Transcranial magnetic stimulation as a prognostic tool in stroke

Transcranial magnetic stimulation as a prognostic tool in stroke

JOURNAL OF THE NEUROLOGICAL SCIENCES ELSEVIER Journal of Neurological Sciences 147 (1997) 73-80 Transcranial magnetic stimulation as a prognostic...

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JOURNAL

OF THE

NEUROLOGICAL SCIENCES

ELSEVIER

Journal of Neurological Sciences 147 (1997) 73-80

Transcranial magnetic stimulation as a prognostic tool in stroke Luis D’OlhaberriaguelT”Tb’*,

Josep-Maria Espadaler Gamissansa, Jaume Marrugat”, Antonio Valls”, Carlos Oliveras Leyb, Jos&Luis Seoanea

“Department of Clinical Neurophysiology, Hospital de1 Mar, Autonomous Universiv of Barcelonu, Barcelona, Spain ‘Department of Neurology, Hospital de1 Mar, Autonomous University of Barcelona, Barcelona, Spain ‘Department of Epidemiology, Institut Municipal d’bwestigacib Mt?dica, Barcelona, Spain

Received 12 April 1996; revised 31 July 1996; accepted 17 October 1996

Abstract Our aims were to evaluate the prognostic usefulness of magnetic motor evoked potentials (MMEPs) in ischemic stroke, to study the evolution of MMEP abnormalities and the relationships between MMEP abnormalities and infarction topography. We prospectively analyzed 50 consecutive ischemic stroke patients who were followed up to 1 year. MMEPs were recorded 1, 3, 30 and 90 days after stroke and we measured amplitudes and latencies/central motor conduction times (CMCTs) of MMEPs from hypothenar, biceps brachiallis, gastrocnemius and quadriceps. Univariate and multivariate analyses of the clinical and MMEPs data were performed. Patients with Rankin O-3 at 1 year had had acutely MMEPs with shorter latencies and higher amplitudes than patients with Rankin 4-5 or deceased patients. Increased blood pressure correlated with increased survival, whereas increased heart rate and hyperglycemia correlated with increased mortality. The variables infarction size on second CT, age, and first day CMCT-SI correctly classified 1 year outcome on discriminant analysis. The inclusion of MMEPs values increased the probability of correct classification from 76% to 84%. We conclude that in patients with nondisabling strokes MMEPs may have an independent value in the prediction of prognosis, increasing the accuracy of prognosis calculations made employing clinical and laboratory data. Topography of lesions should be considered when analyzing MMEP abnormalities after stroke. 0 1997 Elsevier Science B.V. All rights reserved. Keywords: Transcranial magnetic stimulation; Stroke; Cerebra1 infarction Tachycardia; Arterial hypertension; Diagnostic tests

1. Introduction The prognosis of ischemic stroke rests on the neurological status during the acute phase that partially depends on infarction size. Some other factors, such as hyperglycemia, could result in increased infarction size (Helgason, 1989). As new, promising therapies for ischemic stroke emerge, it becomes increasingly necessary to improve the accuracy of stroke prognostic estimations. However, the prognostic *Corresponding author. Tel.: + 1 313 8767253; fax: + 1 313 8763014; e-mail: [email protected]. ‘Current address:Center for Stroke Research,Department of Neurology, K-l 1, Henry Ford Hospital, 2799 West Grand Boulevard, 48202 Detroit, MI, USA. 0022-510X/97/$37.00 0 1997 Elsevier Science B.V. All rights reserved PII SOO22-510X(96)05312-9

prognosis; Motor

evoked potentials;

