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Quantitative gait analysis in patients with dementia with Lewy bodies and Alzheimer's disease
Gait & Posture 26 (2007) 414–419 www.elsevier.com/locate/gaitpost
Quantitative gait analysis in patients with dementia with Lewy bodies and Alzheimer’s disease John R. Merory a, Joanne E. Wittwer b, Christopher C. Rowe c, Kate E. Webster b,* a
Medical and Cognitive Research Unit, Neurology Department, Austin Health, Melbourne, Australia b Musculoskeletal Research Centre, La Trobe University, Melbourne, Victoria 3086, Australia c Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia Received 4 July 2006; received in revised form 16 October 2006; accepted 25 October 2006
Abstract Gait disorders in people with dementia have been documented in a number of studies. There is some preliminary evidence suggesting there may be a relationship between dementia type and gait abnormality. Quantitative gait analysis has not previously been reported for people diagnosed with dementia with Lewy bodies (DLB). Therefore, this study aimed to quantify gait patterns of people with DLB and compare them with those of people with Alzheimer’s disease (AD) and control subjects. Two groups of 10 subjects divided according to a diagnosis of DLB and AD, and 10 control subjects underwent gait analysis using an electronic walkway. Participants were required to walk at self-selected slow, preferred and fast speeds. There were no differences between the DLB and AD patient groups for any of the measured gait variables. Velocity and stride length values were significantly reduced in both patient groups compared to the control group at all speeds and percentage of time spent in double limb support was significantly increased in both patient groups compared to the control group at all walking speeds. Significant correlations were found between gait speeds and gait outcome variables. Spatiotemporal gait characteristics of people with AD and DLB are similar, but significantly different from the normal population. # 2006 Elsevier B.V. All rights reserved. Keywords: Gait disorder; Walking; Lewy body disease; Alzheimer disease
1. Introduction Gait disorders are common in people with dementia and a number of studies have documented various changes in the walking patterns of people with dementia compared with controls [1–4]. These changes include decreased velocity and stride length and increased variability. This is of interest for a number of reasons. Falls in people with dementia, which occur at a higher frequency than in cognitively normal older people and with increased risk of serious injury [5–9], have been associated with changes in walking patterns [8,10–13]. Gait disorders have also been identified as predictors of dementia [14]. van Iersel et al. [15] recently reviewed the literature on quantitative gait analysis in dementia. They concluded that * Corresponding author. Tel.: +61 3 9479 5796; fax: +61 3 9479 5768. E-mail address: [email protected] (K.E. Webster). 0966-6362/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.gaitpost.2006.10.006
there is evidence of consistent differences between the walking patterns of older people with and without dementia. All studies cited in their review were of people with Alzheimer’s disease (AD) and one study also included a group with vascular dementia. These two disorders together were thought to account for most cases of dementia [16]. However, dementia with Lewy bodies (DLB) is now thought to be the second most common form of dementia making up 15–25% of cases [16]. There is some preliminary evidence that people with DLB walk with reduced velocity and step length compared to people with AD [17,18] suggesting there may be a relationship between dementia type and gait abnormality. Allan et al. [19] found that patients with AD scored better using a scale measure of gait and balance activities than those with non-Alzheimer’s dementias such as DLB and suggested that such assessments can augment the diagnostic process. Changes in gait characteristics of people with
J.R. Merory et al. / Gait & Posture 26 (2007) 414–419
dementia may also have the potential to be used to monitor disease progression and measure outcomes both in research and clinical practice [15]. However in order to achieve this, methods of measuring gait must provide reliable, detailed and sensitive data such as is available with quantitative methods of gait analysis. To our knowledge there have been no studies using quantitative gait analysis of people with a specific diagnosis of DLB. We hypothesized that people with DLB would have greater gait abnormalities than those with AD. Therefore, this study aimed to quantify gait patterns of people with probable DLB, compare them with those of people with AD and control subjects, and try to distinguish between DLB and AD patients on the basis of gait characteristics.
2. Methods
415
use of a gait aid and also to follow instructions for the testing procedure. Subjects were excluded if they reported any other neurological, orthopedic, respiratory, circulatory or visual condition, which affected their gait. Control subjects were recruited from a database of research volunteers for gait studies. They were included if they had no symptoms of musculoskeletal, neurological or other problems, which would affect their gait. Age and height measures were similar between the three groups and these characteristics are summarized in Table 1. Mini-Mental State Examination (MMSE) scores [22] are also listed along with medications and scores from the motor examination section (items 18–31) of the Unified Parkinson’s Disease Rating Scale (UPDRS) [23], which were used to document the presence of extrapyramidal motor signs in subjects with dementia. Gait aid usage over rough ground and long distances provides further information about functional mobility.
