Skip Navigation


Age and Ageing Advance Access originally published online on May 4, 2006
Age and Ageing 2006 35(4):371-375; doi:10.1093/ageing/afj084
This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
35/4/371    most recent
afj084v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (2)
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Kumar, R. T. S.
Right arrow Articles by Sharma, A. K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kumar, R. T. S.
Right arrow Articles by Sharma, A. K.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

© The Author 2006. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Biomechanical measurement of post-stroke spasticity

Raj T. S. Kumar1, Anand D. Pandyan2 and Anil K. Sharma1

1 Department of Medicine for the Elderly, University Hospital Aintree, Liverpool L9 7AL, UK
2 Department of Physiotherapy Studies, Keele University, Staffs ST5 5BG, UK

Address correspondence to: R. T. S. Kumar. Tel: (+44) 151 529 8781 Fax: (+44) 151 529 3787 Email: raj.kumar{at}aintree.nhs.uk

Received 19 September 2005; accepted in revised form 13 February 2006


   Abstract
Top
 Abstract
Introduction
 Patients and methods
 Results
 Discussion
 Key points
 References
 
Background: spasticity following stroke is common, but clinical measurement is difficult and inaccurate. The most common measure is the modified Ashworth scale (MAS) which grades resistance to passive movement (RPM), but its validity is unclear.

Aim: to assess the validity of the MAS.

Methods: spasticity was clinically graded using MAS and RPM measured biomechanically in the impaired arm of 111 patients following stroke. The biomechanical device measured RPM, applied force, angular displacement, mean velocity, passive range of movement (PROM) and time required.

Results: the median age was 72 years, and 66 subjects were male. The clinical grading by MAS was ‘0’ in 15, ‘1’ in 15, ‘1+’ in 14, ‘2’ in 13, ‘3’ in 43 and ‘4’ in 11. There was no difference in RPM among ‘0’, ‘1’, ‘1+’ and ‘2’ (P>0.1). However, grade‘4’ was higher than ‘3’ and below (P<0.05). The force required increased with the increasing MAS while velocity and PROM decreased (P<0.01). We regrouped the data using the algorithm: no stiffness = ‘0’; mild = ‘1’ and ‘1+’ and ‘2’; moderate = ‘3’; severe = ‘4’. There was no difference between ‘no stiffness’ and ‘mild ’ (P>0.10), but ‘mild’ and moderate’ as well as ‘moderate’ and ‘severe’ were different (P<0.01).

Conclusion: the MAS is not a valid ordinal level measure of RPM or spasticity. Objective measurement of RPM is possible in the clinical setting. However, additional measurements of muscle activity (electromyography) will be required to quantify spasticity.

Keywords: stroke, cerebrovascular accident, spasticity, measurement, elderly


   Introduction
Top
 Abstract
 Introduction
Patients and methods
 Results
 Discussion
 Key points
 References
 
Stroke is a major cause of disability in the UK [1]. The clinical features and subsequent disability following stroke occur secondary to ischaemia-induced neuronal loss. Damage to the corticofugal fibres (pyramidal and para-pyramidal) leads to motor deficits, which are present in >80% of stroke patients [2, 3]. These deficits, which are collectively described as the upper motor neurone (UMN) syndrome, are characterised by a combination of negative phenomena (e.g. motor weakness) and positive phenomena (e.g. spasticity) [3, 4]. Spasticity is a common impairment, which is one component of the UMN syndrome that could be present in more than a third of all patients at a year following stroke [5].

Spasticity is described as a velocity-dependent increase of tonic stretch reflexes (muscle tone) with exaggerated tendon jerks, resulting from hyperexcitability of the stretch reflex, as one component of the UMN syndrome [6]. Spasticity has been reported to cause stiffness, a reduced range of movement, painful spasms and contractures [7]. These can lead to problems with posture, transfers, physical therapy, nursing care and hygiene [7].

Treating and minimising the effects of spasticity has remained one of the major aims for physicians and therapists as part of rehabilitation following stroke [3, 7–10]. Current research trends would suggest that substantial effort and resources are still being invested in developing and studying the effectiveness of novel therapeutic technologies and strategies aimed at treating spasticity [e.g. 11–16]. Given this research focus, it is, therefore, important to be able to measure spasticity accurately and objectively in order to be able to plan, deliver and monitor various treatment strategies [17]. It is now widely acknowledged that establishing clearly defined goals and outcome measures are important strategies in the management of spasticity [18, 19].

