Postural tremor in Wilson\'s disease: a magnetoencephalographic study

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30. Elble RJ. Diagnostic criteria for essential tremor and differential diagnosis. Neurology 2000;54(Suppl. 4):S2–S6. 31. Lundervold AD, Pahwa R, Ament AP, Corbin ED. Validity of clinical and patient ratings of tremor disability among older adults. Parkinsonism Relat Disord 2003;10:15–18. 32. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215. 33. Friso R, Choi S-W, Gireli D, et al. A common mutation in the 5,10methylenetetra-hydrofolate reductase gene affects genomic DNA methylation through an interaction with folate status. Proc Natl Acad Sci USA 2002;99:5606 –5611. 34. Louis ED, Zheng W, Jurewicz EC, et al. Elevation of blood ␤-carboline alkaloids in essential tremor. Neurology 2002;59:1940 –1944. 35. Deuschl G, Elble RJ. The pathophysiology of essential tremor. Neurology 2000;54(Suppl. 4):S14 –S20. 36. Jankovic J. Essential tremor: heterogeneous disorder. Mov Disord 2002;17:633– 637.

Postural Tremor in Wilson’s Disease: A Magnetoencephalographic Study Martin Su¨dmeyer, MD, Bettina Pollok, PhD, Harald Hefter, MD, PhD, Joachim Gross, PhD, Lars Wojtecki, MD, Markus Butz, MA, Lars Timmermann, MD, and Alfons Schnitzler, MD* Department of Neurology, Heinrich-Heine-University, Du¨sseldorf, Germany Abstract: The following study included 5 Wilson’s disease (WD) patients showing a right-sided postural forearm tremor (4 – 6 Hz) and addressed the question of whether the primary motor cortex (M1) is involved in tremor generation. Using a 122-channel whole-head neuromagnetometer and surface electromyogram (EMG), we investigated cerebromuscular coupling. Postural tremor was observed in a sustained 45-degree posture of the right-sided forearm. Data were analyzed using dynamic imaging of coherent sources (DICS), revealing cerebromuscular coupling between EMG and cerebral activity. Coherent sources were superimposed on individual high-resolution T1-weighted magnetic resonance images (MRI). Phase lags between EMG and cerebral areas showing strongest coherence were determined by means of a Hilbert transform of both signals. In all patients, postural tremor was associated with strong

*Correspondence to: Prof. Alfons Schnitzler, Department of Neurology, MEG-Laboratory, Heinrich-Heine-University, Moorenstr. 5, D-40225 Du¨sseldorf, Germany. E-mail: [email protected] Received 10 October 2003; Revised 5 April 2004; Accepted 13 April 2004 Published online 15 July 2004 in Wiley InterScience (www. DOI: 10.1002/mds.20240

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coherence between tremor EMG and activity in contralateral primary sensorimotor cortex (S1/M1) at tremor or double tremor frequency. Phase lag values between S1/M1 activity and EMG revealed efferent and afferent components in the corticomuscular coupling. Taken together, our results indicate that postural tremor in WD is mediated through a pathological oscillatory drive from the primary motor cortex. © 2004 Movement Disorder Society Key words: Wilson’s disease; tremor; MEG; MRI; DICS; coherence

Neurological manifestations of Wilson’s disease (WD) appear most commonly in adolescents or young adults (average onset age, 20 years). Patients show primarily movement disorders,1 with tremor being present in about one-third to one-half of these cases.2 Tremor can be of any type, from postural to severe cerebellar tremor, and is seen often as a combination of different tremor types.2 Samuel Alexander Kinnier Wilson described this phenomenon in the following way: “ . . .tremors wax and wane, they leave one part for another, or alter their type in the same segment according to whether it is being used or not . . .”3 Histological and radiological studies in patients with WD proved that copper deposition in the brain leads to necrosis of neurons in combination with cavitation. Based on this knowledge and the fact that the main regions of copper deposition are the basal ganglia,4 – 6 it has been considered that subcortical lesions generate postural and action tremor in WD,7 but it remains unclear whether postural tremor in WD is mediated through the primary motor cortex. We used noninvasive magnetoencephalographic (MEG) and electromyographic (EMG) recordings to evaluate whether the primary motor cortex is involved in generation of postural tremor in WD.8,9 PATIENTS AND METHODS Patients Our study included 5 male patients (mean age ⫾ standard deviation [SD], 40.2 ⫾ 8.5 years) with a manifest WD (mean duration ⫾ SD, 11.3 ⫾ 9.9 years) showing a right-sided postural forearm tremor without head or trunk tremor. Laboratory diagnostics, including liver function tests and serum copper, serum ceruloplasmin, serum ammonia, and 24-hour urinary copper excretion, were carried out in each patient on the day of tremor analysis. None of the patients had a history of hepatic encephalopathy or neurological diseases other than WD and all had been undergoing copper-chelating therapy since diagnosis had been made (Table 1). Written informed consent was ob-



TABLE 1. Clinical and laboratory findings of Wilson’s disease patients Patient no.