2.1. Subjects 2.2. Apparatus A total of 30 subjects, comprising three groups of 10 (8 males, 2 females) divided according to a diagnosis of DLB, AD and healthy controls, participated in this study. The University Human Ethics Committee approved the aims and procedure. Thirteen subjects with DLB and AD consecutively referred to Neurology and Geriatric Departments at a local public hospital were invited to participate in the study by one neurologist (JM). In each of the DLB and AD groups, two people declined to participate and one person initially agreed but was unable to participate due to ill health at the time of testing, leaving 10 subjects in each group. The diagnosis of probable DLB was made using a careful and conservative application of the McKeith criteria [16] including neuropsychological tests. The diagnosis of AD used the National Institute of Neurological and Communicative Disorders and the Alzheimer’s Disease and Related Disorders Association (NINCDS–ADRDA) classification [20]. Further confirmation of the diagnosis of DLB was available for 6 of the 10 subjects in the DLB group using the results of dopamine transporter imaging with a Beta-CIT ligand, one of the new items included in the most recent clinical diagnostic criteria for DLB [21]. The inclusion criteria were the ability to walk 100 m without assistance or
The spatial and temporal parameters of subjects’ gait were measured using a GAITRite1 system (CIR Systems Inc., 60 Garlor Drive Havertown, PA 19083), comprising an electronic walkway connected to a Windows based personal computer (PC) via an interface cable, and GAITRite1 GOLD, Version 3.3hb software. The GAITRite1 walkway is a carpet, 8.3 m long and 0.89 m wide, in which sensor pads are embedded, giving an active area of 7.32 m long and 0.61 m wide. Individual sensors in the pads are arranged 12.7 mm apart in a (48 576) grid pattern and allow detection of footstep pressure as a subject walks on the carpet. Data are sampled at a rate of 80 Hz. Gait spatial and temporal characteristics are processed and stored using the application software. The GAITRite1 system has been shown to be a valid and reliable measure of gait [24,25]. 2.3. Procedure After subjects gave written consent, measurements of their height and weight were taken along with a brief medical history. Cognition and motor tests were then administered by
Table 1 Subject characteristics Age, years, mean S.D. Height, m, mean S.D. Levodopa medication, n Cholinesterase inhibitors, n Psychotropic medication, n MMSE score, mean S.D.a UPDRS motor examination score, mean S.D.b Use of gait aid over uneven surfaces/long distances, n a b
Maximum = 30. Maximum = 108.
Lewy body dementia
Alzheimer’s disease
Control
73 5 1.68 0.10 4 8 4 23.5 4.0 27.1 9.4 3
76 6 1.73 0.09 0 8 2 20.0 5.8 2.7 4.2 3
72 7 1.73 0.08 0 0 1 28.7 1.2 Not tested 0
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the neurologist investigator. For the gait assessment each subject was instructed to walk along the GAITRite1 carpet at their self-selected comfortable speed two times to permit them to become familiar with the procedure. They were then asked to complete four walks at selfselected slow speed, four at comfortable speed and four at fast speed. The order of speed conditions was selected randomly and was repeated across the three groups. So that there was no initial change in floor surface subjects commenced each walk with feet level on the carpet at the edge of the active area. They were instructed to begin walking on the command ‘‘Ready, go’’ and to continue walking until they reached a floor mark positioned 2 m beyond the end of the carpet. To minimize the risk of falls, a researcher accompanied each subject during all walks. The researcher remained out of the subject’s field of vision so as to reduce any cues for movement, which their presence may have provided. Subjects were permitted rests as often as required. The investigators were not blind to subject group allocation. 2.4. Data analysis In order to remove the initial acceleration phase of each walk, data from the first 2 m of the mat were removed.
This was done by deleting the required length of mat in the footfall editor menu of the software prior to running the footfall identification algorithm. The spatiotemporal variables analyzed included velocity, cadence, stride length, step width and the percentage of the gait cycle in double limb support. For each subject, data from the four walk trials were averaged to give an individual mean and standard deviation for each variable. This was performed separately for the slow, preferred and fast speed conditions. One-way ANOVAs were used to assess for differences between the three groups (control, DLB, AD). Post hoc testing between the groups was conducted using the Bonferroni correction. Correlations between gait variables and the walking speed conditions were also performed.
3. Results MMSE scores were significantly lower in both patient groups compared to the control group ( p < 0.01). Scores from the motor examination section of the UPDRS were significantly higher (indicating greater motor impairment) in the DLB group than in the AD group ( p < 0.001, Table 1).
Fig. 1. Mean values for walking velocity (A), stride length (B), double support (C), cadence (D) and step width (E) in subjects with AD, DLB and controls at self-selected slow, preferred and fast speeds.
J.R. Merory et al. / Gait & Posture 26 (2007) 414–419 Table 2 Spearman rank order correlations between condition (slow, preferred, fast) and gait variables Condition DLB Velocity Cadence Stride length Step width Double support *
AD *
0.82 0.81* 0.74* 0.08 0.59*
Control *
0.81 0.85* 0.59* 0.22 0.66*
0.82* 0.85* 0.62* 0.11 0.60*
p < 0.01.
Duration of illness was reported to be less than 4 years for all subjects with dementia. Fig. 1 shows the spatiotemporal gait characteristics of velocity, cadence, stride length, step width and doublesupport percentage for each of the three groups of subjects at slow, preferred and fast walking speeds. There were no differences between the DLB and AD patient groups for any of the measured gait variables. Velocity and stride length values were significantly reduced in both patient groups compared to the control group at all speeds ( p < 0.01 slow and preferred speed; p < 0.05 fast speed; Fig. 1A and B). Percentage of time spent in double limb support was significantly increased in both patient groups compared to the control group at all walking speeds ( p < 0.01; Fig. 1C). There was no difference in cadence between the three groups at preferred and fast speeds. However, at slow speed, the AD group walked with a slower cadence than the control group ( p < 0.05). There were no differences in step width between the three groups at any speed. Correlations between conditions (slow, preferred, fast) and gait outcome variables are displayed in Table 2. Significant correlations were found for all three groups for velocity, cadence, stride length and percentage of gait cycle in double limb support.
