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Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?
Journal of Clinical Neuroscience xxx (xxxx) xxx
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Clinical study
Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase? Minsun Kim a, Hyun Haeng Lee a,⇑, Jongmin Lee a,b,⇑ a b
Department of Rehabilitation Medicine, Konkuk University School of Medicine and Konkuk University Medical Center, Seoul, South Korea Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, South Korea
a r t i c l e
i n f o
Article history: Received 9 December 2019 Accepted 27 January 2020 Available online xxxx Keywords: Balance Gait Ambulation Sensory Somatosensory-evoked potential Stroke
a b s t r a c t Balance and ambulation are the result of a multicomponent control process through the interaction of the sensory and motor information. Despite the clinical relevance of the somatosensory system, its role has not drawn much attention from clinical researchers in that motor impairment is considered a major cause of dysfunction. There is little research on how somatosensory impairment alone affects functional disability after stroke. The purpose of this study was to investigate the effects of isolated somatosensory deficit on the balance and ambulation ability in patients with stroke. P38 latency of the SSEP was used to evaluate the integrity of the dorsal column-medial lemniscus pathway and the SSEP reference value was derived from the formula considering individual height and age. According to the SSEP latency, subjects were classified into ’normal’, ’abnormal’, and ’no response’ group. A total of 110 supratentorial stroke patients with at least grade 4 of the Medical Research Council scale of lower extremity on the affected side were enrolled. Berg balance scale (BBS) and functional ambulatory categories (FAC) showed significant differences among the groups (P < 0.05). In post-hoc analysis, the BBS and FAC was significantly different between the ’normal’ and ’abnormal SSEP’ group (P = 0.013 for BBS, P = 0.004 for FAC) and the ’normal’ and ’no response SSEP’ group (P = 0.015 for BBS, P = 0.006 for FAC). We found that isolated somatosensory impairment has a negative effect on the balance and ambulation ability in patients with supratentorial stroke after the acute phase. Ó 2020 Published by Elsevier Ltd.
1. Introduction Balance and ambulation are the result of a multicomponent control process through the interaction of the sensory input and motor output [1]. Balance is achieved through body and head movement strategies that recognize the disruption of the center of gravity due to external disturbances and the forces generated internally during voluntary movement or posture, such as walking and posture [2]. Despite the clinical relevance of the somatosensory system [3,4] its role has not drawn much attention from clinical researchers in that motor impairment is considered a major cause of dysfunction [5,6]. Somatosensory impairment has been reported to occur in over half of the patients with stroke [7,8] and it cause various problems such as inappropriate object recognition and manipulation [9], failure to avoid of danger with the limbs [10], and difficulty in balance control [11]. In particular, bal⇑ Corresponding authors at: Department of Rehabilitation Medicine, Konkuk University School of Medicine and Konkuk University Medical Center, 120-1 Neungdong-ro, Hwayang-dong, Gwangjin-gu, Seoul 05030, South Korea. E-mail addresses: [email protected] (H.H. Lee), [email protected] (J. Lee).
ance and ambulation function are the main determinants of independence of daily living performance, which is crucial for improving overall functioning and returning to society [12]. Locomotion control can be modulated by sensory information through the somatosensory, visual, and vestibular systems [13]. Stroke can affect all three types of sensory input, among which the incidence of somatosensory impairment is particularly high [14,15]. Sensory impairment after stroke is usually evaluated by clinical examinations and somatosensory-evoked potential (SSEP). However, clinical measurements were limited due to the sensitivity and reliability issues of the examiners and subjects [16]. Recently, SSEP has been widely used as a method for objectively assessing the damage to the dorsal column–medial lemniscus pathway of the somatosensory nerves [17,18]. In patients after stroke, the locomotion functions are affected by the motor component as well as the somatosensory system [19]. Previous studies have attempted to determine the effects on balance and gait by simultaneously considering motor and sensory components, and reported that the presence of a combined motor-evoked potential and SSEP response in the lower extremities is significantly associated with functional locomotion [20,21].
https://doi.org/10.1016/j.jocn.2020.01.084 0967-5868/Ó 2020 Published by Elsevier Ltd.
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
However, little research has been conducted on the effects of isolated somatosensory dysfunction on the functional ability in patients with stroke [22]. Therefore, our study sought to control as many factors as possible that could affect balance and ambulation, and determine the influence of the isolated somatosensory deficit. The aim of this study was to investigate the effect of isolated somatosensory deficit on the balance and ambulation in patients with supratentorial stroke after the acute phase using SSEP. 2. Methods 2.1. Study design and subjects We screened the records of 1797 patients admitted to the Department of Rehabilitation Medicine of a university hospital after the acute phase of stroke from January 2006 to August 2019. The lesion location and type of stroke was confirmed by brain computerized tomography (CT) or magnetic resonance imaging (MRI). The inclusion criteria were as follows: patients with only supratentorial brain lesions, who had SSEP assessed after at least 2 weeks post-stroke, who had at least grade 4 on the Medical Research Council (MRC) scale of lower extremity muscle strength on the affected side, including the hip flexor, knee extensor, and ankle dorsiflexor, and who ambulated independently before the stroke. The exclusion criteria were patients with previous symptomatic strokes, history of traumatic brain injury, multiple brain lesions, lower extremity peripheral neuropathy confirmed by electrophysiologic studies, hemineglect, visual field defects, vestibular dysfunction, or spasticity (Fig. 1). 