Influence of Lower Extremity Impairment and Trunk Control on Postural Control and Functional Mobility in Children with Spastic Cerebral Palsy

DOI: https://doi.org/10.21203/rs.3.rs-2088670/v1

Abstract

Purpose

To determine influence of lower extremity impairment and trunk control on postural control and functional mobility in children with spastic Cerebral Palsy (CP).

Methods

25 children with between the ages of 6–17 were evaluated. Gross Motor Function Measure (GMFM) E Section, Modified Timed Up and Go Test (TUG), Trunk Impairment Scale (TIS), Computerized Dynamic Posturography, Sensory Organization Test (SOT) were applied; lower limb’s range of movement (ROM) of joints were evaluated passively to all participants. Spasticity levels of lower limbs were evaluated.

Results

In children with CP, there were significant relationship between spasticity, ROM and trunk control and motor function capacity and composite balance score (p < 0,05). Impairments of the lower extremity in children with CP were related with balance responses (p < 0,05). (p < 0,05). TUG, and composite balance score tests were correlated with all sub-dimensions of TIS (p < 0,05). the results of univariate and multivariate regression analyses and TIS total were found to be independent risk factor of TUG and GMFM-E according to the univariate analyses (ß=-0.77, B:0.353 standard error: 0.061, p < 0.01; ß=0.809, B:3.806 standard error: 0.578 p < 0.045 respectively). According to the multivariate regression analyses, TIS dynamic, SOM and VEST were found predictors of mTUG, and ROM, TIS dynamic and coordination, VIS were found predictors of GMFM-E (p < 0.05).

Conclusion

Lower limb impairment and trunk control plays important role on postural control and functional mobility, therefore it is important including these parameters into the physiotherapy and rehabilitation aiming to improve functional mobility.

Introduction

Cerebral palsy (CP) is a neurodevelopmental condition caused by a non-progressive brain lesion occurs before, during, or shortly after birth resulted with posture and activity disturbance [1]. According to the population based observational studies, spastic type is the most common clinical type and nearly 80% of total CP population is classified as spastic type [2, 3].

Although the primary injury in CP is not progressive; together with muscle tone, postural disorders and movement deficiency, the functional deficiencies and severity of disability are progressive and the main problems [1, 4]. Among these problems, children with CP usually show weak postural control (PC) [5], which can briefly define as the ability to control the body in relation to the person’s base of support for maintenance of stability and orientation [6]. PC is a complex skill based on interaction between dynamic sensory-motor process [7]; motor processes including neuromuscular synergy responses, the sensory structure including the visual, vestibular and somatosensory systems [8]. Because of this complex interaction maintaining a stable posture, even during daily functional activities, is challenging [7]. Impairments on PC in children CP during static and dynamic activities are resulted by sensory deficits, musculoskeletal problems including decreasing joint range of motion (ROM), impaired muscle and biomechanical misalignment adversely affecting their performance of daily activities [9, 10]. In spastic CP, abnormal motor patterns and postural reaction, deficiencies in adjustment and balance reaction cause PC problems and with abnormal tone, affect physical development of the child negatively [11]. This dysfunction provokes limitations in motor skills that require balance, such as walking, and results in participation limitation in a wide range of daily living aspects including self-care, education, entertainment and social relationships [11]. Therefore, improvement of PC is one of the main goals in physical therapy interventions [9, 12] that being so, investigation of movement and PC objectively and revealing any pathology clearly is important to determine the appropriate treatment methods in CP and to understand the effectiveness of these methods. Evaluation of PC responses that play an important place in continuation of the daily living activities of children with CP with objective data and ensuring better understanding of PC mechanisms and synergies can provide clinical support to physiotherapy and rehabilitation interventions [8].

Considering the role of PC in the performance of motor skills and in the adaptation of an individual to changing environmental demands, it is important to understand how these factors interact in the CP population [7] as a consequence, the aims of this study were to reveal the influence of lower extremity impairment and trunk control on PC, balance and functional mobility in children with spastic CP and to investigate what factors cause the PC problems in children with spastic CP. We hypothesized that, there are relationships exist between PC, functional mobility capacity and lower extremity impairment.

Methods

This study was designed as a cross-sectional study and ethical approval was obtained from the Hacettepe University ethical committee (Decision no: HEK11/105) according to principles of the Declaration of Helsinki, and the parents of participant children gave written informed consent to participate.