Age (yr)

Year diagnosed


Tremor (Hz)

Ceruloplasmin (20–60 mg/dl)

Serum copper (0.82–1.39 mg/dl)

Urine copper (0.01–0.06 mg/dl)

IV ammonia (15–55 ␮mol/l)

AST (⬍19 U/L)

1 2 3 4 5


54 34 38 42 33

1981 1987 1999 1997 1997

Trientine Trientine Trientine/zinc Trientine D-penicillamine

6 6 4 5 6

⬍7 ⬍7 12 ⬍7 ⬍7

0.22 0.3 0.6 0.21 0.16

0.19 0.14 0.24 0.14 0.51

10 22 17 31 12

16 14 18 12 13

Normal range of laboratory values noted in brackets. Tremor frequency was assessed by spectral analysis of surface electromyograms. M, male; IV ammonia, intravenous ammonia; AST, aspartate aminotransferase.

tained from each participant before measurement, and the study was approved by the local ethics committee (Study number 2160) and was in accordance with the Declaration of Helsinki. Recordings and Experimental Paradigm Neuromagnetic activity was recorded with a wholehead neuromagnetometer system (Neuromag 122; Neuromag, Helsinki, Finland) at a sampling rate of 1,000 Hz with a band pass filter of 0.03 to 330 Hz.10 Simultaneously, right-sided surface EMG (60-Hz high-pass filtered and rectified) of the thenar muscle group, the first dorsal interosseus (FDI), the superficial flexor digitorum longus (FDL), and the extensor digitorum communis (EDC) muscles were obtained. Electrooculograms (EOGs) were recorded to control for eye blinks. The exact position of the head with respect to the sensor array was determined by four indicator coils attached to the head of the patient.8,9 Postural tremor was observed in a sustained posture of the right-sided forearm. During periods of relaxation the patients laid their arms comfortably onto a self-made arm support, whereas during periods of steady contraction, the patient’s elbow rested on the arm support and they held their right forearm in a 45-degree upright position with splayed fingers (isometric hold task). Data were collected during three to four periods of up to 3 minutes of isometric hold. To exclude development of a fatigue tremor, the patients were allowed to rest for 1 minute after each period. For all patients, high-resolution magnetic resonance images (MRI) of 1-mm slice thickness were obtained from a 1.5-T Siemens Magnetom MRI scanner (Siemens; Munich/Erlangen, Germany). Data Analysis Epochs with eye blinks were rejected from further analysis. We used the analysis tool DICS (dynamic imaging of coherent sources) to calculate coupling between the EMG signals and cerebral activity.8,9 It employs a spatial filter algorithm11 and a realistic head model of the individual subject to identify brain areas that are coherent to the surface EMGs. Coherence spectra between the

identified areas and EMG were calculated with a resolution of 0.98 Hz. Coherence is a measure applied frequently for the interdependence of two signals in the frequency domain.12,13 In a first step, we carried out the transition from time to frequency domain by using fast Fourier transform (FFT). FFT was applied to all MEG and EMG signals in segments 1 second long (after applying a Hanning window), and the cross-spectral density C was computed between all combinations of MEG and EMG signals. The complex spectrum C was finally averaged across the entire recording period. One element Ci,j of the final cross-spectral matrix consists of the cross spectrum of signals i and j (i.e., signals seen by two different sensors). In the second step, we extracted the mean crossspectral density of all sensor combinations in a selected frequency band as a complex N ⫻ N matrix, where N was the number of signals (MEG and EMG). Computation of cerebromuscular coherence used the cross spectrum between the EMG and the MEG signal. A third step consisted of the application of a spatial filter in the frequency domain,8 allowing the estimation of coherence between a point in the brain and an external reference signal (cerebromuscular coherence). To create tomographic maps, the spatial filter was applied to a large number of voxels (6-mm voxel size) covering the entire brain, assigning to each voxel the coherence value to the EMG signal. Anatomical landmarks were identified in the individual MRI scans, and the MEG and MRI coordinates were aligned. Individual maps of strongest cerebromuscular coherence were spatially normalized, averaged, and displayed on a standard brain in SPM99 (Wellcome Department of Cognitive Neurology, Institute of Neurology, University College London, UK; online at,9 To compute the cerebromuscular delay, the activity of the identified cerebral source and the rectified tremor EMG signal of the FDI muscle was filtered with a narrow band pass filter (⫾ 1 Hz) at the frequency band of cerebromuscular coherence. The Hilbert transform was applied to both signals, separating phase and amplitude.