2.2. SSEP method The SSEP was performed to determine the integrity of the dorsal column–medial lemniscus pathway of the somatosensory nervous system after transfer to the rehabilitation department. The Medelec Synergy EMG (VIASYS Healthcare, UK) was used for SSEP measurement. Subjects were positioned in the supine position. The environmental temperature was controlled at 22 °C–28 °C. The posterior tibial nerve was stimulated with rod electrode. The cathode was placed 1–2 cm distal to and posterior to the medial malleolus. The anode was placed 2–3 cm distal to the cathode. The stimulus intensity was adjusted to produce either slight plantar flexion of the great toe or cupping of the sole of the foot. At least 200 stimuli were repeated at a frequency of 3 times per second
and the responses were averaged. The process was repeated 2–3 times in ankle joint of each lower extremity. Using the International 10–20 system, the active electrode was placed on Cz0 , 2 cm behind Cz, and the reference electrode was placed on Fpz, midfrontal point. SSEP latency (named as P1 or P38) referred to the initial positive peak following stimulus onset and indicated the average peak latency of the predominant waveform located at approximately 38 msec. SSEP components, such as latency and amplitude, can be significantly affected by the subjects’ physiologic factors [23]. Considering this, the abnormality criteria for SSEP latency was based on the equation that considers individual height and age, as proposed by Miura et al. [24] (Table 1). Patients with an SSEP latency lower than the upper limit of normal value were classified into the ‘normal SSEP’ group (group 1), and those with equal to or greater than the upper limit of normal value were classified into the ‘abnormal SSEP’ group (group 2) (Fig. 2). Those where a peak could not be identified due to distortion of the graph were classified in the ‘no response SSEP’ group (group 3). 2.3. Clinical assessments The Berg balance scale (BBS), functional ambulatory categories (FACs), Motricity Index (MI), and Mini-Mental State Examination (MMSE) were evaluated in a few days with SSEP measurement. In this study, the BBS and FACs were the primary outcomes to assess the balance and ambulation ability of post-stroke patients. 2.3.1. BBS The BBS was used to assess the patient’s functional balance ability. It is a tool for evaluating the dynamic and static balance developed by Catherine Berg in 1989 and has been shown to have high reliability and validity in patients with stroke [25]. Unlike other balance assessment tools, BBS consists of items related to daily activities, such as sitting and changing posture, as well as standing position. It comprises a total of 14 items, each of which can be scored up to 56 points by measuring the score with 0–4 points. 2.3.2. FAC The FAC is a functional walking test for evaluating the ambulation ability, which is a complicated balance task. It shows high reliability, predictive validity, and good responsiveness in patients with hemiparesis after stroke [26]. Regardless of the use of an assistive device, the gait function is classified into six categories according to the degree of assistance and independence. 2.3.3. MI To exclude the effects of motor impairment on balance and ambulation in the patients after stroke as much as possible, we selected patients with MRC grade 4 or higher of the affected lower extremity and we confirmed that the MI in each subgroup was comparable. The MI is a motor impairment-based measurement in patients with stroke developed by Demeurisse et al. in 1980 [27]. The validity and reliability of the MI have been reported to be high in patients with stroke [28]. The ordinal 6-point MRC scale is used for evaluating the maximal muscle strength of the upper and lower extremities. The measured MRC scale is converted and summed to a modified weighted score, with a total score ranging from 0 (no movement) to 100 (normal strength). 2.4. Statistical analysis
Fig. 1. Flow chart of patient enrollment.
Statistical analysis was performed using the Statistical Package for the Social Sciences version 18.0 (IBM Co., Armonk, NY, USA). Chi-square tests were performed to compare the categorical variables, such as sex, location, and type of brain lesions. Nonparametric statistics, the Kruskal-Wallis test, was used to identify
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx Table 1 Equation to calculate the upper limit of the normal range for SSEP latency [24] Suppose H = (height in cm) 161.06, B = ((age) 20)2 – 1169.6, K_HB = 1.0154 + H2 * 0.0001501 + 2 * H * B * 4.634E07 + B2 * 1.679E08 Upper limit value of the standard P38 latency parameter UL_P38 = 37.75 + 0.1936 * H + 0.001752 * B + 2.5 * SQRT(K_HB * 1.5483)
H and B were calculated using subject factor, and K-HB is a coefficient obtained from predictor variables to calculate the standard error of prediction. UL_P38, upper limit of P38; SQRT, square root.
Table 2 General demographic and clinical characteristics of the patients. Characteristics
N = 110
Age (years) Sex (M/F)
61.50 ± 14.84 52/58 (47.3%/52.7%) 74/36 (67.3%/32.7%) 62/48 (56.4%/43.6%) 18/92 (16.4%/83.6%) 23.13 ± 6.14 160.68 ± 9.61 60.87 ± 12.00 88.71 ± 6.00 37.65 ± 16.58 1.96 ± 4.28 34.86 ± 14.11 3.08 ± 1.31 24.10 ± 20.27
Type of stroke (ischemic/hemorrhagic) Location of brain lesion (right/left) Involvement of thalamus (yes/no) MMSE Height (cm) Weight (kg) Average of Motricity Index for bilateral legs P38 Latency of SSEP – stimulated at the affected side (ms) P38 Amplitude of SSEP – stimulated at the affected side (lV) BBS FAC Interval between onset of stroke and evaluation of BBS, FAC (days) Interval between onset of stroke and evaluation of SSEP (days)
27.01 ± 20.15
Data are presented as means ± standard deviations, unless otherwise indicated. Fig. 2. An example of an abnormal tibial SSEP graph. A 65-year-old male with an ischemic stroke has a longer P1 or P38 latency than the upper limit of the normal value.