4. Discussion This study is the first to report quantitative analysis of the walking patterns of people with a specific diagnosis of probable DLB and compare this to people with AD and control subjects. The study has provided further evidence that people with dementia walk with decreased velocity and stride length and increased double support percentage compared with healthy older people and that these differences persist at different walking speeds. Notwithstanding the differences between control subjects and patients with dementia, all three groups had very similar rates of changes between the three different walking conditions, as evidenced by the significant correlations. Therefore, even though the DLB and AD subjects walked more slowly overall, the magnitude of the gait changes they made between the slow, preferred and fast walking conditions was consistent with that of the control subjects.
417
That we did not find differences between the spatiotemporal gait characteristics of subjects with DLB and AD was not predicted and is at odds with previous studies making similar comparisons [17,18]. This may be due to the interaction of the type of walking test used and the effect of parkinsonism, which is more common and often severe in patients with DLB than those with AD [26], and is accentuated when movement sequences are longer or more complex [27]. Our study used measures of the simple gait task of walking in a straight line and acceleration and deceleration phases were not included in the analysis. Waite et al. [18] used a walking test, which involved timing a 5 m returned walk. Gnanalingham et al. [17] used a similar walking procedure with the addition of rising from an armless chair prior to walking and returning to the seated position. The inclusion of turns, standing up and sitting down, increased the complexity and sequence length of the walking task in these studies. The constant velocity straight line walking task measured in our study is less likely to have produced this differential effect between subjects with the two dementia types. The similarity in the measured gait variables of the DLB and AD subjects also appears to conflict with the differences in scores on the motor section of the UPDRS between the two groups. A possible explanation may be that the UPDRS includes scores for a number of motor characteristics other than gait. No subject with either form of dementia scored more than one for the gait item of the UPDRS (indicating all walked with normal or slowed gait but with no other difficulties), despite the DLB subjects’ higher scores for other motor items. There is also some redundancy of items in the motor section, which may lead to inflation of these scores relative to other items [28]. Related to this is the concern that the scoring of some aspects of the motor section of the UPDRS may not necessarily reflect their impact on a functional activity such as walking [28]. The findings of this pilot study are limited by the small number of mostly male subjects in each group. However the study is well controlled, using a validated method [25] to quantify gait at three self-selected constant speeds. Participants from the two dementia groups also demonstrated only mild cognitive impairment. Increased severity of dementia may produce changes in gait characteristics that are different for different dementia types. Mean MMSE scores for subjects with dementia in one of the previous DLB gait studies were much lower than in this study [17], however Waite et al. [18] found severity of dementia had little or no effect on gait measures in their study. The relationship between measures of gait and brain pathophysiology was not explored as this was beyond the scope of the study. Preliminary evidence suggests that the gait disorders of AD and DLB may occur via different pathophysiological mechanisms. It has been argued that midbrain abnormalities in AD may produce some gait features similar to DLB [29]. However, dopamine transporter ligands such as Beta-CIT demonstrate no diminution
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in AD, in contrast to DLB [30]. Pittsburgh Compound-B (PIB) scans display copious frontal amyloid in AD patients [31], and this frontal amyloid deposition in AD may be associated with the observed gait defects. Future investigations correlating the degree of frontal amyloid involvement with gait abnormalities in AD may shed light on the mechanism of gait changes in AD. In conclusion, this preliminary investigation demonstrates that a group of subjects with probable DLB had very similar spatiotemporal gait parameters when walking in a straight line at self-selected speeds to a group with AD, and that both were significantly different from healthy controls. This illustrates the value of quantitative gait analysis in revealing gait characteristics that may not be obvious using qualitative methods. In order to further examine similarities and differences in gait patterns of people with DLB and related disorders, subsequent studies should evaluate changes in gait characteristics using systematic alteration of the walking task in larger subject groups over time and relate these findings to pathophysiological data. Conflict of interest statement No commercial entity paid or directed, or agreed to pay or direct, any benefits to any research fund, foundation, educational institution, or other charitable or non-profit organization with which the authors of the paper ‘‘Quantitative Gait Analysis In Patients With Dementia With Lewy Bodies And Alzheimer’s Disease’’ are affiliated or associated.
Acknowledgement This project was funded by a La Trobe University Faculty of Health Sciences Research Grant.
References [1] Visser H. Gait and balance in senile dementia of Alzheimer’s type. Age Ageing 1983;12(4):296–301. [2] Tanaka A, Okuzumi H, Kobayashi I, Murai N, Meguro K, Nakamura T. Gait disturbance of patients with vascular and Alzheimer-type dementias. Percept Mot Skills 1995;80(3 Pt 1):735–8. [3] O’Keeffe ST, Kazeem H, Philpott RM, Playfer JR, Gosney M, Lye M. Gait disturbance in Alzheimer’s disease: a clinical study. Age Ageing 1996;25(4):313–6. [4] Sheridan PL, Solomont J, Kowall N, Hausdorff JM. Influence of executive function on locomotor function: divided attention increases gait variability in Alzheimer’s disease. J Am Geriatr Soc 2003;51(11): 1633–7. [5] Buchner D, Larson E. Falls and fractures in patients with Alzheimertype dementia. JAMA 1987;257(11):1492–5. [6] Morris J, Rubin E, Morris E, Mandel S. Senile dementia of the Alzheimer’s type: an important risk factor for serious falls. J Gerontol 1987;42(4):412–7.