Although there are many techniques available to measure spasticity [20], clinical rating scales such as the Ashworth scale [21] and modified Ashworth scale (MAS) [22] are the most commonly used [23]. When using clinical measures to assess spasticity, one assesses the resistance to imposed passive movement (RPM) when the limb is briskly stretched through the full range of available movement about a joint. Although the MAS has been shown to have varying degrees of inter- and intra-rater reliability for measuring RPM [24, 25], the validity of these scales has only been studied cursorily [e.g. 26–31]. Further, existing clinical scales of spasticity have been shown to correlate poorly with each other, and the lack of consistency in their reliability makes it difficult for them to be seen as anything more than subjective measures, and this limits their clinical relevance [26, 32]. Therefore, there is a need for a valid quantitative measurement of spasticity, which is easy to use in a clinical setting.

Aim
The aim of the study was to investigate whether a previously developed biomechanical measure of joint stiffness could be used in routine clinical practice as a measure of RPM and whether this had more resolution in the measurement of RPM at the elbow in a post-stroke population than the MAS.


   Patients and methods
Top
 Abstract
 Introduction
 Patients and methods
Results
 Discussion
 Key points
 References
 
Study design and setting
This was a cross-sectional study with purposeful sampling to ensure an even representation of each level of spasticity. Stroke patients who had been admitted to the University Hospital with spasticity were recruited. An independent researcher selected the patients, and the clinical assessor took all study-related measurements. At the time of measurement, the clinical assessor was blinded to the instrumental (biomechanical) measures. The measurements were carried out at the bedside on the acute stroke ward, stroke rehabilitation unit, in the day hospital or at the patient’s place of residence.

Inclusion and exclusion criteria
Patients with a diagnosis of ischaemic or haemorrhagic stroke were included. Those who had traumatic brain injury or subarachnoid haemorrhage were excluded. Receptive and expressive dysphasia were not used as exclusion criteria; patients were included if they were able to co-operate with the measurement and had sufficient basic communication to establish the pain-free range of movement in the arm.

Ethical issues
The Local Research Ethics Committee approved the study and measurement protocol. Informed written consent was obtained from the patient whenever possible, or written assent was obtained from the relative or carer. Patients and relatives were informed of the option to withdraw from the study of their own accord at any point.

Outcome measures
Demographic details including age, gender, affected side, stroke subtype and the time elapsed from the stroke to measurement were taken at recruitment.

Simultaneous clinical grading of spasticity and RPM measurement was carried out on the affected limb about the elbow. The clinical grading was done using the MAS [22]. For the purpose of RPM measurement, a biomechanical device consisting of a force transducer (measured the force used to stretch the forearm manually) and a flexible electrogoniometer (measured the resulting displacement) was used [29, 30]. The time taken for each measurement was also measured.

The measurement protocol was as follows: the device was attached to the affected arm. An initial slow stretch was first done to establish the pain-free range of movement and this was followed by the clinical test (involving a brisk stretch) as per the measurement protocol described by Bohannon and Smith [22]. The arm was extended from full flexion at the elbow through the range of pain-free passive movement for both the slow and brisk stretch. The device was removed after the brisk stretch was completed.

RPM was measured as the slope of the force angle plot, with data collected from the brisk stretch, within the range of pain-free movement using a linear regression technique. Goodness of fit was tested using the coefficient of determination (r2)—a value of ‘1’ suggests perfect fit and a value of ‘0’ indicates no fit [33]. If the r2 was >0.60, the slope was considered to have an acceptable linear fit [34]. In addition to the above parameters, the average velocity of the fast movement was calculated as the ratio of passive range of movement (PROM) and time.

Data analysis
SPSS (Version 10.0) was used for statistical analysis.

In the primary analysis, validity and resolution was assessed between the MAS groups using analysis of variance (ANOVA). This was used to test for differences in force, PROM, time, velocity and RPM between the various MAS groups.

Previous studies have shown that the greatest problem with the MAS was to discriminate within the lower grades of stiffness (29). In view of this, for further analysis, we grouped the patients as normal (MAS 0), mild stiffness (MAS 1, 1+ and 2), moderate stiffness (MAS 3) and severe stiffness (MAS 4), and ANOVA was again used to compare the variation in mean RPM between these recoded groups.


   Results
Top
 Abstract
 Introduction
 Patients and methods
 Results
Discussion
 Key points
 References
 
A total of 111 patients who had a previous stroke were tested. The median age was 72 years [interquartile range (IQR) 64–78]. The sample comprised 45 female and 66 male patients. The left arm was affected in 59 and the right arm in 52 patients. The median time post-stroke was 11 months (IQR 3–36). The measurements were carried out at the bedside and took an average of 5 min. The maximum time taken for measurement was 10 min, and all measurements were carried out by a single rater with the patient in a chair or bed.