the difference in the continuous variables, such as BBS, FAC, and average of MI on the bilateral legs among the three groups. For variables with significant differences among the subgroups, posthoc analyses were performed using the Bonferroni correction method. SSEP latency and amplitude were analyzed using the Mann-Whitney test to identify the differences between the groups. The statistical significance of the Chi-square, Kruskal-Wallis, and Mann-Whitney tests was set at P < 0.05. 3. Results A total of 110 patients were enrolled (Table 2); the mean age was 61.5 ± 14.84 years, and 52 patients were male. Seventy-four patients had ischemic infarction and 36 had hemorrhagic infarction. The lesions were located on the right side in 62 and on the left side in 48 patients. There was thalamic involvement in 18 cases. The mean MMSE score was 23.13 ± 6.14 and the mean height was 160.68 ± 9.61 cm. The mean MI for the bilateral legs was 88. 71 ± 6.00. The duration from stroke onset to SSEP evaluation averaged 33.30 ± 30.44 days. The mean SSEP latency measured in the affected lower limb was 37.65 ± 16.58 ms and the mean SSEP amplitude was 1.96 ± 4.28 mV. The mean BBS was 34.86 ± 14.11 and the mean FAC was 3.08 ± 1.31. Twenty-two patients were classified into the ‘normal SSEP’ group (group 1), 71 in the ‘abnormal SSEP’ (group 2) and 17 in the ‘no response SSEP’ (group 3). There was no difference in the general and clinical characteristics among the three groups, such as age, sex, height, type (ischemic or hemorrhagic), and location
of cerebral infarction (right or left). The incidence of thalamus involvement was higher in the ’abnormal SSEP’ and ’no response SSEP’ groups than that in the ’normal SSEP’ group, but the difference was not statistically significant (P = 0.241). The mean SSEP latency and amplitude were 40.84 ± 2.14 ms and 2.68 ± 2.40 mV in the ‘normal SSEP’ group and 45.69 ± 3.73 ms and 2.21 ± 5.06 m V in the ‘abnormal SSEP’ group. The average bilateral leg MI was 90.25 ± 7.87, 88.24 ± 5.88, 88.71 ± 2.91 in each group, respectively, with no significant difference in the muscle strength between the groups (Table 3). The BBS scores were 41.14 ± 14.62, 34.52 ± 12.47, and 28.18 ± 17.11 in each group, and the FAC scores were 3.86 ± 1.24, 2.97 ± 1.20, and 2.53 ± 1.46, respectively. Both the BBS and FAC scores were the highest in the ’normal SSEP’ group and the lowest in the ’no response SSEP’ group, and statistically significant differences were found between the groups (P = 0.012 for BBS, P = 0.004 for FAC) (Table 4). In addition, Bonferroni multiple comparison was performed to examine the differences between the BBS and FAC scores for each group classified by the SSEP latency. As a result, the BBS score was significantly different between the ’normal SSEP’ group and the ’abnormal SSEP’ group (P = 0.013) and between the ’normal SSEP’ group and the ’no response SSEP’ group (P = 0.015). However, no significant difference was found between the ’abnormal SSEP’ group and the ’no response SSEP’ group (P = 0.155) (Fig. 3). The FAC scores showed similar results as those of the BBS score in the group comparisons. There was a significant difference in the FAC score between the ’normal SSEP’ group and the ’abnormal SSEP’ group (P = 0.004) and between the ’normal SSEP’ group and the ’no response SSEP’ group (P = 0.006). However, there was no significant difference in the FAC score between the ’abnormal SSEP’ group and the ’no response SSEP’ group (P = 0.221) (Fig. 4).
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
Table 3 Comparison of demographic and clinical variables among the groups classified according to the SSEP findings. Characteristics
Normal SSEP group (group 1) (n = 22)
Abnormal SSEP group (group 2) (n = 71)
No response SSEP group (group 3) (n = 17)
P-value
Age (years) Sex (M/F) Type of stroke (ischemic/hemorrhagic) Location of brain lesion (right/left) Involvement of thalamus (yes/no) MMSE Height (cm) Weight (kg) P38 Latency of SSEP – stimulated at affected side (ms) P38 Amplitude of SSEP – stimulated at affected side (lV) Average of MI for bilateral leg Interval between onset of stroke and evaluation of BBS, FAC (days) Interval between onset of stroke and evaluation of SSEP (days)
61.05 ± 19.17 12/10 (54.5%/45.5%) 16/6 (72.7%/27.3%) 11/11 (50.0%/50.0%) 1/21 (4.5%/95.5%) 22.95 ± 5.46 161.64 ± 10.04 60.18 ± 13.99 40.84 ± 2.14
62.76 ± 13.05 30/41 (42.3%/57.7%) 48/23 (67.6%/32.4%) 42/29 (59.2%/40.8%) 14/57 (19.7%/80.3%) 23.41 ± 5.86 159.46 ± 9.27 60.27 ± 11.37 45.69 ± 3.73
56.82 ± 15.54 10/7 (58.8%/41.2%) 10/7 (58.8%/41.2%) 9/8 (52.9%/47.1%) 3/14 (17.6%/82.4%) 22.18 ± 8.13 164.53 ± 9.85 64.24 ± 11.98 –
0.197 0.351 0.653 0.716 0.241 0.823 0.153 0.479 0.000*
2.68 ± 2.40
2.21 ± 5.06
–
0.075
90.25 ± 7.87 20.04 ± 16.33
88.24 ± 5.88 25.09 ± 21.64
88.71 ± 2.91 25.17 ± 19.25
0.248 0.427
23.00 ± 16.63
27.91 ± 21.39
27.23 ± 19.40
0.344
Data are presented as means ± standard deviations, unless otherwise indicated. The P-value was derived from the Chi-square and Kruskal-Wallis tests (P < 0.05). *P-value < 0.05.
Table 4 Comparison of the BBS and FAC scores among the groups classified by the SSEP findings. Characteristics
Normal SSEP group (group 1) (n = 22)
Abnormal SSEP group (group 2) (n = 71)
No response SSEP group (group 3) (n = 17)
KruskalWallis
Pvalue
BBS FAC
41.14 ± 14.62 3.86 ± 1.24
34.52 ± 12.47 2.97 ± 1.20
28.18 ± 17.11 2.53 ± 1.46
8.878 11.087
0.012* 0.004*
Data are presented as means ± standard deviations. The P value was derived from the Chi-square and Kruskal-Wallis tests (P < 0.05). *P-value < 0.05.
Fig. 3. Distribution of the BBS score by SSEP latency groups. Using the KruskalWallis test and the Post-hoc Bonferroni’s test, the significance level of P < 0.0167 was determined as statistically significant. n.s. not significant difference between Group 2 and Group 3 (P = 0.155).
Fig. 4. Distribution of the FAC score by SSEP latency groups. Using the KruskalWallis test and the Post-hoc Bonferroni’s test, the significance level of P < 0.0167 was determined as statistically significant. n.s. not significant difference between Group 2 and Group 3 (P = 0.221).