[7] Tinetti ME, Speechley M, Ginter SF. Risk factors for falls among elderly persons living in the community. N Engl J Med 1988;319(26):1701–7. [8] van Dijk PT, Meulenberg OG, van de Sande HJ, Habbema JD. Falls in dementia patients. Gerontologist 1993;33(2):200–4. [9] Kenny RA, Richardson DA, Steen IN, McKeith IG, Bond J, Shaw FE. Predictors of further falls in patients with cognitive impairment and dementia attending the casualty department. Age Ageing 2000;29(Suppl 1):A23. [10] Nakamura T, Meguro K, Sasaki H. Relationship between falls and stride length variability in senile dementia of the Alzheimer type. Gerontology 1996;42(2):108–13. [11] Camicioli R, Licis L. Motor impairment predicts falls in specialized Alzheimer care units. Alzheimer Dis Assoc Disord 2004;18(4):214–8. [12] Franssen EH, Souren LE, Torossian CL, Reisberg B. Equilibrium and limb coordination in mild cognitive impairment and mild Alzheimer’s disease. J Am Geriatr Soc 1999;47(4):463–9. [13] Alexander NB, Mollo JM, Giordani B, et al. Maintenance of balance, gait patterns, and obstacle clearance in Alzheimer’s disease. Neurology 1995;45(5):908–14. [14] Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H. Abnormality of gait as a predictor of non-Alzheimer’s dementia. N Engl J Med 2002;347(22):1761–8. [15] van Iersel MB, Hoefsloot W, Munneke M, Bloem BR, Olde Rikkert MG. Systematic review of quantitative clinical gait analysis in patients with dementia. Z Gerontol Geriatr 2004;37(1):27–32. [16] McKeith IG, Galasko D, Kosaka K, et al. Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 1996;47(5):1113–24. [17] Gnanalingham K, Byrne E, Thornton A, Sambrook M, Bannister P. Motor and cognitive function in Lewy body dementia: comparison with Alzheimer’s and Parkinson’s diseases. J Neurol Neurosurg Psychiatry 1997;62:243–52. [18] Waite LM, Broe GA, Grayson DA, Creasey H. Motor function and disability in the dementias. Int J Geriatr Psychiatry 2000;15:897–903. [19] Allan LM, Ballard CG, Burn DJ, Kenny RA. Prevalence and severity of gait disorders in Alzheimer’s and non-Alzheimer’s dementias. J Am Geriatr Soc 2005;53(10):1681–7. [20] McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDSADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34(7):939–44. [21] McKeith IG, Dickson DW, Lowe J, et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 2005;65(12):1863–72. [22] Folstein MF, Folstein SE, McHugh PR. Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–98. [23] Fahn S, Elton RL. Unified Parkinson’s disease rating scale. In: Fahn S, editor. Recent developments in Parkinson’s disease. New York: MacMillan; 1987. p. 153–63. [24] Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait Posture 2003;17(1):68–74. [25] Webster KE, Wittwer JE, Feller JA. Validity of the GAITRite((R)) walkway system for the measurement of averaged and individual step parameters of gait. Gait Posture 2005;22(4):317–21. [26] Ballard C, O’Brien J, Swann A, et al. One year follow-up of parkinsonism in dementia with Lewy bodies. Dement Geriatr Cogn Disord 2000;11:219–22. [27] Morris ME, Iansek R, Summers JJ, Matyas TA. Motor control considerations for the rehabilitation of gait in Parkinson’s disease. In: Glencross DJ, Piek JP, editors. Motor control and sensory motor integration: issues and directions. Elsevier Science B. V; 1995 . p. 61–93.
J.R. Merory et al. / Gait & Posture 26 (2007) 414–419 [28] Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease. The Unified Parkinson’s Disease Rating Scale (UPDRS): status and recommendations. Move Dis 2003;18(7):738– 50. [29] Burns JM, Galvin JE, Roe CM, Morris JC, McKeel DW. The pathology of the substantia nigra in Alzheimer disease with extrapyramidal signs. Neurology 2005;64(8):1397–403.
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[30] Rowe CC, Villemagne VL, Ellis JR, et al. I-123 Beta-CIT SPECT and FDG-PET in dementia with Lewy bodies and Alzheimer’s disease. In: Proceedings of the program and abstracts of the 7th international conference AD/PD; 2005. p. 79. [31] Rowe CC, Ackermann U, Gong S, et al. Amyloid imaging in Lewy body dementia with 11C-PIB-PET. J Neurol Sci 2005;238(Suppl 1):S98–9.