Hyperglycemia;

information obtained from the initial CT is limited by its drawbacks to detect early ischemic changes (Orgogozo and Dartigues, 1991; Chamorro et al., 1995; Henon et al., 1995). New imaging techniques, such as diffusion-weighted MRI, enable us to image very early ischemic changes (Welch et al., 1995). Transcranial magnetic stimulation (TMS) (Barker et al., 1985) allows us to obtain magnetic motor evoked potentials (MMEP) (King and Chiappa, 1990; Murray, 1992) that may be employed to study motor pathways damage. Previous studies (Bridgers, 1989; Kandler et al., 1991; Ferbert et al., 1992; Heald et al., 1993a, Heald et al., 1993b; Arac et al., 1994) suggested some value of MMEP in ischemic stroke prognosis. However,, it is not satisfactory to only demonstrate a correlation between MMEPs

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abnormalities and stroke outcome, but it is also necessary to demonstrate the prognostic value of MMEPs after taking into account the neurological status and other biological factors (Yatsu et al., 1992). Although previous experimental studies suggested that MMEP abnormalities could relate to the topography of the infarctions (Patton and Amasian, 1954; Amassian et al., 1989; Hallet et al., 1989), the relevance of infarction topography on the evolution of MMEP changes has not been clarified. Additionally, it is unclear if the recovery of MMEPs reflects the pattern of muscle paralysis and the timing of motor recovery after stroke. The primary objectives of this study are to demonstrate whether abnormalities in MMEPs after ischemic stroke correlate with functional impairment, and to compare the prognostic value of MMEPs with that of the more timehonored clinical data. The secondary goals are to analyze the role of infarction topography on MMEPs abnormalities, the relationship between infarction topography and MMEPs evolution, the pattern and timing of MMEP recovery and finally the feasibility of lower limb MMEP recording.

2. Method 2.1. Patients and clinical evaluation We studied consecutive patients, aged between 45 and 80 years, admitted to Hospital de1 Mar (Barcelona, Spain) for ischemic stroke. Inclusion criteria were: admission within 24h after the onset of symptoms; motor pyramidal deficit in at least one limb; head CT scan excluding other disorders; and informed consent. Exclusion criteria were lack of motor impairment, inability to give consent or contraindications to TMS (Bridgers, 1989; King and Chiappa, 1990; Murray, 1992). Acute phase evaluation included: patient history; clinical assessment (Toronto Stroke Scale, TSS) (Hachinski and Norris, 1987); blood pressure; routine laboratory tests; EKG; continuous and B-mode carotid Doppler studies; and two CT scans. A first CT was done on admission (prior to inclusion in the study), and a second CT scan was done 3-6 days afterwards (Orgogozo and Dartigues, 1991) to determine size, arterial distribution and topography. When no lesion was seen on CT, a MRI study was performed to assess arterial distribution and topography. There were four categories of infarction size on CT: ‘zero’ (no lesion); ‘small’ (maximal diameter 3 cm) (Marti-Vilalta and Matias-Gum, 1987). Infarction size was measured on serial slices parallel to the orbitomental plane. Infarctions were considered of carotid or vertebrobasilar distribution according to arterial territory involved; superficial (cortical) or deep (subcortical) in topography (as one of the aims of this study was to

compare differences between ‘neuronal’ and ‘axonal’ lesions, comparisons were done between superficial cortical - infarctions versus all deep - subcortical infarctions, these including deep hemispheric infarctions and brainstem infarctions; infarctions with negative neuroradiological studies were considered also to be deep as all of them presented with lacunar syndromes); and atherothrombotic, cardioembolic, lacunar, of unknown pathogenesis, or others according to etiology (Hachinski, 1990; Mohr and Sacco, 1992). Handicap at 1 and 3 months and 1 year was assessed employing the modified Rankin score (Van Jign, 1992). Rankin score categories were pooled as follows: Group A or ‘Nondisabled’, Rankin score 0 (no symptoms), 1 (only symptoms), 2 (some restriction on life style but independent) and 3 (partly dependent); Group B or ‘Disabled’, 4 (dependent, but not constant attention required) and 5 (fully dependent); and Group C or ‘Deceased’. Mortality was gauged using the Oxfordshire Community Stroke Project categories (Bamford et al., 1990). 2.2. Neurophysiologic