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
4. Discussion Our study aimed to investigate the role of somatosensory deficit alone on the balance and gait ability in patients with supratentorial stroke after the acute phase. By distinguishing somatosensory and motor components, we confirmed that isolated somatosensory impairment has a negative effect on the balance and gait function in patients with stroke. Maintenance of upright posture is achieved through a central posture program that recognizes postural instability and coordinates limb movement by sensory feedback from visual, vestibular, muscular, and cutaneous origin [13]. Balance is the ability to maintain a Center of Mass (CoM) at the base of the support in a given environment, and body sway must be reduced to control adequate posture [29]. The main somatosensory tract used to maintain balance is the dorsal column-meniscus pathway, which is responsible for delivering sensory inputs, such as light touch, proprioception, and vibration to the primary somatosensory cortex [30]. According to Connell’s research [31], tactile sensation is impaired in 7–53% of patients with stroke and 34–64% is impaired in proprioception, but the severity of somatosensory loss may vary depending on the extent of the lesion. Cutaneous plantar sensation and ankle proprioception play a predominant role in detecting body sway during static standing posture [32]. Cutaneous sensory information, such as tactile, vibration, and pressure sensation comes through mechanoreceptors that are present in the glabrous skin of the foot sole. The shear force from the ground caused by postural sway elicits a change in pressure distribution and contact area under the foot [3]. Stimulation of cutaneous receptors triggers the action potential of the neuro-membrane, which rapidly transmits signals through the myelinated large fibers to the primary somatosensory cortex [33]. These sensory inputs provide feedback about the direction and amplitude of the body sway relative to the contact location, creating a ‘‘dynamometric map”, which triggers the muscular response of the lower limbs [34,35]. Watanabe and Okubo [36] reported increased tibial nerve discharge as a result of mechanical stimulation of the plantar mechanoreceptors in the foot in standing posture. Similarly, Wu and Chiang [3] identified the role of isolated cutaneous mechanoreceptors in postural reflex initiation and found that the latency of the lower extremity muscles using EMG is related to the cutaneous mechanoreceptors at the sole of the foot. In addition, some studies have shown that postural sway significantly increases when the somatosensory tactile input from the cutaneous receptors of the foot sole is disrupted [37,38]. Proprioception consists of a limb position sense of stationary position and kinesthesia sense of limb movement. Body sway means that CoM moves relative to the foot in a static posture, which induces stretching of the muscles and tendons of the lower extremities with various velocity, thereby activating proprioceptive receptors [39]. This proprioceptive feedback provides information of the equilibrium state to maintain a static posture in external perturbation [40]. Many studies have reported a positive correlation between impaired ankle proprioception and balance in stroke patients. Niam et al. [41] reported a higher postural sway calculated by the Center of Pressure (COP) and a lower BBS score in patients with impaired ankle proprioception compared to those with intact one. These findings are in line with those of Keenan et al. [42] and Lin [43]. As one of the methods for assessing somatosensory impairment, SSEP is an effective tool to objectively quantify the damage to the dorsal column-medial lemniscus pathway. The SSEP latency is affected by the examiner’s technique, room temperature, and patient’s physiologic factors, such as age, height, and gender [44]. Shagass and Schwartz [23] examined the association between
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age and tibial SSEP components and found that the latency and amplitude of SSEP increased with age in the range of 15–80 years. Lüders et al. [45] also reported a significant increase in SSEP latency with increased age. Lastimosa et al. [46] found height significantly affects the tibial SSEP latency. Romani et al. [47] also reported similar results, showing that SSEP latency increases with the subject’s height at a rate of about 0.16–0.18 ms per cm. In a study that considered gender differences, Allison et al. [48] found that the peak latency was significantly prolonged in men compared to that in women. However, most SSEP studies considering physiologic factors analyzed the contribution of each variable using only simple regression [49,50]. Multiple regression analyzes for height, age, and/or gender were performed in only few studies, but were insufficient to make suggestions for upper or lower limits of the normal range [51]. Miura et al. [24] performed multiple regression analysis on the effect of physical indices on the tibial SSEP and proposed a standard value for the tibial SSEP components. The SSEP latency of the tibial nerve is best explained by two factors: height and age, except that N30 latency was affected by gender. Therefore, in this study, we considered the subject’s physiologic conditions in determining the degree of somatosensory deficit through SSEP. Some authors have measured tibial SSEP to identify the functional status of the lower extremities. Yoon et al. [52] reported that the sensory function at baseline is closely related to gait performance, and that the ’normal SSEP’ group had better gait parameters than the ‘abnormal SSEP’ group. Hwang et al. [22] reported that the ‘no response SSEP’ group showed lower BBS and FAC scores than those of the ‘normal’ and ‘abnormal SSEP’ groups. However, there was a clear difference from this study in that the abnormality of SSEP latency in patients with various demographics was determined using the uniform cut off value derived from previous researches that studied the standard value of SSEP. In our study, we overcame many of the problems that were not considered in previous studies on rehabilitation of somatosensory deficit. We measured the tibial SSEP focusing on the lower extremities and used a standard equation including the height and age proposed by Miura et al. [24] to determine the abnormal criteria for SSEP latency. The use of individual SSEP latency criteria by taking into account the height and age is different from previous studies using simple cut off values. As shown in Figs. 3 and 4, our results can be thought of as using the abnormality criteria of individual SSEP latency, which clearly distinguishes between ‘normal’ and ‘abnormal SSEP’ groups. By considering the physical indices of patients with stroke, the individual cut-off point of SSEP latency was clinically useful in that it accurately reflected the actual abnormalities of the SSEP. Furthermore, factors determining the functional level include the motor component as well as the somatosensory system. Therefore, it has a significant meaning that our study confirms the effect of isolated somatosensory system on the functional gait and balance ability in patients with comparable lower extremity muscle strength. Finally, our study included a total of 110 patients, which, to the best of our knowledge, is the largest cohort among those in studies using SSEP in patients with stroke. This study also has some limitations. SSEP parameters such as latency and amplitude, balance, and ambulation ability may change over time, because this was a cross-sectional study. In future research, we propose that the change should be identified by serial electrophysiologic tests and functional status evaluations, taking into account the physiological recovery period of the tissues. 5. Conclusion Our study revealed that isolated somatosensory impairment has a negative effect on the balance and gait ability in patients with supratentorial stroke after the acute phase.
