary status. measurement error. As the absence of real change is a The purpose of this study was to define a criterion parameter for stability, a change of less than 5 points for stability o f the m otor function of the lower for the lower extremity scale and of less than 4 points extremity and balance, using a test-re test design, for balance confirms stability of motor function. Key words: reproducibility, cerebrovascular accident, lower extremity, measurement, reliability. M ETHODS Patients IN TR O D U C TIO N Stroke recovery generally begins early, with the main improvement occurring over the first three to four months after stroke. Thereafter, the recovery pattern generally reaches a plateau (7, 13, 16, 18). In randomized clinical trials it is thought necessary, although not always possible, only to include patients with a stable neurologic status, in order to prevent bias of the study results by spontaneous recovery (14). The Fugl-Meyer Assessment Scale, a disease-specilie performance-based measurement instrument especially The study population consisted of stroke patients referred to the outpatient Department of Rehabilitation Medicine of the Academisch Ziekenhuis Vrije Universiteit, Amsterdam. Patients between the ages of 18 to 75 years, who at least one year previously luid suffered an ischaemic or haemorrhagic stroke of a cerebral hemisphere resulting in hemiplegia, could participate. They were all experiencing walking problems caused by a spastic equinus or equino va rus position of the foot. Patients without sufficient communication and cognition functions, or with an unsatisfactory general condition were excluded. The participants were examined on two separate occasions with a 3-week interval. No clinically relevant changes in the motor function status of these chronic patients were cxpeetcd during this interval. All patients were examined by the same experienced physiotherapist (second author TWV). Sentid J Rehab Med 28

4 H. Beckevman et a i Table I. (n - 49) Variable Characteristics of the study population Gender Female 16 Male 33 Age (yrs) < 50 10 51-60 22 61-70 14 > 70 3 Months post-stroke 13-24 15 25-36 9 37-48 4 49-60 7 > 60 14 ITemiplegic side Left 24 Right 25 Type of stroke Haemorrhagic 13 Ischaemic 36 Number of participants Sixteen women and 33 men, with a median age of 58 years (range: 21-72 years), and with a median time since stroke of 37 months (range: 13-185 months) gave their informed consent to participate in the study (Table I). Data analysis Test-retest reproducibility was assessed by calculating 3 different numerical indexes: the intraclass correlation coefficient, the standard error of measurement, and the error threshold. These reproducibility indexes are all based on the analyses of variance components. Analysis of variance (ANOVA) was performed using the PC version of the program GENOVA, developed by Crick & Brennan (3). 1. lntraclass Correlation Coefficient (ICC). ICC is a preferred method of quantifying reproducibility (10). The ICC can be calculated as the ratio of the variance between subjects (i.e. patients) and the total variance. 2. Standard Error of Measurement (SEM). Quantifying the test-retest reproducibility of an assessment involves calculating the variability in measurements of the same patient. The SEM provides an interpretation of the magnitude of this within-subject variability, which is also known as error variance. The SEM is the square root of the within-subject variance (11, 17), and is expressed in the same dimension as the measurement. (Note that the standard error of measurement (SEM) is not synonymous with the standard error of the mean, also abbreviated as SEM.) 3. Error Threshold (ET). Assuming that the measurement errors of two measurements are independent of each other, an interval can be calculated which expresses the uncertainty about the difference between two true scores. The difference between both measurements should be at least 1.96*\/2*SEM in order to be 95% confident of a real difference between the true scores. We call the quantity 1.96*\/2*SEM the error threshold (ET). In other words, the ET is a criterion to differentiate real changes from changes due to chance variation or measurement error. Measi tremen t instrumen t In this study we used two subscales of the Fugl-Meyer Assessment Scale: the motor function of the lower extremity (FM-LE, 17 items, maximum score of 34 points) and the 'balance scale (FM-B, 7 items to test the sitting and standing balance, maximum score of 14 points). Most items consist of standardized motor activities which are to be performed independently by the patient. The scoring involves direct observation of the performance. Each performance is rated on an ordinal 3-point scale (0 = the item cannot be performed; 1 = the item can be partially performed; 2 = the item can be fully performed) (6). RESULTS Criterion for stability Descriptive statistics (the mean and standard deviation) for both parts of the Fugl-Meyer Assessment Scale are presented in Table II. O n the first measurement, the FM -LE score varied between 5 and 29 points (15% -85% of the maximum possible score), whereas the FM -B score varied between 6 and 14 points (43% -100% of the maximum possible score). Table II. Mean and standard deviation of the Fugl-Meyer Assessment Scale on two separate occasions with a three- week interval SD = standard deviation First measurement Second measurement Difference Fugl-Meyer Assessment Scale Mean SD Mean SD Mean SD Lower extremity (0-34) 17.67 4.50 17.71 4.89 0.041 2.483 Balance (0-14) 12.78 1.64 13.69 0.80-0.918 1.382 Scatuì J Rehab Med 28