The frequency distribution of the MAS is described in Table 1. It was not possible to demonstrate any difference in RPM among ‘0’, ‘1’, ‘1+’ and ‘2’ (P>0.1). MAS grade‘4’ was significantly different from individual MAS values of 3 and below (P<0.05).


View this table:
[in this window]
[in a new window]
  		Table 1.. Biomechanically measured resistance to passive movement (RPM) for the clinically graded elbow stiffness according to the modified Ashworth scale (MAS)

 

The force required increased with the increasing MAS, and this was associated with a progressive decrease in velocity (P<0.01) (Table 2). The PROM decreased with increasing MAS (P<0.01). There were no significant differences in the time taken for passive movement of the arm across all grades of the MAS (P>0.1).


View this table:
[in this window]
[in a new window]
  		Table 2.. Biomechanically measured force required to achieve the maximum range of pain-free passive movement (PROM) and velocity of movement of the limb, for the clinically graded elbow stiffness according to the MAS

 

Further analysis based on the newly created groups shown in Table 3 showed no significant difference between ‘no stiffness’ and ‘mild stiffness’ (P>0.10). However, there were significant differences between ‘mild’ and moderate’ as well as between ‘moderate’ and ‘severe’ (P< 0.01).


View this table:
[in this window]
[in a new window]
  		Table 3.. A four-point grouping of patients based on biomechanically measured RPM

 


   Discussion
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
Key points
 References
 
In this study, RPM was objectively measured according to current protocols of clinical measurement, using a previously developed biomechanical device [30]. We were able to carry out bedside measurements using the device in a short period of time in various clinical settings on the acute stroke unit, stroke rehabilitation ward, stroke review clinic and patients’ place of residence (own home or institution). The measurement technique was quick, easy to administer and non-invasive. No adverse events were recorded throughout the study. The technique proved as easy to use in bed-bound patients, requiring high levels of nursing care, who had high grade stiffness of their arm, as in fully mobile patients with lower grades of stiffness. Because of this, we were able to include patients across the whole range of stiffness according to the MAS grading.

The protocol provided us with accurate measurements of the modalities of force, PROM, velocity and time using first principles. Subsequently, it was possible to quantify RPM objectively from the force angle plot using a linear regression technique. This provided us with a variety of biomechanically measurable components of a passive stretch at the elbow according to the definition of spasticity [6].

There was little difference in RPM at the lower grades of the MAS. This may have resulted from the inability of the MAS to discriminate among the lower grades of spasticity, and this observation is consistent with findings in other studies [29, 31, 32]. Although it was possible to identify accurately participants with higher grades of stiffness/RPM as per guidance in the MAS, it was not possible to confirm if the increase in stiffness exclusively represented changes in spasticity as defined by Lance [6]. Current evidence would suggest that the increase in RPM could result from the biomechanical changes in the soft tissue and joints [27–30] or ‘spastic dystonia’, a phenomenon described by Sheean [3] as a state of continuous muscle activity which is not movement related, both of which can occur in people who have had strokes. The above two phenomena, if present, could be the main reasons for the reduction in the passive range of movement and the velocity of movement seen in MAS grades of ‘3 (4)’ and ‘4 (5)’ even though the time taken to complete the movement remained constant.

The secondary analysis showed that it may be more appropriate to use a four-point scale to measure RPM and that this may provide an alternative to the current clinical measures. The decreased sensitivity (obtained by merging the lower grades of the MAS) in clinical grading of RPM may have led to improved validity and could contribute to increased reliability. However, even after reducing the sensitivity, it was extremely difficult to establish clinically the difference between a normal tone and mild degree of limb stiffness. This would suggest that, for routine clinical practice, even the suggested four-point scale may lack sensitivity at the lower end of the scale.

In clinical practice and research trials [e.g. 13, 15, 16], antispasticity treatment is normally aimed at people who have moderate to severe levels of RPM as graded by the MAS. Therefore, there may be some advantage to using a three-point clinical scale (none/mild, moderate and severe) to measure stiffness. However, even such a scale will be inferior to objective measures of RPM, such as those described in this study. For example, the increased sensitivity of the biomechanical measure demonstrated that in people with an MAS grade of ‘4’ described as having a ‘rigid and fixed limb’, angular displacement of ~20° was obtained.