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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Clinical study
Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase? Minsun Kim a, Hyun Haeng Lee a,⇑, Jongmin Lee a,b,⇑ a b
Department of Rehabilitation Medicine, Konkuk University School of Medicine and Konkuk University Medical Center, Seoul, South Korea Research Institute of Medical Science, Konkuk University School of Medicine, Seoul, South Korea
a r t i c l e
i n f o
Article history: Received 9 December 2019 Accepted 27 January 2020 Available online xxxx Keywords: Balance Gait Ambulation Sensory Somatosensory-evoked potential Stroke
a b s t r a c t Balance and ambulation are the result of a multicomponent control process through the interaction of the sensory and motor information. Despite the clinical relevance of the somatosensory system, its role has not drawn much attention from clinical researchers in that motor impairment is considered a major cause of dysfunction. There is little research on how somatosensory impairment alone affects functional disability after stroke. The purpose of this study was to investigate the effects of isolated somatosensory deficit on the balance and ambulation ability in patients with stroke. P38 latency of the SSEP was used to evaluate the integrity of the dorsal column-medial lemniscus pathway and the SSEP reference value was derived from the formula considering individual height and age. According to the SSEP latency, subjects were classified into ’normal’, ’abnormal’, and ’no response’ group. A total of 110 supratentorial stroke patients with at least grade 4 of the Medical Research Council scale of lower extremity on the affected side were enrolled. Berg balance scale (BBS) and functional ambulatory categories (FAC) showed significant differences among the groups (P < 0.05). In post-hoc analysis, the BBS and FAC was significantly different between the ’normal’ and ’abnormal SSEP’ group (P = 0.013 for BBS, P = 0.004 for FAC) and the ’normal’ and ’no response SSEP’ group (P = 0.015 for BBS, P = 0.006 for FAC). We found that isolated somatosensory impairment has a negative effect on the balance and ambulation ability in patients with supratentorial stroke after the acute phase. Ó 2020 Published by Elsevier Ltd.
1. Introduction Balance and ambulation are the result of a multicomponent control process through the interaction of the sensory input and motor output [1]. Balance is achieved through body and head movement strategies that recognize the disruption of the center of gravity due to external disturbances and the forces generated internally during voluntary movement or posture, such as walking and posture [2]. Despite the clinical relevance of the somatosensory system [3,4] its role has not drawn much attention from clinical researchers in that motor impairment is considered a major cause of dysfunction [5,6]. Somatosensory impairment has been reported to occur in over half of the patients with stroke [7,8] and it cause various problems such as inappropriate object recognition and manipulation [9], failure to avoid of danger with the limbs [10], and difficulty in balance control [11]. In particular, bal⇑ Corresponding authors at: Department of Rehabilitation Medicine, Konkuk University School of Medicine and Konkuk University Medical Center, 120-1 Neungdong-ro, Hwayang-dong, Gwangjin-gu, Seoul 05030, South Korea. E-mail addresses: [email protected] (H.H. Lee), [email protected] (J. Lee).
ance and ambulation function are the main determinants of independence of daily living performance, which is crucial for improving overall functioning and returning to society [12]. Locomotion control can be modulated by sensory information through the somatosensory, visual, and vestibular systems [13]. Stroke can affect all three types of sensory input, among which the incidence of somatosensory impairment is particularly high [14,15]. Sensory impairment after stroke is usually evaluated by clinical examinations and somatosensory-evoked potential (SSEP). However, clinical measurements were limited due to the sensitivity and reliability issues of the examiners and subjects [16]. Recently, SSEP has been widely used as a method for objectively assessing the damage to the dorsal column–medial lemniscus pathway of the somatosensory nerves [17,18]. In patients after stroke, the locomotion functions are affected by the motor component as well as the somatosensory system [19]. Previous studies have attempted to determine the effects on balance and gait by simultaneously considering motor and sensory components, and reported that the presence of a combined motor-evoked potential and SSEP response in the lower extremities is significantly associated with functional locomotion [20,21].
https://doi.org/10.1016/j.jocn.2020.01.084 0967-5868/Ó 2020 Published by Elsevier Ltd.
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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However, little research has been conducted on the effects of isolated somatosensory dysfunction on the functional ability in patients with stroke [22]. Therefore, our study sought to control as many factors as possible that could affect balance and ambulation, and determine the influence of the isolated somatosensory deficit. The aim of this study was to investigate the effect of isolated somatosensory deficit on the balance and ambulation in patients with supratentorial stroke after the acute phase using SSEP. 2. Methods 2.1. Study design and subjects We screened the records of 1797 patients admitted to the Department of Rehabilitation Medicine of a university hospital after the acute phase of stroke from January 2006 to August 2019. The lesion location and type of stroke was confirmed by brain computerized tomography (CT) or magnetic resonance imaging (MRI). The inclusion criteria were as follows: patients with only supratentorial brain lesions, who had SSEP assessed after at least 2 weeks post-stroke, who had at least grade 4 on the Medical Research Council (MRC) scale of lower extremity muscle strength on the affected side, including the hip flexor, knee extensor, and ankle dorsiflexor, and who ambulated independently before the stroke. The exclusion criteria were patients with previous symptomatic strokes, history of traumatic brain injury, multiple brain lesions, lower extremity peripheral neuropathy confirmed by electrophysiologic studies, hemineglect, visual field defects, vestibular dysfunction, or spasticity (Fig. 1). 