evaluation

One, three, 30 and 90 days after stroke, MMEPs were obtained through TMS, and recorded in four muscle groups from the affected side: hypothenar, biceps brachiallis, gastrocnemius and quadriceps. We delivered TMS through a 1.5 Tesla round coil (outer diameter 14 cm and inner diameter 4.5 cm), applied on vertex and connected to a Magstim (Novametrix) apparatus. We registered MMEPs on a EMG apparatus (MS-60, Medelec). Clockwise current was applied to the left motor cortex, and anticlockwise current to the right motor cortex. We employed cutaneous electrodes and conventional filter band in motor neurography studies to register MMEPs, that were obtained during a slight voluntary contraction of the target muscle at 10% of strength, i.e. in facilitation. In plegic patients, in which no EMG activity was detected, facilitation was attempted contracting the contralateral target muscle (Chiappa et al., 1991). We describe the complete technique elsewhere (Espadaler et al., 1992). Parameters measured were the shortest latency (or central motor conduction time, CMCT) and the highest amplitude of MMEPs in four responses. We estimated CMCTs (the time needed for the cortical stimuli to reach C8-Tl and L5-S 1 spinal levels), according to the following formula (Rossini et al., 1985): CMCT = Cortex to CMAP - (F + DL - 1)/2 where CMCT is the central motor conduction time; cortex to compound muscle action potential (CMAP), is the latency of the hypothenar or gastrocnemius MMEP after cortical stimuli; F is the shortest F-wave latency after 20 electrical peripheral responses in the cubital and tibia1 nerves; and DL is the distal latency of the hypothenar or gastrocnemius after cubital or tibia1 nerve electrical

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stimuli, at wrist and knee levels, respectively. Problems related with amplitude measurements made some researchers to concentrate on CMCT measurements alone (Heald et al., 1993a). However, both methodological (Claus, 1990; Eisen and Shtybel, 1990) and clinical (Kandler et al., 1991; Ferbert et al., 1992) studies did find it feasible. We did not include MMEPs thresholds in the current analyses, since in a preliminary analysis (yet unpublished) we did not find meaningful threshold differences.

2.3. Statistical analysis x2 test (with Yates correction when required), Fisher’s exact test, Student’s t-test, Mann Whitney U-test, ANOVA, and ANOVA test for repeated measures were used as required. Exact P values for x2 test for lineal trends were calculated with STATXACT-TURBO (Cytel, Cambridge, MA, USA) software. When significant differences were found in one-factor ANOVA, cross-tabulation of all categories was established using Scheffee method. Normality of distribution was assessed by the ratio of range to standard deviation. Latencies were logarithmically transformed because they deviated from normal distribution. The impact of a set of independent variables on 1 year prognosis (dependent variable) was analyzed with stepwise discriminant analysis. Twenty four independent variables were tested. Some of them had well known prognostic value (Allen, 1984; Yatsu et al., 1992) and those related to TMS were under specific evaluation in this study. These variables were: old infarctions on CT scan, age, systolic and diastolic blood pressure on admission, hemoglobin, glycemia on admission and 48 h later, heart rate on admission, heart rhythm (sinus rhythm, atria1 fibrillation), total TSS score on admission, score for 4 different items of the TSS (motor deficits - face, upper and lower limb - and ocular deviation) - the items aphasia and consciousness level scored ‘zero’ according to our inclusion criteria, size of infarction on the second CT scan, topography of infarction on CT scan or MRI and acute phase MMEPs values as described. Dependent variable included the prognostic categories (A,B,C) previously described. Discriminant analysis was used to calculate the mean group coordinates (mX1, mX2) for X equal to A, B, and C, and discriminant functions (Y 1, Y2) (number of outcome categories minus one) that allow to estimate an individual coordinates, and their probability of belonging to X group. The accuracy of classification predicted by the model is tested by comparison to the actual outcome. The contribution of variables to discriminate among the different prognostic groups was analyzed with Wilks’s lambda. Changes obtained by inclusion of MMEP variables were analyzed by eliminating them from the model using discriminant fixed models. Analyses were performed with BMDP (Dixon, 1992) statistical package. Results are expressed as mean?S.D., or, in the case of ordinal scale

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values, as median (Van Jign, 1992). Significance level was set at PcO.05.