Quantitative gait analysis in patients with dementia with Lewy bodies and Alzheimer’s disease John R. Merory a, Joanne E. Wittwer b, Christopher C. Rowe c, Kate E. Webster b,* a
Medical and Cognitive Research Unit, Neurology Department, Austin Health, Melbourne, Australia b Musculoskeletal Research Centre, La Trobe University, Melbourne, Victoria 3086, Australia c Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia Received 4 July 2006; received in revised form 16 October 2006; accepted 25 October 2006
Abstract Gait disorders in people with dementia have been documented in a number of studies. There is some preliminary evidence suggesting there may be a relationship between dementia type and gait abnormality. Quantitative gait analysis has not previously been reported for people diagnosed with dementia with Lewy bodies (DLB). Therefore, this study aimed to quantify gait patterns of people with DLB and compare them with those of people with Alzheimer’s disease (AD) and control subjects. Two groups of 10 subjects divided according to a diagnosis of DLB and AD, and 10 control subjects underwent gait analysis using an electronic walkway. Participants were required to walk at self-selected slow, preferred and fast speeds. There were no differences between the DLB and AD patient groups for any of the measured gait variables. Velocity and stride length values were significantly reduced in both patient groups compared to the control group at all speeds and percentage of time spent in double limb support was significantly increased in both patient groups compared to the control group at all walking speeds. Significant correlations were found between gait speeds and gait outcome variables. Spatiotemporal gait characteristics of people with AD and DLB are similar, but significantly different from the normal population. # 2006 Elsevier B.V. All rights reserved. Keywords: Gait disorder; Walking; Lewy body disease; Alzheimer disease
1. Introduction Gait disorders are common in people with dementia and a number of studies have documented various changes in the walking patterns of people with dementia compared with controls [1–4]. These changes include decreased velocity and stride length and increased variability. This is of interest for a number of reasons. Falls in people with dementia, which occur at a higher frequency than in cognitively normal older people and with increased risk of serious injury [5–9], have been associated with changes in walking patterns [8,10–13]. Gait disorders have also been identified as predictors of dementia [14]. van Iersel et al. [15] recently reviewed the literature on quantitative gait analysis in dementia. They concluded that * Corresponding author. Tel.: +61 3 9479 5796; fax: +61 3 9479 5768. E-mail address: [email protected] (K.E. Webster). 0966-6362/$ – see front matter # 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.gaitpost.2006.10.006
there is evidence of consistent differences between the walking patterns of older people with and without dementia. All studies cited in their review were of people with Alzheimer’s disease (AD) and one study also included a group with vascular dementia. These two disorders together were thought to account for most cases of dementia [16]. However, dementia with Lewy bodies (DLB) is now thought to be the second most common form of dementia making up 15–25% of cases [16]. There is some preliminary evidence that people with DLB walk with reduced velocity and step length compared to people with AD [17,18] suggesting there may be a relationship between dementia type and gait abnormality. Allan et al. [19] found that patients with AD scored better using a scale measure of gait and balance activities than those with non-Alzheimer’s dementias such as DLB and suggested that such assessments can augment the diagnostic process. Changes in gait characteristics of people with
J.R. Merory et al. / Gait & Posture 26 (2007) 414–419
dementia may also have the potential to be used to monitor disease progression and measure outcomes both in research and clinical practice [15]. However in order to achieve this, methods of measuring gait must provide reliable, detailed and sensitive data such as is available with quantitative methods of gait analysis. To our knowledge there have been no studies using quantitative gait analysis of people with a specific diagnosis of DLB. We hypothesized that people with DLB would have greater gait abnormalities than those with AD. Therefore, this study aimed to quantify gait patterns of people with probable DLB, compare them with those of people with AD and control subjects, and try to distinguish between DLB and AD patients on the basis of gait characteristics.
2. Methods
415
use of a gait aid and also to follow instructions for the testing procedure. Subjects were excluded if they reported any other neurological, orthopedic, respiratory, circulatory or visual condition, which affected their gait. Control subjects were recruited from a database of research volunteers for gait studies. They were included if they had no symptoms of musculoskeletal, neurological or other problems, which would affect their gait. Age and height measures were similar between the three groups and these characteristics are summarized in Table 1. Mini-Mental State Examination (MMSE) scores [22] are also listed along with medications and scores from the motor examination section (items 18–31) of the Unified Parkinson’s Disease Rating Scale (UPDRS) [23], which were used to document the presence of extrapyramidal motor signs in subjects with dementia. Gait aid usage over rough ground and long distances provides further information about functional mobility.