2.2. SSEP method The SSEP was performed to determine the integrity of the dorsal column–medial lemniscus pathway of the somatosensory nervous system after transfer to the rehabilitation department. The Medelec Synergy EMG (VIASYS Healthcare, UK) was used for SSEP measurement. Subjects were positioned in the supine position. The environmental temperature was controlled at 22 °C–28 °C. The posterior tibial nerve was stimulated with rod electrode. The cathode was placed 1–2 cm distal to and posterior to the medial malleolus. The anode was placed 2–3 cm distal to the cathode. The stimulus intensity was adjusted to produce either slight plantar flexion of the great toe or cupping of the sole of the foot. At least 200 stimuli were repeated at a frequency of 3 times per second
and the responses were averaged. The process was repeated 2–3 times in ankle joint of each lower extremity. Using the International 10–20 system, the active electrode was placed on Cz0 , 2 cm behind Cz, and the reference electrode was placed on Fpz, midfrontal point. SSEP latency (named as P1 or P38) referred to the initial positive peak following stimulus onset and indicated the average peak latency of the predominant waveform located at approximately 38 msec. SSEP components, such as latency and amplitude, can be significantly affected by the subjects’ physiologic factors [23]. Considering this, the abnormality criteria for SSEP latency was based on the equation that considers individual height and age, as proposed by Miura et al. [24] (Table 1). Patients with an SSEP latency lower than the upper limit of normal value were classified into the ‘normal SSEP’ group (group 1), and those with equal to or greater than the upper limit of normal value were classified into the ‘abnormal SSEP’ group (group 2) (Fig. 2). Those where a peak could not be identified due to distortion of the graph were classified in the ‘no response SSEP’ group (group 3). 2.3. Clinical assessments The Berg balance scale (BBS), functional ambulatory categories (FACs), Motricity Index (MI), and Mini-Mental State Examination (MMSE) were evaluated in a few days with SSEP measurement. In this study, the BBS and FACs were the primary outcomes to assess the balance and ambulation ability of post-stroke patients. 2.3.1. BBS The BBS was used to assess the patient’s functional balance ability. It is a tool for evaluating the dynamic and static balance developed by Catherine Berg in 1989 and has been shown to have high reliability and validity in patients with stroke [25]. Unlike other balance assessment tools, BBS consists of items related to daily activities, such as sitting and changing posture, as well as standing position. It comprises a total of 14 items, each of which can be scored up to 56 points by measuring the score with 0–4 points. 2.3.2. FAC The FAC is a functional walking test for evaluating the ambulation ability, which is a complicated balance task. It shows high reliability, predictive validity, and good responsiveness in patients with hemiparesis after stroke [26]. Regardless of the use of an assistive device, the gait function is classified into six categories according to the degree of assistance and independence. 2.3.3. MI To exclude the effects of motor impairment on balance and ambulation in the patients after stroke as much as possible, we selected patients with MRC grade 4 or higher of the affected lower extremity and we confirmed that the MI in each subgroup was comparable. The MI is a motor impairment-based measurement in patients with stroke developed by Demeurisse et al. in 1980 [27]. The validity and reliability of the MI have been reported to be high in patients with stroke [28]. The ordinal 6-point MRC scale is used for evaluating the maximal muscle strength of the upper and lower extremities. The measured MRC scale is converted and summed to a modified weighted score, with a total score ranging from 0 (no movement) to 100 (normal strength). 2.4. Statistical analysis
Fig. 1. Flow chart of patient enrollment.
Statistical analysis was performed using the Statistical Package for the Social Sciences version 18.0 (IBM Co., Armonk, NY, USA). Chi-square tests were performed to compare the categorical variables, such as sex, location, and type of brain lesions. Nonparametric statistics, the Kruskal-Wallis test, was used to identify
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx Table 1 Equation to calculate the upper limit of the normal range for SSEP latency [24] Suppose H = (height in cm) 161.06, B = ((age) 20)2 – 1169.6, K_HB = 1.0154 + H2 * 0.0001501 + 2 * H * B * 4.634E07 + B2 * 1.679E08 Upper limit value of the standard P38 latency parameter UL_P38 = 37.75 + 0.1936 * H + 0.001752 * B + 2.5 * SQRT(K_HB * 1.5483)
H and B were calculated using subject factor, and K-HB is a coefficient obtained from predictor variables to calculate the standard error of prediction. UL_P38, upper limit of P38; SQRT, square root.
Table 2 General demographic and clinical characteristics of the patients. Characteristics
N = 110
Age (years) Sex (M/F)
61.50 ± 14.84 52/58 (47.3%/52.7%) 74/36 (67.3%/32.7%) 62/48 (56.4%/43.6%) 18/92 (16.4%/83.6%) 23.13 ± 6.14 160.68 ± 9.61 60.87 ± 12.00 88.71 ± 6.00 37.65 ± 16.58 1.96 ± 4.28 34.86 ± 14.11 3.08 ± 1.31 24.10 ± 20.27
Type of stroke (ischemic/hemorrhagic) Location of brain lesion (right/left) Involvement of thalamus (yes/no) MMSE Height (cm) Weight (kg) Average of Motricity Index for bilateral legs P38 Latency of SSEP – stimulated at the affected side (ms) P38 Amplitude of SSEP – stimulated at the affected side (lV) BBS FAC Interval between onset of stroke and evaluation of BBS, FAC (days) Interval between onset of stroke and evaluation of SSEP (days)
27.01 ± 20.15
Data are presented as means ± standard deviations, unless otherwise indicated. Fig. 2. An example of an abnormal tibial SSEP graph. A 65-year-old male with an ischemic stroke has a longer P1 or P38 latency than the upper limit of the normal value.