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Times of maximum amplitudes of the EMG, which corresponded to maximum tremor, were detected from the Hilbert amplitude to improve the signal-to-noise ratio due to natural fluctuation in the intensity of postural tremor. The instantaneous phase differences between the cerebral source activity and the EMG signal at these times of maximum amplitude were computed. Phase differences between the two signals were transferred into time differences and plotted in histograms to estimate the cerebromuscular delay. Positive time values indicate that cerebral oscillations precede peripheral oscillations, whereas negative time values indicate cerebral oscillations lagging peripheral oscillations (for further details of the phase delay calculation, see Schnitzler and colleagues13 and Gross and coworkers14). RESULTS Diagnostic details and laboratory findings are summarized in Table 1. Postural tremor affected different forearm muscles in the range of 4 to 6 Hz (mean ⫾ SD 5.4 ⫾ 0.9 Hz) and started with a latent period of up to 20 to 30 seconds. Spectral analysis of the surface EMGs consistently revealed a peak at tremor frequency and at double tremor frequency (Fig. 1, lower panels).

In all patients, the cerebral area with the strongest coherence to the right-sided tremor EMGs in both frequency bands could be identified in the contralateral primary sensorimotor cortex (S1/M1; Fig. 2A,B). Group results of cerebromuscular coupling are illustrated in Figure 3 and confirm S1/M1 as the area of maximum coherence to the tremor muscles. Coherence values between S1/M1 and the surface EMGs are summarized in Table 2. Significant coupling was observed with the FDI muscle in at least one of both tremor frequency bands in all cases. Coherence between the sensorimotor cortex and the thenar muscles and FDL muscle could be identified in 4 patients each, whereas the EDC muscle revealed significant coupling to S1/M1 in 3 of 5 patients. Coherence between the cerebral source and each muscle was strongest at double tremor frequency in all cases (Table 2, Fig. 2C). Comparison of coherence between the first half and the second half of the tremor period revealed no significant differences (P ⬎ 0.05). Furthermore, the cerebromuscular coherence spectra showed broad peaks in the physiological 15- to 33-Hz frequency range. Between EDC muscle and S1/M1, all patients showed significant coupling in the 15- to 33-Hz

FIG. 1. Surface EMGs of postural tremor in Patient 3 with Wilson’s disease. A: Right-hand surface EMG trace (2 seconds) demonstrating a 4-Hz tremor in thenar muscles (lower trace) but not in the extensor digitorum communis (EDC) muscle (upper trace). B: EMG power spectral analysis of the thenar muscle group with dominant peaks in the single and double tremor frequency (4 and 8 Hz) and no tremor peak in the EDC muscle.

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FIG. 2. Cerebromuscular coherence in a patient with Wilson’s disease. A: MEG whole-head plot viewed from above presenting the coherence between all 122 sensors and the right thenar muscle group. Significant cerebromuscular coherence at single and double tremor frequency was found in sensors above the left sensorimotor cortex. B: The area of strongest cerebromuscular coupling is located in the left primary sensorimotor cortex (S1/M1). Source analysis was accomplished with DICS and superimposed on the individual high-resolution MRI-scan. (L, left; R, right; A, anterior; P, posterior). C: Coupling between left S1/M1 activity and right EMG of thenar muscles. Dashed line indicates 99% confidence level. The graph shows large significant coherence at double tremor frequency, and a small, nonsignificant peak at single tremor frequency. Inset: Histogram of delays between contralateral S1/M1 and the rectified EMG signal of the thenar muscle. Delays were computed from phase differences during times of strongest tremor. Maximum peaks were evident at 13.5 msec (indicating efferent drive of M1) and at ⫺16.5 msec (indicating afferent input to S1). FIG. 3. Mean localization of the corticomuscular coherence at single or double tremor frequency was spatially normalized and mapped onto a brain normalized with SPM99 (A, anterior; P, posterior). In all 5 Wilson’s disease patients, contralateral M1/S1 source consistently demonstrated strongest coherence to the right-sided tremor EMGs.