Participants

Children with spastic CP aged 6–16 years were included in the study. Study size was identified as 20 children with CP after power analysis, 31 children included at the beginning, 4 of the children did not complete posturographic evaluation because of difficulty, 2 of them had been applied Botulinum-toxin injection and excluded from study. Finally, 25 children with spastic CP were completed the study. Inclusion criteria were: diagnosis of spastic CP, able to walk independently without any orthotics; not having cognitive impairment; not having vision problems and hearing loss. Children who underwent Botulinum toxin injections and/or surgical intervention for the musculoskeletal system in the past year, who were using any medication were excluded from study. None of participant was undergone to the posturographic study before. Demographic characteristics of children, including gender, height, weight was recorded. Children classified according to the Gross Motor Function Classification System (GMFCS). The characteristics of children with CP presented in Table 1.

Table 1

Characteristics of children with CP

Characteristics (n = 25)

Age (year) Mean ± SD

9.64 ± 4.73

Gender

Girl (n)

13 (52%)

Boy (n)

12 (48%)

GMFCS

Level I

13 (52%)

Level II

12 (48%)

Height (cm) Mean ± SD

128.16 ± 23.64

Weight (kg) X ± SD

31.12 ± 15.93

GMFCS: Gross Motor Function Classification System n: number, SD: standard deviation,

 

Posturographic Evaluation

Postural stability of participants was measured by Computerized Dynamic Posturography (CDP) (NeuroCom International, Inc., Clackamas, OR, USA), Smart Balance Master which has visual biofeedback on either a stable or unstable support surface and visual environment is used for assessment. With this technique, individual’s ability of use visual, vestibular, and somatosensory information can be evaluated. Smart Balance Master assesses a dynamic force plate with rotation capabilities to quantify the vertical forces exerted through the patient’s feet to measure center of gravity (COG) position and PC; and a dynamic visual surround to measure the patient’s use of visual information to maintain balance [13].

The Sensory Organization Test (SOT) protocol assesses postural balance abilities under six conditions in which visual, sensory, and proprioceptive inputs vary. During the SOT, information delivered to the patient’s eyes, feet and joints is effectively eliminated through calibrated ‘‘sway referencing’’ of the support surface and/or visual surround, which tilt to directly follow the patient’s antero-posterior body sway. An equilibrium-score determines the amount of the anteroposterior COG compared with maximal sway limits was calculated for each condition. A composite balance score (CBS) is subsequently calculated. The scores range from 0-100, higher values indicating better stability. The six different conditions were: SOT-1, stable surface, eyes open; SOT-2, stable surface, eyes closed; SOT-3, eyes open with sway referenced surrounded; SOT-4, eyes open with sway referenced surface; SOT-5, eyes closed with sway referenced surface; and SOT-6, eyes open, referenced surface and surround. SOT-1, SOT2, and SOT-3 are static conditions, while SOT-4, SOT-5, and SOT-6 are dynamic conditions. SOT-1-2 refer to patient’s ability to utilize input from the somatosensory system and maintain balance. SOT-1-4 give objective information about patient’s ability of the visual system to maintain balance. SOT-1-5 are identifying ability of using input from vestibular system. Two postural adjustment strategies were examined: relative movements of ankle (ankle strategy) or hip (hip strategy). A software program calculates an equilibrium score, which determines the success of the patient’s sway for each sensory condition. Each test condition was repeated three times, and the average of the three trials was used for data analysis [13].

Trunk Impairment Scale (Tis)

The trunk control of participants was evaluated using the TIS. The validity and reliability of TIS for patients with CP has been demonstrated. The TIS consists of three sub-sections: static balance, dynamic balance, and coordination. Task scores for each activity range from 0–2. The total score ranges from 0–23. Higher total scores indicate better trunk control in sitting posture [14].

Functional Mobility Assessment

The modified Timed Up and Go (mTUG) and Gross Motor Function Measure (GMFM) were used to assess functional mobility. The pediatric version of the mTUG was performed for functional mobility assessment. It records the time a child needs to stand up from a chair with foot contact, to walk three meter to a target, turn around and return to the chair and sit down. We performed three mTUG trials and calculated the mean time. Reliability and validity of the mTUG were shown [15].