the difference in the continuous variables, such as BBS, FAC, and average of MI on the bilateral legs among the three groups. For variables with significant differences among the subgroups, posthoc analyses were performed using the Bonferroni correction method. SSEP latency and amplitude were analyzed using the Mann-Whitney test to identify the differences between the groups. The statistical significance of the Chi-square, Kruskal-Wallis, and Mann-Whitney tests was set at P < 0.05. 3. Results A total of 110 patients were enrolled (Table 2); the mean age was 61.5 ± 14.84 years, and 52 patients were male. Seventy-four patients had ischemic infarction and 36 had hemorrhagic infarction. The lesions were located on the right side in 62 and on the left side in 48 patients. There was thalamic involvement in 18 cases. The mean MMSE score was 23.13 ± 6.14 and the mean height was 160.68 ± 9.61 cm. The mean MI for the bilateral legs was 88. 71 ± 6.00. The duration from stroke onset to SSEP evaluation averaged 33.30 ± 30.44 days. The mean SSEP latency measured in the affected lower limb was 37.65 ± 16.58 ms and the mean SSEP amplitude was 1.96 ± 4.28 mV. The mean BBS was 34.86 ± 14.11 and the mean FAC was 3.08 ± 1.31. Twenty-two patients were classified into the ‘normal SSEP’ group (group 1), 71 in the ‘abnormal SSEP’ (group 2) and 17 in the ‘no response SSEP’ (group 3). There was no difference in the general and clinical characteristics among the three groups, such as age, sex, height, type (ischemic or hemorrhagic), and location
of cerebral infarction (right or left). The incidence of thalamus involvement was higher in the ’abnormal SSEP’ and ’no response SSEP’ groups than that in the ’normal SSEP’ group, but the difference was not statistically significant (P = 0.241). The mean SSEP latency and amplitude were 40.84 ± 2.14 ms and 2.68 ± 2.40 mV in the ‘normal SSEP’ group and 45.69 ± 3.73 ms and 2.21 ± 5.06 m V in the ‘abnormal SSEP’ group. The average bilateral leg MI was 90.25 ± 7.87, 88.24 ± 5.88, 88.71 ± 2.91 in each group, respectively, with no significant difference in the muscle strength between the groups (Table 3). The BBS scores were 41.14 ± 14.62, 34.52 ± 12.47, and 28.18 ± 17.11 in each group, and the FAC scores were 3.86 ± 1.24, 2.97 ± 1.20, and 2.53 ± 1.46, respectively. Both the BBS and FAC scores were the highest in the ’normal SSEP’ group and the lowest in the ’no response SSEP’ group, and statistically significant differences were found between the groups (P = 0.012 for BBS, P = 0.004 for FAC) (Table 4). In addition, Bonferroni multiple comparison was performed to examine the differences between the BBS and FAC scores for each group classified by the SSEP latency. As a result, the BBS score was significantly different between the ’normal SSEP’ group and the ’abnormal SSEP’ group (P = 0.013) and between the ’normal SSEP’ group and the ’no response SSEP’ group (P = 0.015). However, no significant difference was found between the ’abnormal SSEP’ group and the ’no response SSEP’ group (P = 0.155) (Fig. 3). The FAC scores showed similar results as those of the BBS score in the group comparisons. There was a significant difference in the FAC score between the ’normal SSEP’ group and the ’abnormal SSEP’ group (P = 0.004) and between the ’normal SSEP’ group and the ’no response SSEP’ group (P = 0.006). However, there was no significant difference in the FAC score between the ’abnormal SSEP’ group and the ’no response SSEP’ group (P = 0.221) (Fig. 4).
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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Table 3 Comparison of demographic and clinical variables among the groups classified according to the SSEP findings. Characteristics
Normal SSEP group (group 1) (n = 22)
Abnormal SSEP group (group 2) (n = 71)
No response SSEP group (group 3) (n = 17)
P-value
Age (years) Sex (M/F) Type of stroke (ischemic/hemorrhagic) Location of brain lesion (right/left) Involvement of thalamus (yes/no) MMSE Height (cm) Weight (kg) P38 Latency of SSEP – stimulated at affected side (ms) P38 Amplitude of SSEP – stimulated at affected side (lV) Average of MI for bilateral leg Interval between onset of stroke and evaluation of BBS, FAC (days) Interval between onset of stroke and evaluation of SSEP (days)
61.05 ± 19.17 12/10 (54.5%/45.5%) 16/6 (72.7%/27.3%) 11/11 (50.0%/50.0%) 1/21 (4.5%/95.5%) 22.95 ± 5.46 161.64 ± 10.04 60.18 ± 13.99 40.84 ± 2.14
62.76 ± 13.05 30/41 (42.3%/57.7%) 48/23 (67.6%/32.4%) 42/29 (59.2%/40.8%) 14/57 (19.7%/80.3%) 23.41 ± 5.86 159.46 ± 9.27 60.27 ± 11.37 45.69 ± 3.73
56.82 ± 15.54 10/7 (58.8%/41.2%) 10/7 (58.8%/41.2%) 9/8 (52.9%/47.1%) 3/14 (17.6%/82.4%) 22.18 ± 8.13 164.53 ± 9.85 64.24 ± 11.98 –
0.197 0.351 0.653 0.716 0.241 0.823 0.153 0.479 0.000*
2.68 ± 2.40
2.21 ± 5.06
–
0.075
90.25 ± 7.87 20.04 ± 16.33
88.24 ± 5.88 25.09 ± 21.64
88.71 ± 2.91 25.17 ± 19.25
0.248 0.427
23.00 ± 16.63
27.91 ± 21.39
27.23 ± 19.40
0.344
Data are presented as means ± standard deviations, unless otherwise indicated. The P-value was derived from the Chi-square and Kruskal-Wallis tests (P < 0.05). *P-value < 0.05.
Table 4 Comparison of the BBS and FAC scores among the groups classified by the SSEP findings. Characteristics
Normal SSEP group (group 1) (n = 22)
Abnormal SSEP group (group 2) (n = 71)
No response SSEP group (group 3) (n = 17)
KruskalWallis
Pvalue
BBS FAC
41.14 ± 14.62 3.86 ± 1.24
34.52 ± 12.47 2.97 ± 1.20
28.18 ± 17.11 2.53 ± 1.46
8.878 11.087
0.012* 0.004*
Data are presented as means ± standard deviations. The P value was derived from the Chi-square and Kruskal-Wallis tests (P < 0.05). *P-value < 0.05.
Fig. 3. Distribution of the BBS score by SSEP latency groups. Using the KruskalWallis test and the Post-hoc Bonferroni’s test, the significance level of P < 0.0167 was determined as statistically significant. n.s. not significant difference between Group 2 and Group 3 (P = 0.155).
Fig. 4. Distribution of the FAC score by SSEP latency groups. Using the KruskalWallis test and the Post-hoc Bonferroni’s test, the significance level of P < 0.0167 was determined as statistically significant. n.s. not significant difference between Group 2 and Group 3 (P = 0.221).