3. Results 3.1. Clinical and radiological

characteristics

Out of the 50 patients there were 30 men (aged 64.958.8 years) and 20 women (aged 70.426.8 years), women being significantly older than men (Mann-Whitney, P = 0.02); 28 patients (56%) had a left hemiparesis and 22 (44%) a right hemiparesis; median Toronto Stroke Scale Score was 23.5. One year after stroke, eight patients had died (brain edema and transtentorial herniation, one patient; septic shock, two patients; myocardial infarction, two patients; heart failure, one patient; sudden death, one patient; disseminated intravascular coagulation, one patient). Clinical and radiological characteristics are shown in Table 1. Patients’s evolution was as follows: at 1 month Rankin 0 l/50 (2%), Rankin 1 12/50 (24%), Rankin 2 15/50 (30%), Rankin 3 10150 (20%), Rankin 4 7/50 (14%), Rankin 5 4/50 (8%), and Deceased l/50 (2%); at 3 months Rankin 0 l/50 (2%), Rankin 1 13/50 (26%), Rankin 2 14/50 (28%), Rankin 3 12/50 (24%), Rankin 4 4/50 (8%), Rankin 5 5/50 (lo%), and Deceased l/50 (2%); and at 1 year Rankin 0 5150 (lo%), Rankin 1 15/50 (30%), Rankin 2 11/50 (22%), Rankin 3 7/50 (14%), Rankin 4 3/50 (6%), Rankin 5 l/50 (2%), and Deceased 8/50 (16%). Table 1 Clinical and radiologic characteristics of the patients Slight upper limb impairment Mild upper limb impairment Severe upper limb impairment Plegia on the upper limb Slight lower limb impairment Mild lower limb impairment Severe lower limb impairment Plegia on the lower limb Arterial distribution: carotid Arterial distribution: vertebrobasilar Arterial distribution: unknown Infarction topography: superficial Infarction topography: deep Infarction size: zero Infarction size: small Infarction size: medium Infarction size: large Etiopathogenesis: atherothrombotic Etiopathogenesis: cardioembolic Etiopathogenesis: lacunar Etiopathogenesis: unknown Etiopathogenesis: others

16/50 16/50 6/50 12/50 18/50 14/50 5/50 5/50 41/50 5/50 4/50 12/50 38/50 10/50 19/50 13/50 8/50 13/50 14/50 13/50

(32%) (32%) (12%) (24%) (36%) (28%) (10%) (10%) (82%) (10%) (8%) (24%) (76%) (20%) (38%) (26%) (16%) (26%) (28%) (26%)

g/50(16%) 2/50 (4%)

The first CT scan did not show current lesions in 37/50 patients (74%), while current lesions were detected on the second CT scan in 40/50 patients (80%).