It is clear from Lance’s definition [6] that if one were to measure spasticity one needs to measure RPM. The implicit assumption is that the changes in RPM reflect changes in reflex-mediated neuronal activity. However, in clinical practice, the changes in RPM are often confounded by changes in biomechanical properties and neuronal activity, which is not exclusive to reflex hyperexcitability. Using first principles, we were able to use two primary measures, namely force and angular displacement, to quantify RPM objectively and accurately. This provides a valid measurement of RPM, which is an indicator of the stiffness of the limb and could represent spasticity. However, as muscle electrical activity was not measured (using electromyography), it was not possible to confirm whether the stiffness was purely biomechanical, purely neural or a combination of both.

MAS lacks the ability to discriminate small changes in RPM. This could be due to the fact that when using the MAS to quantify spasticity, one may be quantifying, in addition to RPM, other parameters (such as force applied, range of movement, time taken to move, momentum and catch), which then have the potential to confound the clinical grading [30].

It would be tempting to suggest the use of a three-point scale for the grading of arm stiffness in a clinical setting. However, the evidence from this study and others [e.g. 26–30] would suggest that any such scale would provide limited diagnostic information, i.e. the clinical scale would not be able to identify whether the stiffness is ‘purely biomechanical’, ‘purely neural’ or a combination of both. It is possible to measure stiffness objectively at the bedside, and this may provide valuable information in identifying patients for intervention and in measuring the effects of treatment. However, if one is interested in neural components of stiffness/RPM, then there is a need additionally to measure levels of muscle activity. Further work will be required to explore the feasibility of such a measurement system.


   Key points
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Key points
References
 

  • The six-point clinical scale (MAS) is not a valid ordinal level measure of RPM or spasticity.
  • Objective measurement of RPM is possible at the bedside.
  • RPM is influenced by biomechanical factors, neural factors or a combination of both. Additional measurements of muscle activity will be required to obtain meaningful diagnostic information.


   References
Top
 Abstract
 Introduction
 Patients and methods
 Results
 Discussion
 Key points
 References
 