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TABLE 2. Cerebromuscular coherence between S1/M1 and surface electromyograms S1/M1-muscle frequency (Hz)/coherence (%) Thenar




Patient no.



15–33 Hz



15–33 Hz



15–33 Hz



15–33 Hz

1 2 3 4 5 Mean SD

6.5/3.1 6.5/1.2 — — — 6.5/2.1 0.0/1.4

13.0/9.9 — 9.1/10.0 — 13.0/0.6 11.7/6.8 2.3/5.4

31.3/0.4 — — — 18.2/0.7 24.8/0.6 9.3/0.2

6.5/3.6 6.5/1.3 — 5.2/1.5 — 6.1/2.1 0.8/1.3

13.0/9.5 11.7/2.5 7.8/3.4 13.0/2.2 10.4/1.0 11.2/3.7 2.2/3.3

30.0/1.0 32.6/1.2 — 19.5/8.2 19.5/1.5 25.4/3.0 6.9/3.5

6.5/2.9 6.5/1.0 — 5.2/6.9 — 6.1/3.6 0.8/3.0

13.0/13.3 — — — 13.0/0.6 13.0/6.9 0/9.0

31.3/1.0 — — — 19.5/0.5 25.4/0.8 8.3/0.4

6.5/3.1 — — 5.2/2.1 — 5.9/2.6 0.9/0.7

13.0/14.7 11.7/1.4 — 9.1/2.1 — 11.3/6.1 2.0/7.5

31.3/1.2 27.4/1.0 20.9/1.7 19.5/5.7 19.5/0.9 23.7/2.1 5.4/2.0

The strength of corticomuscular coherence (%) at tremor, double tremor, and 15–33 Hz frequency range is demonstrated. The first number indicates the frequency (Hz), the second number the significant coherence above the 95% confidence interval (in %). Mean values and standard deviation (SD) were calculated. FDI, first dorsal interosseus muscle; FDL, superficial flexor digitorum longus muscle; EDC, extensor digitorum communis muscle.

band (Table 2). In 2 cases, there was no clear tremor peak detectable in the EDC muscle whereas tremor EMG peaks were demonstrated in the thenar, FDI, and FDL muscle. Comparison of MEG-EMG coherence localization between the tremor frequency range and the 15- to 33-Hz band showed no significant differences in position or orientation of the S1/M1 source. To characterize cerebromuscular coherence, we calculated the phase shift between S1/M1 and tremor EMGs. Because all patients showed significant coupling at single or double tremor frequency between S1/M1 and FDI muscle, we used FDI activity as a reference signal to calculate the average conduction time. Analysis of the phase differences corresponded to consistent delays of 16.2 ⫾ 4.4 msec and ⫺17.3 ⫾ 4.8 msec, which were evident as peaks in the histogram and were in agreement with corticomuscular conduction times (Table 3).14,15 DISCUSSION The results of the present study demonstrate focal involvement of S1/M1 in postural tremor generation of WD. We showed that the cerebromuscular coupling durTABLE 3. Phase differences between contralateral S1/M1 source and right-sided FDI muscle during times of strongest tremor Patient no.

Time (msec)

Bin counts

Time (msec)

Bin counts

1 2 3 4 5 Mean SD

⫺15 ⫺18.5 ⫺11 ⫺18 ⫺24 ⫺17.3 4.8

57 91 107 13 71 67.8 36.1

19 13 11 22 16 16.2 4.4

129 65 107 52 123 95.2 34.8

FDI, first dorsal interosseus muscle; SD, standard deviation.