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3.2. Transcranial magnetic stimulation 3.2.1. Abolition of MMEPs All along the study there was a trend towards diminution of abolished MMEPs, which was statistically significant in every target muscle but the hypothenar: abolished biceps MMEP 22% day 1, 19% day 3, 8% day 30, and 0% day 90 (P = 0.0014; x2 for linear trends); abolished gastrocnemius MMEP 20% day 1, 11% day 3, 8% day 30, and 0% day 90 (P=O.O021; x2 for linear trends); and abolished quadriceps MMEP 18% day 1, 10% day 3, 3% day 30, and 0% day 90 (P=O.O018; x2 for linear trends). Considering topography and target muscle location, the diminution in abolished MMEPs was statistically significant in biceps MMEPs from superficial infarctions (58% day 1, 45% day 3, 11% day 30, and 0% day 90; P= 0.0018; x2 for linear trends), in gastrocnemius from deep infarctions (16% day 1, 19% day 3, 4% day 30, and 0% day 90; P = 0.014; x2 for linear trends); and in quadriceps MMEPs from deep infarctions (16% day 1, 8% day 3, 0% day 30, and 0% day 90; P =0.0039; x2 for linear trends). Both in superficial and in deep infarctions abolished MMEPs were scantly seen on Day 90, especially in proximal muscles where there was only one abolished MMEP on Day 90. Abolished MMEPs were more frequently seen all along the study in superficial than in deep infarctions, although statistically significant differences were restricted to biceps MMEPs recorded on days 1 (superficial 58% vs. deep 10%; P=O.O02; x2) and 3 (superficial 45% vs. deep 10%; P = 0.032; x2). 3.2.2. Relationships between MMEP abnormalities, topography and evolution On day 1, MMEPs from superficial infarctions had smaller amplitudes and longer latencies and CMCTs than those from deep infarctions, with statistically significant differences in hypothenar, gastrocnemius and quadriceps amplitudes and biceps latency (Table 2). From day 1 to day 90 (Table 3) amplitudes increased significantly in hypothenar, biceps and quadriceps from all cases; in biceps, gastrocnemius and quadriceps from superficial infarctions; and in hypothenar, biceps and quadriceps from deep infarctions. Significant latency changes consisted on CMCT-C8 and quadriceps latency decrease from all infarctions, and on CMCT-C8 decrease from deep infarctions. Interestingly, biceps MMEP latency showed a non-significant increase. 3.3. Prognostic indicators 3.3.1. Univariate analyses One year prognosis was significantly worse in patients with superficial than deep infarctions: Superficial A 33%, Superficial B 17% and Superficial C 50% vs. Deep A 89%, Deep B 5% and Deep C 5% (P=O.O002; x2) (proportions

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Table 2 Topographic comparison of day 1 MMEPs after cerebral infarction

Hypothenar CMCT-C8 Amplitude Biceps Latency Amplitude Gastrocnemius CMCT-S 1 Amplitude Quadriceps Latency Amplitude

Superficial (n = 12)

Deep (n = 38)

P

7.422.1 0.8+ 1.0

7.322.5 1.7t1.4

NS 0.04

16.723.4 0.95 1.7

14.122.7 1.5t1.3

0.009 NS

14.8k2.4 0.8kO.7

14.126.6 2.22 1.8

NS 0.01

26.3k4.0 0.8kO.7

25.424.1 2.622.3

NS 0.01

P: Unpaired two-tailed Student’s t-test. CMCT-C8 and CMCT-Sl, central motor conduction time to C8 and Sl, respectively. Latencies and CMCTs are expressed in ms and amplitudes in mV.

do not reach 100% because of rounding). Group A patients had significantly smaller biceps and quadriceps latencies and significantly higher gastrocnemius and quadriceps amplitudes than Group B or Group C patients (Table 4). Admission heart rate was significantly lower in Group A than in Group C (Group A 81.1?17 vs. Group B Table 3 Ninety days evolution of MMEPs

Hypothenar CMCT-C8 - all infarctions CMCT-C8 - superficial infarctions CMCT-C8 - deep infarctions Amplitude - all infarctions Amplitude - superficial infarctions Amplitude - deep infarctions Biceps Latency - all infarctions Latency - superficial infarctions Latency - deep infarctions Amplitude - all infarctions Amplitude - superficial infarctions Amplitude - deep infarctions Gastrocnemius CMCT-Sl - all infarctions CMCT-Sl - superficial infarctions CMCT-Sl - deep infarctions Amplitude - all infarctions Amplitude - superficial infarctions Amplitude - deep infarctions Quadriceps Latency - all infarctions Latency - superficial infarctions Latency - deep infarctions Amplitude - all infarctions Amplitude - superficial infarctions Amplitude - superficial infarctions