The GMFM-88 is the most commonly used, valid and reliable measure to evaluate motor function in children with CP, that contains five sections and 88 items. The total score of the GMFM-88 is obtained by adding up the total points for each section. A total score or the scores of each section can be used separately. In this study, we used Section-E to measure walking function [16].

Lower Limb Impairment Assessment

Spasticity and limitations of ROM assessment of lower limb assessed. The measurements were made without clothing.

Modified Ashworth Scale (MAS) was used to evaluate spasticity of the gastrocnemius, soleus, hamstring, hip adductor and flexors muscles were evaluated bilaterally. The MAS is a commonly used scale for measuring muscle tone during passive movement with a 6-point scale: (0–4) The MAS is valid and reliable in children with CP [17, 18].

For ROM assessment, a universal goniometry which is valid and reliable in children with CP [19], was used in the evaluation of ROM and Kendall’s values were taken as reference and limitation values were recorded. The ankle dorsiflexion, plantar flexion, eversion and inversion; knee flexion and extension; hip flexion, extension, abduction, adduction, internal and external rotation movements were evaluated passively in the lower extremity.

Statistical Analysis:

Data analysis was completed using the statistical software program SPSS for Windows v.21.0 (SPSS Inc., Chicago, IL). The Shapiro-Wilk’s test was used to test normality. Data were expressed as means standard deviations. The analysis of the linear relationship was performed Spearman's correlation analysis. The statistical significance level was accepted as p < 0.05. Simple and multiple linear regression analysis (backward modeling) were carried out to determine the most important predictor(s) for explaining mTUG and GMFM-E variance.

Results

Twenty-five patients, consisting of 13 (52%) girls and 12 (48%) boys, with CP were included in the study. The mean age of the patients was 9.64 ± 4.73 years (range 6–16 years) (Table 1). The results of the SOT, trunk control and functional capacity are shown in Table 2, and results of lower limb impairments in Table 3.

Table 2

Results of Computarized Dynamic Posturography and Gait Capasity

 

Equilibrium Score

Strategy Score

 

Mean ± SD

Mean ± SD

Condition 1

83.32 ± 7.28

93.84 ± 3.50

Condition 2

82.22 ± 7.79

94.34 ± 2.79

Condition 3

72.46 ± 20.82

92.72 ± 2.79

Condition 4

63.25 ± 15.19

85.32 ± 5.38

Condition 5

45.02 ± 20.39

75.18 ± 9.60

Condition 6

43.45 ± 17.57

73.90 ± 11.25

Sensory Ratio Analysis

Somatosensory Ratio

97.77 ± 2.50

Visual Ratio

69.83 ± 26.48

Vestibular Ratio

46.93 ± 28.86

Visual Preferance

95.11 ± 5.46

Composite Equilibrium Score

57.92 ± 14.43

Functiomal Capasity

mTUG (s)

9.24 ± 1.64

GMFM-E

85.66 ± 16.86

Trunk Control (TIS)

TIS Static

6.60 ± 0.57

TIS Dynamic

6.92 ± 2.37

TIS Coordination

3.92 ± 0.99

TIS Total

17.44 ± 3.58

GMFM-E: Gross Motor Function Measure Section E, mTUG: modified timed up and go test, SD: standard deviation

 

Table 3

Lower limb impairment in children with CP

Joint

Passive Range of Movement (Degree)

Right Lower Extremity

Mean ± SD

Left Lower Extremity

Mean ± SD

Passive Range of Movement (Degree)

Ankle

Dorsiflexion

16.5 ± 2.32

15.92 ± 2.17

Plantar flexion

0

0

Inversion

0

0

Eversion

4.0 ± 1

4.0 ± 1

Knee

Flexion

0

0

Extantion

23.83 ± 2.93

22.72 ± 7.92

Hip

Flexion

0

0

Extantion

17.55 ± 5.91

18.27 ± 5.68

Abduktion

0

0

Adduktion

21.14 ± 2.86

22.74 ± 3.58

Internally rotation

0

0

Externally rotation

11.37 ± 2.30

11.43 ± 2.72

Spasticity Assessment (MAS 0–5)