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
4. Discussion Our study aimed to investigate the role of somatosensory deficit alone on the balance and gait ability in patients with supratentorial stroke after the acute phase. By distinguishing somatosensory and motor components, we confirmed that isolated somatosensory impairment has a negative effect on the balance and gait function in patients with stroke. Maintenance of upright posture is achieved through a central posture program that recognizes postural instability and coordinates limb movement by sensory feedback from visual, vestibular, muscular, and cutaneous origin [13]. Balance is the ability to maintain a Center of Mass (CoM) at the base of the support in a given environment, and body sway must be reduced to control adequate posture [29]. The main somatosensory tract used to maintain balance is the dorsal column-meniscus pathway, which is responsible for delivering sensory inputs, such as light touch, proprioception, and vibration to the primary somatosensory cortex [30]. According to Connell’s research [31], tactile sensation is impaired in 7–53% of patients with stroke and 34–64% is impaired in proprioception, but the severity of somatosensory loss may vary depending on the extent of the lesion. Cutaneous plantar sensation and ankle proprioception play a predominant role in detecting body sway during static standing posture [32]. Cutaneous sensory information, such as tactile, vibration, and pressure sensation comes through mechanoreceptors that are present in the glabrous skin of the foot sole. The shear force from the ground caused by postural sway elicits a change in pressure distribution and contact area under the foot [3]. Stimulation of cutaneous receptors triggers the action potential of the neuro-membrane, which rapidly transmits signals through the myelinated large fibers to the primary somatosensory cortex [33]. These sensory inputs provide feedback about the direction and amplitude of the body sway relative to the contact location, creating a ‘‘dynamometric map”, which triggers the muscular response of the lower limbs [34,35]. Watanabe and Okubo [36] reported increased tibial nerve discharge as a result of mechanical stimulation of the plantar mechanoreceptors in the foot in standing posture. Similarly, Wu and Chiang [3] identified the role of isolated cutaneous mechanoreceptors in postural reflex initiation and found that the latency of the lower extremity muscles using EMG is related to the cutaneous mechanoreceptors at the sole of the foot. In addition, some studies have shown that postural sway significantly increases when the somatosensory tactile input from the cutaneous receptors of the foot sole is disrupted [37,38]. Proprioception consists of a limb position sense of stationary position and kinesthesia sense of limb movement. Body sway means that CoM moves relative to the foot in a static posture, which induces stretching of the muscles and tendons of the lower extremities with various velocity, thereby activating proprioceptive receptors [39]. This proprioceptive feedback provides information of the equilibrium state to maintain a static posture in external perturbation [40]. Many studies have reported a positive correlation between impaired ankle proprioception and balance in stroke patients. Niam et al. [41] reported a higher postural sway calculated by the Center of Pressure (COP) and a lower BBS score in patients with impaired ankle proprioception compared to those with intact one. These findings are in line with those of Keenan et al. [42] and Lin [43]. As one of the methods for assessing somatosensory impairment, SSEP is an effective tool to objectively quantify the damage to the dorsal column-medial lemniscus pathway. The SSEP latency is affected by the examiner’s technique, room temperature, and patient’s physiologic factors, such as age, height, and gender [44]. Shagass and Schwartz [23] examined the association between
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age and tibial SSEP components and found that the latency and amplitude of SSEP increased with age in the range of 15–80 years. Lüders et al. [45] also reported a significant increase in SSEP latency with increased age. Lastimosa et al. [46] found height significantly affects the tibial SSEP latency. Romani et al. [47] also reported similar results, showing that SSEP latency increases with the subject’s height at a rate of about 0.16–0.18 ms per cm. In a study that considered gender differences, Allison et al. [48] found that the peak latency was significantly prolonged in men compared to that in women. However, most SSEP studies considering physiologic factors analyzed the contribution of each variable using only simple regression [49,50]. Multiple regression analyzes for height, age, and/or gender were performed in only few studies, but were insufficient to make suggestions for upper or lower limits of the normal range [51]. Miura et al. [24] performed multiple regression analysis on the effect of physical indices on the tibial SSEP and proposed a standard value for the tibial SSEP components. The SSEP latency of the tibial nerve is best explained by two factors: height and age, except that N30 latency was affected by gender. Therefore, in this study, we considered the subject’s physiologic conditions in determining the degree of somatosensory deficit through SSEP. Some authors have measured tibial SSEP to identify the functional status of the lower extremities. Yoon et al. [52] reported that the sensory function at baseline is closely related to gait performance, and that the ’normal SSEP’ group had better gait parameters than the ‘abnormal SSEP’ group. Hwang et al. [22] reported that the ‘no response SSEP’ group showed lower BBS and FAC scores than those of the ‘normal’ and ‘abnormal SSEP’ groups. However, there was a clear difference from this study in that the abnormality of SSEP latency in patients with various demographics was determined using the uniform cut off value derived from previous researches that studied the standard value of SSEP. In our study, we overcame many of the problems that were not considered in previous studies on rehabilitation of somatosensory deficit. We measured the tibial SSEP focusing on the lower extremities and used a standard equation including the height and age proposed by Miura et al. [24] to determine the abnormal criteria for SSEP latency. The use of individual SSEP latency criteria by taking into account the height and age is different from previous studies using simple cut off values. As shown in Figs. 3 and 4, our results can be thought of as using the abnormality criteria of individual SSEP latency, which clearly distinguishes between ‘normal’ and ‘abnormal SSEP’ groups. By considering the physical indices of patients with stroke, the individual cut-off point of SSEP latency was clinically useful in that it accurately reflected the actual abnormalities of the SSEP. Furthermore, factors determining the functional level include the motor component as well as the somatosensory system. Therefore, it has a significant meaning that our study confirms the effect of isolated somatosensory system on the functional gait and balance ability in patients with comparable lower extremity muscle strength. Finally, our study included a total of 110 patients, which, to the best of our knowledge, is the largest cohort among those in studies using SSEP in patients with stroke. This study also has some limitations. SSEP parameters such as latency and amplitude, balance, and ambulation ability may change over time, because this was a cross-sectional study. In future research, we propose that the change should be identified by serial electrophysiologic tests and functional status evaluations, taking into account the physiological recovery period of the tissues. 5. Conclusion Our study revealed that isolated somatosensory impairment has a negative effect on the balance and gait ability in patients with supratentorial stroke after the acute phase.
Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084
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M. Kim et al. / Journal of Clinical Neuroscience xxx (xxxx) xxx
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Please cite this article as: M. Kim, H. H. Lee and J. Lee, Does isolated somatosensory impairment affect the balance and ambulation of patients with supratentorial stroke after the acute phase?, Journal of Clinical Neuroscience, https://doi.org/10.1016/j.jocn.2020.01.084