2.1. Subjects 2.2. Apparatus A total of 30 subjects, comprising three groups of 10 (8 males, 2 females) divided according to a diagnosis of DLB, AD and healthy controls, participated in this study. The University Human Ethics Committee approved the aims and procedure. Thirteen subjects with DLB and AD consecutively referred to Neurology and Geriatric Departments at a local public hospital were invited to participate in the study by one neurologist (JM). In each of the DLB and AD groups, two people declined to participate and one person initially agreed but was unable to participate due to ill health at the time of testing, leaving 10 subjects in each group. The diagnosis of probable DLB was made using a careful and conservative application of the McKeith criteria [16] including neuropsychological tests. The diagnosis of AD used the National Institute of Neurological and Communicative Disorders and the Alzheimer’s Disease and Related Disorders Association (NINCDS–ADRDA) classification [20]. Further confirmation of the diagnosis of DLB was available for 6 of the 10 subjects in the DLB group using the results of dopamine transporter imaging with a Beta-CIT ligand, one of the new items included in the most recent clinical diagnostic criteria for DLB [21]. The inclusion criteria were the ability to walk 100 m without assistance or
The spatial and temporal parameters of subjects’ gait were measured using a GAITRite1 system (CIR Systems Inc., 60 Garlor Drive Havertown, PA 19083), comprising an electronic walkway connected to a Windows based personal computer (PC) via an interface cable, and GAITRite1 GOLD, Version 3.3hb software. The GAITRite1 walkway is a carpet, 8.3 m long and 0.89 m wide, in which sensor pads are embedded, giving an active area of 7.32 m long and 0.61 m wide. Individual sensors in the pads are arranged 12.7 mm apart in a (48 576) grid pattern and allow detection of footstep pressure as a subject walks on the carpet. Data are sampled at a rate of 80 Hz. Gait spatial and temporal characteristics are processed and stored using the application software. The GAITRite1 system has been shown to be a valid and reliable measure of gait [24,25]. 2.3. Procedure After subjects gave written consent, measurements of their height and weight were taken along with a brief medical history. Cognition and motor tests were then administered by
Table 1 Subject characteristics Age, years, mean S.D. Height, m, mean S.D. Levodopa medication, n Cholinesterase inhibitors, n Psychotropic medication, n MMSE score, mean S.D.a UPDRS motor examination score, mean S.D.b Use of gait aid over uneven surfaces/long distances, n a b
Maximum = 30. Maximum = 108.
Lewy body dementia
Alzheimer’s disease
Control
73 5 1.68 0.10 4 8 4 23.5 4.0 27.1 9.4 3
76 6 1.73 0.09 0 8 2 20.0 5.8 2.7 4.2 3
72 7 1.73 0.08 0 0 1 28.7 1.2 Not tested 0
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J.R. Merory et al. / Gait & Posture 26 (2007) 414–419
the neurologist investigator. For the gait assessment each subject was instructed to walk along the GAITRite1 carpet at their self-selected comfortable speed two times to permit them to become familiar with the procedure. They were then asked to complete four walks at selfselected slow speed, four at comfortable speed and four at fast speed. The order of speed conditions was selected randomly and was repeated across the three groups. So that there was no initial change in floor surface subjects commenced each walk with feet level on the carpet at the edge of the active area. They were instructed to begin walking on the command ‘‘Ready, go’’ and to continue walking until they reached a floor mark positioned 2 m beyond the end of the carpet. To minimize the risk of falls, a researcher accompanied each subject during all walks. The researcher remained out of the subject’s field of vision so as to reduce any cues for movement, which their presence may have provided. Subjects were permitted rests as often as required. The investigators were not blind to subject group allocation. 2.4. Data analysis In order to remove the initial acceleration phase of each walk, data from the first 2 m of the mat were removed.
This was done by deleting the required length of mat in the footfall editor menu of the software prior to running the footfall identification algorithm. The spatiotemporal variables analyzed included velocity, cadence, stride length, step width and the percentage of the gait cycle in double limb support. For each subject, data from the four walk trials were averaged to give an individual mean and standard deviation for each variable. This was performed separately for the slow, preferred and fast speed conditions. One-way ANOVAs were used to assess for differences between the three groups (control, DLB, AD). Post hoc testing between the groups was conducted using the Bonferroni correction. Correlations between gait variables and the walking speed conditions were also performed.
3. Results MMSE scores were significantly lower in both patient groups compared to the control group ( p < 0.01). Scores from the motor examination section of the UPDRS were significantly higher (indicating greater motor impairment) in the DLB group than in the AD group ( p < 0.001, Table 1).
Fig. 1. Mean values for walking velocity (A), stride length (B), double support (C), cadence (D) and step width (E) in subjects with AD, DLB and controls at self-selected slow, preferred and fast speeds.
J.R. Merory et al. / Gait & Posture 26 (2007) 414–419 Table 2 Spearman rank order correlations between condition (slow, preferred, fast) and gait variables Condition DLB Velocity Cadence Stride length Step width Double support *
AD *
0.82 0.81* 0.74* 0.08 0.59*
Control *
0.81 0.85* 0.59* 0.22 0.66*
0.82* 0.85* 0.62* 0.11 0.60*
p < 0.01.
Duration of illness was reported to be less than 4 years for all subjects with dementia. Fig. 1 shows the spatiotemporal gait characteristics of velocity, cadence, stride length, step width and doublesupport percentage for each of the three groups of subjects at slow, preferred and fast walking speeds. There were no differences between the DLB and AD patient groups for any of the measured gait variables. Velocity and stride length values were significantly reduced in both patient groups compared to the control group at all speeds ( p < 0.01 slow and preferred speed; p < 0.05 fast speed; Fig. 1A and B). Percentage of time spent in double limb support was significantly increased in both patient groups compared to the control group at all walking speeds ( p < 0.01; Fig. 1C). There was no difference in cadence between the three groups at preferred and fast speeds. However, at slow speed, the AD group walked with a slower cadence than the control group ( p < 0.05). There were no differences in step width between the three groups at any speed. Correlations between conditions (slow, preferred, fast) and gait outcome variables are displayed in Table 2. Significant correlations were found for all three groups for velocity, cadence, stride length and percentage of gait cycle in double limb support.