  1. Royal College of Physicians of London. National Sentinel Stroke Audit. 2001/2002.
  2. Peltonen M, Stegmayr B, Asplund K. Time trends in long term survival after stroke. Stroke 1998; 29: 1358–65.[Abstract/Free Full Text]
  3. Sheean G. Neurophysiology of spasticity. In: Barnes MP, Johnson GR, eds. Upper Motor Neuron Syndrome and Spasticity. Cambridge University Press, 2001: 12–78.
  4. Burke D. Spasticity as an adaptation to pyramidal tract injury. Adv Neurol 1988; 47: 401–3.[Medline]
  5. Watkins CL, Leathley MJ, Gregson JM, Moore AP, Smith TL, Sharma AK. Prevalence of spasticity post stroke. Clin Rehabil 2002; 16: 515–22.[Abstract/Free Full Text]
  6. Lance JW. Symposium synopsis. In: Feldman RG, Young RR, Koella WP, eds. Spasticity: Disorder of Motor Control. Chicago: Year Book Medical Publishers, 1980: 485–94.
  7. Barnes MP. Medical management of spasticity in stroke. Age and Ageing 2001; 30: 13–6.[Free Full Text]
  8. Ada L, Dean CM, Hall JM, Bampton J, Crompton S. A treadmill and overground walking programme improves walking in persons residing in community after stroke: a placebo controlled randomized trial. Arch Phys Med Rehabil 2003; 84: 1486–91.[CrossRef][ISI][Medline]
  9. Dean CM, Shepherd RB. Task-related training improves performance of seated reaching tasks after stroke—a RCT. Stroke 1997; 28: 722–8.[Abstract/Free Full Text]
  10. Bobath B. Adult Hemiplegia: Evaluation and Treatment, 3rd edn. London: Butterworth Heinemann, 1990.
  11. Pittock SJ, Moore AP, Hardiman O et al. A double-blind randomised placebo-controlled evaluation of three doses of botulinum toxin type A (Dysport) in the treatment of spastic equinovarus deformity after stroke. Cerebrovasc Dis 2003; 15.
  12. Remy-Neris O, Tiffreau V, Bouilland S, Bussel B. Intrathecal baclofen in subjects with spastic hemiplegia: assessment of the antispastic effect during gait. Arch Phys Med Rehabil 2003; 84: 643–50.[ISI][Medline]
  13. Brashear A, Gordon MF, Elovic E et al. Intramuscular injection of botulinum toxin for the treatment of wrist and finger spasticity after a stroke. N Engl J Med 2002; 347: 395–400.[Abstract/Free Full Text]
  14. Shakespeare DT, Boggild M, Young C. Anti-spasticity agents for multiple sclerosis. Cochrane Database Syst Rev 2003, Issue 4. Art. No.: CD001332. DOI: 10.1002/14651858.CD001332.
  15. Bhakhta BB, Cozens J.A., Chamberlain MA, Bamford JM. Impact of botulinum toxin type A on disability and carer burden due to arm spasticity after stroke: a randomised double blind placebo controlled trial. J Neurol Neurosurg Psychiatry 2000; 69: 217–21.[Abstract/Free Full Text]
  16. Bakheit AM, Thilmann AF, Ward AB et al. A randomized, double-blind, placebo-controlled, dose-ranging study to compare the efficacy and safety of three doses of botulinum toxin type A (Dysport) with placebo in upper limb spasticity after stroke. Stroke 2000; 31: 2402–6.[Abstract/Free Full Text]
  17. Haas BM, Crow JL. Towards a clinical measurement of spasticity? Physiotherapy 1995; 81: 474–9.
  18. Moore AP. Spasticity after stroke. Prescriber’s Jl 1998; 38: 40–6.
  19. Barnes MP. Management of spasticity (review). Age and Ageing 1998; 27: 239–45.[Free Full Text]
  20. Johnson GR. Measurement of Spasticity. In: Barnes MP, Johnson GR, eds. Upper Motor Neurone Syndrome and Spasticity. Cambridge: Cambridge University Press, 2001: 79–96.
  21. Ashworth B. Preliminary trial of carisoprodol in multiple sclerosis. Practitioner 1964; 192: 540–2.[ISI][Medline]
  22. Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther 1987; 67: 206–7.[ISI][Medline]
  23. Van Wijck FM, Pandyan AD, Johnson GR, Barnes MP. Assessing motor deficits in neurological rehabilitation: patterns of instrument usage. Neurorehabil Neural Repair 2001: 15: 22–30.
  24. Gregson JM, Leathley MJ, Moore AP, Smith TL, Sharma AK, Watkins CL. Reliability of measurements of muscle tone and muscle power in stroke patients. Age and Ageing 2000; 29: 223–8.[Abstract/Free Full Text]
  25. Leslie GC, Muir C, Part NJ, Roberts RC. A comparison of the assessment of spasticity by the Wartenburg pendulum test and the Ashworth grading scale in patients with multiple sclerosis. Clin Rehabil 1992; 6: 41–8.
  26. Priebe MM, Sherwood AM, Thornby JI, Kharas NF, Markowski J. Clinical assessment of spasticity in spinal cord injury: a multidimensional problem. Arch Phys Med Rehabil 1996; 77: 713–6.[CrossRef][ISI][Medline]
  27. O’Dwyer NJ, Ada L, Neilson PD. Spasticity and muscle contracture following stroke. Brain 1996; 119: 1737–49.[Abstract/Free Full Text]
  28. Vattanasilp W, Ada L. The relatioship between clinical and laboratory measures of spasticity. Aust J Physiother 1999; 45: 135–9.[ISI][Medline]
  29. Pandyan AD, Price CI. Barnes MP, Johnson GR. A biomechanical investigation into the validity of the modified Ashworth scale as a measure of elbow spasticity. Clin Rehabil 2003; 17: 290–3.[Abstract/Free Full Text]
  30. Pandyan AD, Price CI, Barnes MP, Johnson GR. Biomechanical examination of a commonly used measure of spasticity. Clin Biomech 2001; 16: 859–65.[CrossRef][Medline]
  31. Pomeroy VM, Dean D, Sykes L et al. The unreliability of clinical measures of muscle tone: implications for stroke therapy. Age and Ageing 2000; 29: 229–33.[Abstract/Free Full Text]
  32. Blackburn M, van Vliet P, Mockett SP. Reliability of measurements obtained with the modified Ashworth scale in the lower extremities of people with stroke. Phys Ther 2002; 82: 25–34.[Abstract/Free Full Text]
  33. Harnett DL. Statistical Methods, 3rd edn. Addison Wesley, 1982.
  34. Neter J, Kutner M, Nachtsheim CJ, Wasserman W. Applied Linear Statistical Models, 4th edn. Time Mirror Higher Education Group, 1996.

Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?



This Article
Right arrow Abstract Freely available
Right arrow FREE Full Text (PDF) Freely available
Right arrow All Versions of this Article:
35/4/371    most recent
afj084v1
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in ISI Web of Science
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Search for citing articles in:
ISI Web of Science (2)
Right arrowRequest Permissions
Right arrow Disclaimer
Google Scholar
Right arrow Articles by Kumar, R. T. S.
Right arrow Articles by Sharma, A. K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kumar, R. T. S.
Right arrow Articles by Sharma, A. K.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?