Stability in the lower extremity in stroke patients 5 Table III. Test-retest reproducibility results of the Fugl-Meyer Assessment Scale ICC = Intraclass Correlation Coefficient SEM = Standard Error of Measurement ET - Error Threshold Fugl-Meyer Assessment Scale Between subject variance Within subject variance Total variance ICC SEM ET Lower extremity (0-34) 18.988 3.082 22.070 0.86 1.756 4.87 Balance (0-14) 0.701 1.357 2.058 0.34 1.165 3.23 r between-subject variance ^ ~ between -snbj ect v a ri a n ce t-wi t h i îvsiïeject va ria ncë SEM = ywi thin-subject variance = ^total variance * ^'(1-ICC) ET = 1.96* SEM The mean differences between the first and the DISCUSSION second measurement were small. Nevertheless, the differences varied between 5 points and + 9 points To gain more insight into the methodological quality on the FM -LE scale, and between 6 and + 2 points of instruments measuring change or, as in our case, on the FM-B scale. For the FM-B score the mean stability of the variable within a subject over time, difference between the first and the second measure- the standard error of measurement (SEM ) as well as ment was significantly different from zero (two-tailed the error threshold (ET) are well suited indexes since paired t-test: p-value 0.0001). No statistically significant relationship was found the magnitude o f within-subject variance is the most relevant (11, 12). The ET, which can be transformed between the test-retest differences and single patient from the SEM, is a real threshold to differentiate real characteristics (Table 1; /-tests, Pearson's correlation changes from changes due to chance variation or coefficients). The ICC for the FM -LE is 0.86, and 0.34 For FM - B (Table III). The SEM, which is expressed in the measurement error, ICCs are less appropriate since the variance between subjects is considered as the variance of interest, whereas stability depends on the same unit as the Fugl-M eyer score, is 1.76 and within-subject variance. Furtherm ore, in our study 1,17 points for each scale, respectively (Table 111), population, the ceiling effect of the balance scale Twice the SEM value approximately encompasses resulted in a skewed distribution o f balance scores, 95% of the obtained scores around the true and a relatively small between-subject variance. This score. For example, given that one single assessment has probably caused the low ICC of 0.34. By results in a FM -LE score of 18 points, the true score choosing a study population with a greater variety will lie between 14.5 and 21.5 points. The same (heterogeneity) of balance scores, the resulting ICC calculation could be presented for FM-B. The ET would be more impressive (10). Pearson s product for each scale is 4.87 and 3.23 points, respectively. moment correlation coefficients are even less appro- This means that, to be sure that the changes are pria te for quantifying test-retest reproducibility, real rather than due to a measurement error, the because systematic differences between measurescore of the FM -LE should increase by at least 5 ments are neglected (I, 4). Reliability studies of the points, whereas the score on the balance scale should increase by at least 4 points. These differences are Fugl-Meyer Assessment Scale using Pearson s product moment correlation coefficient should therefore equal to 15% and 29% of the maximum possible be interpreted with caution (2, 5). M oreover, reproscore. Smaller changes are to be interpreted as ducibility coefficients such as the ICC and Pearson s measurement error; there is no indication of real product moment correlation coefficient are expressed change and it may be inferred that the patient s as a dimensionless number between 0 and 1, and do motor function is stable. not open for a straightforward interpretation. Scam! J Rehab Med 28