Day 1

Day 90

P

7.222.6 7.0’2.3 7.3k2.7 1.6k1.5 0.7kl.l 1.921.4

6.22 1.9 6.8k2.0 6.0? 1.9 2.221.7 1.0+1.8 2.6k1.5

0.0482 NS 0.0285 0.0027 NS 0.0073

14.523.2 17.423.1 13.622.8 1.4k1.4 1.1t2.0 1.421.2

15.025.3 17.728.2 14.2k3.9 2.021.8 1.8Z2.4 2.121.6

NS NS NS 0.0173 0.0393 0.0489

14.023.9 14.3t2.9 13.924.2 1.921.7 0.9kO.8 2.22 1.8

12.9t4.5 13.1k3.8 12.824.8 2.4k1.7 2.321.8 2.521.7

NS NS NS NS 0.0133 NS

25.224.4 25.524.5 25.224.5 2.2k2.2 0.8kO.6 2.6k2.4

23.522.9 24.1 i-4.6 23.322.3 3.522.2 3.0k2.4 3.7k2.1

0.0497 NS NS 0.0017 0.0202 0.0259

P, ANOVA test for repeated measures. CMCT-C8 and CMCT-Sl, central motor conduction time to C8 and Sl, respectively. Latencies and CMCTs are expressed in ms, and amplitudes in mV.

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Table 4 MMEPs latencies and amplitudes according to 1 year prognosis

Hypothenar CMCT-CI (ms) Amplitude (mV) Biceps Latency (ms) Amplitude (mV) Gastrocnemius CMCT-S 1 (ms) Amplitude (mV) Quadriceps Latency (ms) Amplitude (mV)

Group A

Group B

Group C

P”

8.6k1.4 1.751.4

11.155.9 1.221.4

7.4* 1.8 0.8?0.8

NS NS

14.423.3 1.621.4

17.923.3 1.221.8

17.224.5 0.320.6

0.04* NS

18212.6 2.22 1.8

28.42 19.4 0.5 +0.9

25.92 16.1 0.920.9

NS 0.04

25.925.2 2.622.2

33.825.9 0.5-tO.l

2826.6 1.2e1.6

0.02** 0.03**

CMCTC8, central motor conduction time to C8; CMCT-Sl, central motor conduction time to Sl. “ANOVA. *A vs. C and **A vs. B significant differences (0.05) Scheffee method.

82.2214.3 vs. Group C 103.2223.8 beats per min; ANOVA, P = 0.002). Systolic blood pressure was nonsignificantly different among the three groups, but diastolic blood pressure was significantly higher in group A than in group C (Group A 95518.1 vs. Group B 8525.7 VS. Group C 77.5? 18.3 mmHg; ANOVA, P=O.Ol). Deceased patients had significantly lower systolic (143.1 k30.8 vs. 168.0529.8 mmHg; t-test, P=O.O3) and diastolic (77.5218.2 vs. 94.Ok17.5 mmHg; t-test, P=O.Ol) blood pressure and higher heart rate (103.2223.8 vs. 81.126.1 beats per min; t-test, P =0.002) on admission than survivors. Glycemia 48 h after stroke in nondiabetics was significantly higher in deceased patients than in survivors (8.425.6 vs. 5.921.1 mmol/l; t-test, P=O.O2). 3.3.2. Multivariate analysis Discriminant analysis selected, in that order, the variables infarction size on CT, age, and CMCT-Sl as those Table 5 Effect of magnetic motor evoked potentials on the accuracy of classification at 1 year after stroke according to prognostic categories Prognostic categories