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ing postural tremor was mediated consistently through an oscillatory drive at the single and double tremor frequency. In addition, the physiological corticomuscular coherence of 15- to 33-Hz was evident. The most frequent presentation in WD, diagnosed in up to 30% of the cases, is a progressive cirrhosis of the liver; accordingly patients may have hepatic encephalopathy.16 Both hepatic disorders and copper deposition in the brain can therefore lead to tremor development.17 The patients participating in our study underwent exhaustive measurements of liver function values to exclude a hepatoencephalopathic genesis of the postural tremor. Evidently, excessive intracerebral copper accumulation leads to toxic neuronal reactions.18 Histological and radiological examinations disclosed the cerebral lesion mostly bilaterally in the basal ganglia, lenticular nuclei, thalami, dentate nuclei, and the brainstem.19 –23 Detailed empirical data about the correlation between the morphological changes and the clinical findings are rare, with MRI studies showing discordant results. Typical MR findings with no correlation to the clinical neurological symptoms were described in a collective of 38 patients.22 In contrast, another MRI study of 47 patients identified three clinical subgroups. The second subgroup was associated with tremor, ataxia, and focal thalamic lesions.4 It was therefore considered that the interruption of connections between the thalamus and cerebellum in particular might be responsible for the generation of tremor and ataxia in WD.4 Another study demonstrated pronounced lesions in the dentate nucleus. Correspondingly, it was argued that lesions of the dentato-rubrothalamic tract cause postural and action tremor in WD.7 None of these studies, however, combined electrophysiological methods with imaging analysis to classify and

TREMOR IN WILSON’S DISEASE identify pathological mechanisms of WD tremor generation. Our findings revealed significant coherence between the contralateral sensorimotor cortex (S1/M1) and the tremor EMGs in all patients. To differentiate whether the significant coupling was mainly efferent, afferent, or both, we calculated corticomuscular time delays.14 Our data revealed consistent phase lags between S1/M1 and EMG signals, reflecting efferent and afferent conduction. Mean positive phase lags between S1/M1 and FDI muscle are compatible with corticomuscular conduction times evaluated by transcranial stimulation of the human motor cortex and corticomuscular coherence analysis in normal subjects.14,15 Negative delays are probably a result of peripheral and central reafferences. These findings support the conjecture that the primary motor cortex (M1) drives the spinal motor neuron pool in postural tremor of WD. Primary motor area is also shown as the region of strongest coupling to the surface EMGs in patients with resting tremor of Parkinson’s disease and mini-asterixis caused by hepatic encephalopathy,24,25 whereas M1 involvement in essential tremor remains a matter of debate. On the one hand, Halliday and coworkers26 described an absence of significant coherence between MEG and EMG at tremor frequencies, considering that essential tremor is imposed on the active muscle through descending pathways other than those originating in M1. On the other hand, results of an electroencephalogram (EEG)-EMG recording published by Hellwig and coauthors27 demonstrated significant corticomuscular coherence between S1/M1 and tremor dominant muscles. The findings of the present study, however, suggest that the motor cortex is involved in WD postural tremor generation. Physiological corticomuscular coupling during voluntary isometric muscle contraction has been found characteristically in the frequency range of 15 to 33 Hz.14,28,29 In our patients, corticomuscular coherence was present during isometric contraction in the frequency range of 15 to 33 Hz independently from cerebromuscular coupling at tremor frequency. Interestingly, our cerebral source analysis in the 15- to 33-Hz frequency range revealed maximum coupling between EMGs and contralateral S1/M1 corresponding to the cerebral source localization and orientation at tremor or double tremor frequency. Based on our data, in WD postural tremor it might therefore be speculated that different central oscillators are independently activating the muscles at frequencies of 15 to 33 Hz as well as in the tremor frequency range. In contrast to our findings, however, during isometric contraction in patients with postural tremor caused by hepatic encephalopathy, corticomuscular coherence


could be found at tremor frequency only but not in the 15- to 33-Hz range.24 The cerebromuscular coupling observed in our study demonstrated coherence at tremor or double frequency in all patients; coherence analysis in Parkinson’s resting tremor has shown similar results.25,30 The functional meaning of this phenomenon remains under discussion. It should be noted that the tremor-related signals are not strictly sinusoidal, leading to the occurrence of higher harmonics in a frequency representation. In summary, our study demonstrates that the primary motor cortex (M1) modulates the descending corticospinal pathways, leading to oscillations in muscle activity in Wilson’s disease postural tremor. The possible contribution of other cerebral areas connected with M1 requires evaluation in further studies. Acknowledgments: This study was supported by the VolkswagenStiftung (I/73240). We thank the Wilson’s disease patients for their participation in this study, Dr. Hemker and Dr. Kircheis for expert help measuring liver function values, and Mrs. E. Ra¨disch for technical support with the MRI scans.