6 H. Becker man ei al. In some way, our results could be compared with the results recently published by Sanford et al (15), investigating the interrater reliability of the Fugl-Meyer Assessment Scale among three experienced physiotherapists. They investigated 12 acute stroke patients (less than 6 months after the stroke), aged 49 to 86 years (mean age: 66 years). All patients were following an inpatient rehabilitation programme at the time of the reliability study. Patients were tested within one working day of the previous assessment. The interrater ICC for the lower extremity was 0.92 and for the balance score 0.93. The SEMs were 3.20 and 1.00, respectively. As compared with our results, the SEM of the lower extremity is 1.44 points larger, whereas the SEM of the balance score is nearly the same as in our study (1.00 versus 1.17). In general, intrarater (or test-retest) reliability is higher than interrater reliability because each rater brings in some variance. Nevertheless, the ICCs presented by Sanford et al are better than ours. This could be explained by the differences between the study populations with respect to the between-subject variance. Heterogeneity of subjects may account for higher ICCs. In our chronic stroke patients, the withinsubject differences were smaller, resulting in smaller SEMs. Short-term follow-up studies of stroke patients have shown that the motor recovery usually occurs and reaches its plateau within six months. Our chronic study population was investigated at least one year after their stroke. Therefore the motor function of the lower extremity and the sitting and standing balance of these chronic stroke patients were assumed to be stable between the first and second assessments. Because of the large standard errors of measurement, observed scores are obviously a very imprecise measure of the unknown true lower extremity and balance scores. Clinical decisions based on these imprecise scores will certainly bear a high risk of false decisions. Our study has shown that in chronic stroke patients a criterion of a 5-point change of the Fugl-Meyer lower extremity score, and a 4-point change of the balance score over a 3-week period seems scientifically valid to differentiate between stable and unstable (improved or deteriorated) stroke patients. These criteria, which are equal to 15% and 29% of the maximum possible score of each scale, are very large. Therefore, in clinical trials as well as in clinical practice, scores on the Fugl-Meyer Assessment Scale should be used with caution. A CK N O W LED G EM EN T This study is part of a project that has been supported by a grant from the Netherlands Heart Foundation (project 91.060). REFERENCES 1. Bland, J. M. & Altman, D. G.: Statistical methods for assessing agreement between two methods of clinical measurement. Lancet i: 307-310, 1986. 2. Brinker, B. P. L. M. den & Kobus, M. H.: Betrouwbaarheid van bewegingsobservaties van video-opnamen van de Fugl-Meyer test. Ned T Fysiotherapie 98: 120-122, 1988. 3. Crick, J. E, & Brennan, R.L.; Manual for GENOVA: a generalized analysis of variance system. American College Testing Program, Iowa City, 1983. 4. Deyo, R. A., Diehr, P. & Patrick, D. L.: Reproducibility and responsiveness of health status measures. Statistics and strategies for evaluation. Control Clin Trials 12: 142S-15SS, 1991. 5. Duncan, P. W., Propet, M. & Nelson, S. G.: Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther 63: 1606-1610, 1983. 6. Duncan, P. W. & Badke, M. B.: Measurement of motor performance and functional abilities following stroke. In Stroke rehabilitation: the recovery of motor control, (ed. P, W. Duncan & M. B. Badke). Year Book Publishers Inc, Chicago, 1987. 7. Duncan, P. W., Goldstein, L. B., Matchar, D., Divine, G. W. & Feussner, J.; Measurement of motor recovery after stroke. Outcome assessment and sample size requirements. Stroke 23: 1084-1089, 1992. 8. Fugl-Meyer, A. R., Jääskö, L., Leyman, J., Olsson, S. & Steglind, S.: The post-stroke hemiplegic patient. I: a method of evaluation of physical performance. Scand J Rehabil Med 7; 13-31, 1975. 9. Fugl-Meyer, A. R.: Post-stroke hemiplegia: assessment of physical properties. Scand J Rehabil Med suppl 7: 85-93, 1980. 10. Guyatt, G., Walter, S. & Norman, G.: Measuring change over time: assessing the usefulness of evaluative instruments. J Chron Dis 40: 171-178, 1987. 1L Guyatt, G. H., Kirschner, B. & Jaeschke, R.: Measuring health status: what are the necessary measurement properties? J Clin Epidemiol 45: 1341-1345, 1992. 12. Kramer, M. S. & Feinstein, A. R.: Clinical biostatistics. LIV. The biostatistics of concordance. Clin Pharmacol Ther 29: 111-123, 1981. 13. Partridge, C. 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Stability in the lower extremity in stroke patients 1 16. Skilbeck, C. E., Wade, D. T. & Langton Hewer, R.: Recovery after stroke. J Neurol Neurosurg Psychiatry 46: 5-8, 1983. 17. Streiner, D. L. & Norman, G. R.: Health measurement scales. A practical guide to their development and use. Oxford University Press, Oxford, 1993, 18. Wade, D. T. & Langton Hewer, R.: Functional activities after stroke: measurement, natural history and prognosis. J Neurol Neurosurg Psychiatry 50: 177-182, 1987. Address for offprints: Ms H Beckerman Department of Rehabilitation Medicine Academisch Ziekenhuis Vrije Universi te it PO Box 7057 NL-1007 MB Amsterdam The Netherlands Scand J Rehab M ed 2H