Proportion of correct classification MMEPS in Y,l and Y,2

1 Year after stroke A, ‘good’ B, ‘poor’ C, ‘deceased’ All categories

MMEPs included (a)

MMEPs not included (b)

87% 100% 63% 84%

76% 100% 62% 76%

Yl =9.20 - 0.77 (age) ~ 0.85 (size of infarction on CT scan) - 0.59 (CMCT-Sl). Y2= -4.31 + 0.68 (age) - 0.12 (size of infarction on CT scan) 0.49 (CMCT-Sl). Mean coordinates: A, m,l =0.50, m,2= -0.01. B, m,l = - 1.35, m,2=0.72. C, m,l=-1.69, m,2=-0.30. Prognosis calculated with MMEPs (a) and without them (b).

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that correctly classified 1 year outcome. Wilks’s lambda was
4. Discussion Our first aim was to test whether MMEPs recorded after stroke were reliable prognostic markers. This study shows that information provided by MMEPs may be useful in the prediction of stroke prognosis in patients with nondisabling strokes, since there were significant differences in latency and amplitude of MMEPs between patients with nondisabling strokes (Group A) and the other two groups. Previous studies of TMS in stroke did not compare MMEPs with the set of clinical data (Bridgers, 1989; Kandler et al., 1991; Ferbert et al., 1992; Heald et al., 1993a, Heald et al., 1993b; AraG et al., 1994). Accordingly, the second prognostic issue was whether MMEPs studies increased the prognostic accuracy of the classical clinical and laboratory data. Infarction size on second CT, age and CMCT-Sl were the variables selected in discriminant analysis. To note that current lesions showed up on first CT in just 20% of cases. In the prognostic score the addition of MMEPs values to clinical features improved the model from 76% to 84%. Most of this difference came from the improvement in the diagnosis in patients with a Rankin score from 0 to 3. In this group, in which an accurate prognostic estimation seems both more difficult and more important, the addition of MMEPs values increased the accuracy of classification from 76% to 87%. Prognosis was worse in superficial than in deep infarctions, probably due to differences in size, among others. A striking finding was the association between increased heart rate on admission and increased one year mortality. As cardiac arrhythmia monitoring was not performed by us, we can only speculate that increased heart rate could imply a worse prognosis through cerebrogenic arrhythmias (Oppenheimer et al., 1990). The prognostic implications of hyperglycemia are well known (Helgason, 1989). However, although there are solid physiopathological reasons to avoid a decrease in blood pressure in the acute phase of stroke (Powers, 1993), very few studies have actually analyzed the prognostic value of acute phase hypertension. Recently, it was shown that the lack of efficacy of nimodipine in ischemic stroke could be related to a decrease in blood pressure (Grotta, 1994). Only one of previous studies (Arac et al., 1994) recorded lower limb MMEPs. Lower limb palsy has been shown to be an important prognostic feature in stroke as it could reflect a larger area of lesion and may imply a longer period of bed rest (Allen, 1984; Chambers et al., 1987; Schneider and Gautier, 1994). That is why lower limb