REFERENCES 1. Jones EA, Weissenborn K. Neurology and the liver. J Neurol Neurosurg Psychiatry 1997;63:279 –293. 2. Matsumoto JY. Tremor disorders: overview. In: Adler CH, Ahlskog JE, editors. Parkinson’s disease and movement disorders: diagnosis and treatment guidelines for the practicing physician. Totowa, NJ: Humana Press; 2000. p 273–281. 3. Wilson SAK. Progressive lenticular degeneration. In: Bruce AN, editor. Neurology. Vol. 2, 2nd ed. London: Butterworth; 1954. p 941–967. 4. Oder W, Prayer L, Grimm G, et al. Wilson’s disease: evidence of subgroups derived from clinical findings and brain lesions. Neurology 1993;43:120 –124. 5. van Wassenaer-van Hall HN, van den Heuvel AG, Algra A, Hoogengrad TU, Mali WP. Wilson disease: findings at MR imaging and CT of the brain with clinical correlation. Radiology 1996; 198:531–536. 6. Hermann W, Gunther P, Hahn S, et al. [Cerebral MRI and evoked potentials in Wilson disease. Comparison of findings in patients with neurological follow-up]. Nervenarzt 2002;73:349 –354. 7. Matsuura T, Sasaki H, Tashiro K. Atypical MR findings in Wilson’s disease: pronounced lesions in the dentate nucleus causing tremor. J Neurol Neurosurg Psychiatry 1998;64:161. 8. Gross J, Kujala J, Hamalainen M, Timmermann L, Schnitzler A, Salmelin R. Dynamic imaging of coherent sources: Studying neural interactions in the human brain. Proc Natl Acad Sci USA 2001;98:694 – 699. 9. Gross J, Timmermann L, Kujala J, et al. The neural basis of intermittent motor control in humans. Proc Natl Acad Sci USA 2002;99:2299 –2302. 10. Ahonen AI, Ha¨ma¨la¨inen MS, Kajola MJ, et al. 122-channel SQUID instrument for investigating the magnetic signals from the human brain. Physica Scripta 1993;49:198 –205. 11. Gross J, Ioannides AA. Linear transformations of data space in MEG. Phys Med Biol 1999;44:2081–2097. 12. Halliday DM, Rosenberg JR, Amjad AM, Breeze P, Conway BA, Farmer SF. A framework for the analysis of mixed time series/ point process data—theory and application to the study of physi-

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Prevalence of Tremor in Multiple Sclerosis and Associated Disability in the Olmsted County Population Sean J. Pittock, MD,1 Robyn L. McClelland, PhD,2 William T. Mayr, MD,1 Moses Rodriguez, MD,1,3 and Joseph Y. Matsumoto, MD1* 1

Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA; 2Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA; 3Mayo Medical School and Graduate School, Mayo Clinic, Rochester, Minnesota, USA Abstract: We applied a clinical tremor rating scale and measures of disability to 200 of 201 multiple sclerosis patients from a prevalence cohort in Olmsted County, Minnesota. In a community-based sample, tremor was found clinically in 51 (25%) patients, although only 6 (3%) patients had severe tremor. Within the population as a whole, tremor was strongly associated with impairment disability and handicap. © 2004 Movement Disorder Society Key words: multiple sclerosis; tremor; epidemiology; population-based

There are few epidemiologic studies estimating the prevalence of tremor in multiple sclerosis (MS).1 An MS clinic-based study found tremor in 58% of patients and moderate or severe tremor in 15% of patients.2 This study was undertaken to provide population-based estimates of the prevalence of clinically evident MS tremor and assess its impact on impairment, disability, and handicap. PATIENTS AND METHODS Using the computerized centralized diagnostic index at the Mayo Clinic, we identified all patients with a diagnosis of MS in Olmsted County (OMC). All cases of definite (clinical and laboratory supported) MS who were residents of OMC on December 1, 2000, formed the prevalence cohort.3 The majority of patients in OMC received their care at the Mayo Clinic, with the remainder receiving care at either the Olmsted Medical Group

This article contains supplementary material, which is available online at *Correspondence to: Dr. Joseph Y. Matsumoto, Department of Neurology, Mayo Clinic, 200 First Street S.W., Rochester, MN 55905. E-mail: [email protected] Received 10 September 2003; Accepted 13 April 2004 Published online 16 June 2004 in Wiley InterScience (www. DOI: 10.1002/mds.20227

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