4. Discussion This study is the first to report quantitative analysis of the walking patterns of people with a specific diagnosis of probable DLB and compare this to people with AD and control subjects. The study has provided further evidence that people with dementia walk with decreased velocity and stride length and increased double support percentage compared with healthy older people and that these differences persist at different walking speeds. Notwithstanding the differences between control subjects and patients with dementia, all three groups had very similar rates of changes between the three different walking conditions, as evidenced by the significant correlations. Therefore, even though the DLB and AD subjects walked more slowly overall, the magnitude of the gait changes they made between the slow, preferred and fast walking conditions was consistent with that of the control subjects.
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That we did not find differences between the spatiotemporal gait characteristics of subjects with DLB and AD was not predicted and is at odds with previous studies making similar comparisons [17,18]. This may be due to the interaction of the type of walking test used and the effect of parkinsonism, which is more common and often severe in patients with DLB than those with AD [26], and is accentuated when movement sequences are longer or more complex [27]. Our study used measures of the simple gait task of walking in a straight line and acceleration and deceleration phases were not included in the analysis. Waite et al. [18] used a walking test, which involved timing a 5 m returned walk. Gnanalingham et al. [17] used a similar walking procedure with the addition of rising from an armless chair prior to walking and returning to the seated position. The inclusion of turns, standing up and sitting down, increased the complexity and sequence length of the walking task in these studies. The constant velocity straight line walking task measured in our study is less likely to have produced this differential effect between subjects with the two dementia types. The similarity in the measured gait variables of the DLB and AD subjects also appears to conflict with the differences in scores on the motor section of the UPDRS between the two groups. A possible explanation may be that the UPDRS includes scores for a number of motor characteristics other than gait. No subject with either form of dementia scored more than one for the gait item of the UPDRS (indicating all walked with normal or slowed gait but with no other difficulties), despite the DLB subjects’ higher scores for other motor items. There is also some redundancy of items in the motor section, which may lead to inflation of these scores relative to other items [28]. Related to this is the concern that the scoring of some aspects of the motor section of the UPDRS may not necessarily reflect their impact on a functional activity such as walking [28]. The findings of this pilot study are limited by the small number of mostly male subjects in each group. However the study is well controlled, using a validated method [25] to quantify gait at three self-selected constant speeds. Participants from the two dementia groups also demonstrated only mild cognitive impairment. Increased severity of dementia may produce changes in gait characteristics that are different for different dementia types. Mean MMSE scores for subjects with dementia in one of the previous DLB gait studies were much lower than in this study [17], however Waite et al. [18] found severity of dementia had little or no effect on gait measures in their study. The relationship between measures of gait and brain pathophysiology was not explored as this was beyond the scope of the study. Preliminary evidence suggests that the gait disorders of AD and DLB may occur via different pathophysiological mechanisms. It has been argued that midbrain abnormalities in AD may produce some gait features similar to DLB [29]. However, dopamine transporter ligands such as Beta-CIT demonstrate no diminution
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in AD, in contrast to DLB [30]. Pittsburgh Compound-B (PIB) scans display copious frontal amyloid in AD patients [31], and this frontal amyloid deposition in AD may be associated with the observed gait defects. Future investigations correlating the degree of frontal amyloid involvement with gait abnormalities in AD may shed light on the mechanism of gait changes in AD. In conclusion, this preliminary investigation demonstrates that a group of subjects with probable DLB had very similar spatiotemporal gait parameters when walking in a straight line at self-selected speeds to a group with AD, and that both were significantly different from healthy controls. This illustrates the value of quantitative gait analysis in revealing gait characteristics that may not be obvious using qualitative methods. In order to further examine similarities and differences in gait patterns of people with DLB and related disorders, subsequent studies should evaluate changes in gait characteristics using systematic alteration of the walking task in larger subject groups over time and relate these findings to pathophysiological data. Conflict of interest statement No commercial entity paid or directed, or agreed to pay or direct, any benefits to any research fund, foundation, educational institution, or other charitable or non-profit organization with which the authors of the paper ‘‘Quantitative Gait Analysis In Patients With Dementia With Lewy Bodies And Alzheimer’s Disease’’ are affiliated or associated.
Acknowledgement This project was funded by a La Trobe University Faculty of Health Sciences Research Grant.
References [1] Visser H. Gait and balance in senile dementia of Alzheimer’s type. Age Ageing 1983;12(4):296–301. [2] Tanaka A, Okuzumi H, Kobayashi I, Murai N, Meguro K, Nakamura T. Gait disturbance of patients with vascular and Alzheimer-type dementias. Percept Mot Skills 1995;80(3 Pt 1):735–8. [3] O’Keeffe ST, Kazeem H, Philpott RM, Playfer JR, Gosney M, Lye M. Gait disturbance in Alzheimer’s disease: a clinical study. Age Ageing 1996;25(4):313–6. [4] Sheridan PL, Solomont J, Kowall N, Hausdorff JM. Influence of executive function on locomotor function: divided attention increases gait variability in Alzheimer’s disease. J Am Geriatr Soc 2003;51(11): 1633–7. [5] Buchner D, Larson E. Falls and fractures in patients with Alzheimertype dementia. JAMA 1987;257(11):1492–5. [6] Morris J, Rubin E, Morris E, Mandel S. Senile dementia of the Alzheimer’s type: an important risk factor for serious falls. J Gerontol 1987;42(4):412–7.