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MMEPs would seem to be their neurophysiologic counterpart. In accordance with this hypothesis, CMCT-SI was one of the parameters included in the prognostic score, stressing the value of lower limb MMEPs. Abolished MMEPs were observed in the acute phase in 20% of patients which agrees with other MMEP studies (Bridgers, 1989; Kandler et al., 1991; Ferbert et al., 1992; Heald et al., 1993a; Heald et al., 1993b; AraG et al., 1994), which showed smaller percentages of abolished MMEPs than studies of electric motor evoked potentials (Berardelli et al., 1987; Thompson et al., 1987; Macdonell et al., 1989; Dominkus et al., 1990; Berardelli et al., 1991; Misra and Kalita, 1995). Superficial infarctions related with a higher proportion of abolished MMEPs, which had longer latenties and smaller amplitudes than MMEPs from deep infarctions. Lack of response after TMS does not imply a disruption in neural conduction. It could also be the result of a diminution in the size of descending volleys. Direct (D) waves being unable by themselves to generate a response, superficial lesions would preclude the generation of sufficient I waves to induce to such a response. Deep infarctions should not affect indirect (I) wave generation. The relationships between topography, latency and amplitude are multifarious. Latency could increase as a result of slowing of conduction through the largest, selective vulnerable, pyramidal fibers (Edgley et al., 1990; Kogure and Kato, 1992), diminution in the cortical stimulus, or partial lack of temporal summation due to a diminution in the initial descending volley. All three mechanisms might underlay latency changes in superficial infarctions. Amplitude could decrease as a result of temporal dispersion of the descending input or reduction in the number of descending fibers or volleys. Superficial lesions seem more likely to act through any of these mechanisms. Recovery of responses did not begin immediately (on day 3) but sometime afterwards; it was more expressive in deep than in superficial infarctions; and amplitudes clearly increased as the time passed whereas latencies and CMCTs could either decrease or marginally increase. Regarding the timing of recovery, our results are close to others (Duncan et al., 1992; Heald et al., 1993a). Restoration of protein synthesis does not take place before 72 h of recirculation (Kogure and Kato, 1992), deterioration of brain energy metabolism can continue for 3-4 days after stroke, and signs of late death of initially viable neurons have been detected within 2 weeks after stroke (Levine et al., 1988). The increase in amplitudes in our study is similar to that found by Kandler et al. (199 1) and might reflect in part the disappearance of acute phase phenomena. Persistent latency increase could suggest that the conduction through neural pathways after stroke is slower than through the normal corticospinal tract. Ipsilateral descending pathways (Chollet et al., 1991; Fries et al., 1991; Cao et al., 1996) or Wallerian degeneration of the pyramidal tract (Pujol et al., 1990) might also account for long lasting conduction delays. Whereas on day 1 abolished MMEPs were evenly

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distributed among the different muscles, recovery of responses took place earlier in biceps and lower limbs. This pattern of recovery could reflect the well known clinical feature of earlier and stronger improvement in proximal muscles (Colebatch and Gandevia, 1989; Warabi et al., 1990). We would like to mention some limitations of this study. First, we were able to find clear differences in MMEPs between patients with nondisabling strokes and all the other patients, but unable to differentiate between patients with disabling strokes and those who eventually died. This can be in part due to a selection bias related to the exclusion of patients with consciousness or language impairments. Similarly, there appear to be few advantages in using MMEPs to predict mortality, that in this population, as in almost any stroke population, was delayed and rarely due to the stroke itself. It is unlikely that MMEP recordings would predict death due to cardiac conditions (Silver et al., 1984; Bamford et al., 1990). The fact that the prognostic formula selected MMEPs values recorded 24 h after stroke, indicates the possible prognostic usefulness of MMEPs in stroke patients. The information MMEPs provide could be obtained early, when CT scan is still normal in most cases, and almost painlessly (as opposed to electrical stimulation). Our data also suggest that superficial lesions cause a deeper breakdown in MMEPs than deep lesions, and that lower limb MMEPs recordings are as feasible and reliable as upper limb MMEPs are.

Acknowledgments The authors are grateful to Alfons Moral, MD, Angel Chamorro, MD, and Panayiotis Mitsias, MD, for critical revision of the manuscript, to Joan Santamaria MD, YhD, and Vijaya Nagesh, PhD for providing access to references and to Marta Pulido MD, PhD, for editorial assistance and copy editing. Supported by the grant 90/0207 from the Fondo de Investigaciones Sanitarias de la Seguridad Social, Madrid. LD was the recipient of the grant 90/4217 ‘Beta de Iniciaci6n a la Investigacibn’ from the Fondo de Investigaciones Sanitarias de la Seguridad Social (Madrid) and currently receives the ‘Junior Javitz’ NIH fellowship.

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