[7] Tinetti ME, Speechley M, Ginter SF. Risk factors for falls among elderly persons living in the community. N Engl J Med 1988;319(26):1701–7. [8] van Dijk PT, Meulenberg OG, van de Sande HJ, Habbema JD. Falls in dementia patients. Gerontologist 1993;33(2):200–4. [9] Kenny RA, Richardson DA, Steen IN, McKeith IG, Bond J, Shaw FE. Predictors of further falls in patients with cognitive impairment and dementia attending the casualty department. Age Ageing 2000;29(Suppl 1):A23. [10] Nakamura T, Meguro K, Sasaki H. Relationship between falls and stride length variability in senile dementia of the Alzheimer type. Gerontology 1996;42(2):108–13. [11] Camicioli R, Licis L. Motor impairment predicts falls in specialized Alzheimer care units. Alzheimer Dis Assoc Disord 2004;18(4):214–8. [12] Franssen EH, Souren LE, Torossian CL, Reisberg B. Equilibrium and limb coordination in mild cognitive impairment and mild Alzheimer’s disease. J Am Geriatr Soc 1999;47(4):463–9. [13] Alexander NB, Mollo JM, Giordani B, et al. Maintenance of balance, gait patterns, and obstacle clearance in Alzheimer’s disease. Neurology 1995;45(5):908–14. [14] Verghese J, Lipton RB, Hall CB, Kuslansky G, Katz MJ, Buschke H. Abnormality of gait as a predictor of non-Alzheimer’s dementia. N Engl J Med 2002;347(22):1761–8. [15] van Iersel MB, Hoefsloot W, Munneke M, Bloem BR, Olde Rikkert MG. Systematic review of quantitative clinical gait analysis in patients with dementia. Z Gerontol Geriatr 2004;37(1):27–32. [16] McKeith IG, Galasko D, Kosaka K, et al. Consensus guidelines for the clinical and pathologic diagnosis of dementia with Lewy bodies (DLB): report of the consortium on DLB international workshop. Neurology 1996;47(5):1113–24. [17] Gnanalingham K, Byrne E, Thornton A, Sambrook M, Bannister P. Motor and cognitive function in Lewy body dementia: comparison with Alzheimer’s and Parkinson’s diseases. J Neurol Neurosurg Psychiatry 1997;62:243–52. [18] Waite LM, Broe GA, Grayson DA, Creasey H. Motor function and disability in the dementias. Int J Geriatr Psychiatry 2000;15:897–903. [19] Allan LM, Ballard CG, Burn DJ, Kenny RA. Prevalence and severity of gait disorders in Alzheimer’s and non-Alzheimer’s dementias. J Am Geriatr Soc 2005;53(10):1681–7. [20] McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDSADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34(7):939–44. [21] McKeith IG, Dickson DW, Lowe J, et al. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology 2005;65(12):1863–72. [22] Folstein MF, Folstein SE, McHugh PR. Mini-mental state: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–98. [23] Fahn S, Elton RL. Unified Parkinson’s disease rating scale. In: Fahn S, editor. Recent developments in Parkinson’s disease. New York: MacMillan; 1987. p. 153–63. [24] Bilney B, Morris M, Webster K. Concurrent related validity of the GAITRite walkway system for quantification of the spatial and temporal parameters of gait. Gait Posture 2003;17(1):68–74. [25] Webster KE, Wittwer JE, Feller JA. Validity of the GAITRite((R)) walkway system for the measurement of averaged and individual step parameters of gait. Gait Posture 2005;22(4):317–21. [26] Ballard C, O’Brien J, Swann A, et al. One year follow-up of parkinsonism in dementia with Lewy bodies. Dement Geriatr Cogn Disord 2000;11:219–22. [27] Morris ME, Iansek R, Summers JJ, Matyas TA. Motor control considerations for the rehabilitation of gait in Parkinson’s disease. In: Glencross DJ, Piek JP, editors. Motor control and sensory motor integration: issues and directions. Elsevier Science B. V; 1995 . p. 61–93.
J.R. Merory et al. / Gait & Posture 26 (2007) 414–419 [28] Movement Disorder Society Task Force on Rating Scales for Parkinson’s Disease. The Unified Parkinson’s Disease Rating Scale (UPDRS): status and recommendations. Move Dis 2003;18(7):738– 50. [29] Burns JM, Galvin JE, Roe CM, Morris JC, McKeel DW. The pathology of the substantia nigra in Alzheimer disease with extrapyramidal signs. Neurology 2005;64(8):1397–403.
419
[30] Rowe CC, Villemagne VL, Ellis JR, et al. I-123 Beta-CIT SPECT and FDG-PET in dementia with Lewy bodies and Alzheimer’s disease. In: Proceedings of the program and abstracts of the 7th international conference AD/PD; 2005. p. 79. [31] Rowe CC, Ackermann U, Gong S, et al. Amyloid imaging in Lewy body dementia with 11C-PIB-PET. J Neurol Sci 2005;238(Suppl 1):S98–9.