Gastrocnemius

3.34 ± 0.65

3.28 ± 0.76

Soleus

1.84 ± 0.93

1.87 ± 0.91

Hamstrins

276 ± 0.38

2.57 ± 0.59

Hip flexor

1.97 ± 0.83

1.82 ± 0.71

Hip adductor

1.74 ± 0.75

1.76 ± 0.78

MAS: Modified Ashworth Scale, SD: standard deviation

 

Results Of Correlations

There was a significant relationship between static trunk control and displacement of the COG in the antero-posterior direction (r = 0.777, p < 0.01), as well as the lateral direction in SOT-2 (r = 0.680; p < 0.05) and between the static trunk control and displacement of the COG in the antero-posterior direction in SOT-4 (r = 0.7; p < 0.05). There was a significant relationship between the hip external rotation (r = 2, p < 0.05) and abduction limitations (right, r = 0.855 p < 0.01, r = 0.715, left p < 0.05) and hip adductors (r=- 0.657 p < 0.05) and flexors (r=-0.663 p < 0.05) and spasticity of hamstrings (r=-0.648 p < 0.05), and antero-posterior displacement of the COG in the SOT-5.

When spasticity and SOT strategy analyses were examined, a significant relationship was found between the spasticity of bilateral hamstring (r=-0.648; p < 0.05), soleus (r=-0.713 p < 0.05) and gastrocnemius (r=-0.716 p < 0.05) muscles and the SOT-1 strategy analysis.

There was a significant relationship between the hip external rotation (r = 1, p < 0.05) and extension limitations (r = 0.775 p < 0.05), and the SOT somatosensory ratio in the lower extremity.

There was a significant relationship between bilateral hip extension (r=-0.695 p < 0.059) and knee extension (r=-0.644 p < 0.05) limitations and spasticity of soleus (r=-0.794 p < 0.05), gastrocnemius (r=-0.657 p < 0,05). Bilateral hip extension (right r = 0.673 p < 0.05, r = 0.773, left p < 0.05) and hip abduction (r=-0.779 p < 0.05) limitations and bilateral hamstring (r = 0.735 p < 0, 05), gastrocnemius (r = 0.747 p < 0.05) and soleus (r = 0.814 p < 0.01) muscled were related with the mTUG tests.

A relationship was found between the ankle dorsiflexion passive joint limitation of the affected side and vestibular response (r=-0.828, p = 0.006), and between the hip external rotation and abduction passive joint limitations and VEST as well as the CBS (external rotation VEST r=-0.673, p < 0.05, CBS r=-0.676 p < 0.05; abduction VEST r=-0.758, p < 0.05; CBS r=-0.778, p < 0.05). A significant relationship was seen between the displacement of the COG towards lateral and hip flexors spasticity in the SOT-5 (r=-0.825, p < 0.01). TUG, and CBS tests were correlated with all sub-dimensions of TIS (p < 0,05) (Table 4).

Table 4

Correlations between the Trunk Impairment Scale and Sensory Organization Test

Sensory Organization Test

Trunk Impairment Scale

Static

Dynamic

Coordination

Total

r

P*

r

P*

r

P*

r

P*

Somatosensorial

0.130

0.431

-0.117

0.478

-0.165

0.3140

-0.119

0.472

Visual

0.211

0.197

0.435

< 0.01

0.404

< 0.05

0.431

< 0.01

Vestibular

0.213

0.193

0.210

0.2

0.179

0.275

0.217

0.185

Composite Balance Score

0.415

< 0.01

0.530

< 0.01

0.518

< 0.01

0.544

< 0.01

Modified Timed Up and Go Test

-0.641

0.016

-0.806

< 0.01

-0.590

0.008

-0.80

< 0.01

r: Spearman’s Rho. p: Spearmen Correlation Test

 

Table 5 shows the results of univariate and multivariate regression analyses and TIS total were found to be independent risk factor of TUG and GMFM-E according to the univariate analyses (ß=-0.77, B:-0.353 standard error: 0.061, p < 0.01; ß=0.809, B:3.806 standard error: 0.578 p < 0.045 respectively). According to the multivariate regression analyses, TIS dynamic, SOM and VEST were found predictors of mTUG, and ROM, TIS dynamic and coordination, VIS were found predictors of GMFM-E (p < 0.05).

Table 5

Results of regression analyses

Dependent variable

Independent variable

B

Std. Error

Beta

p

R2

mTUG

Simple linear regression

Constant

15.388

1.083

 

< 0.01

 

TIS Total

− .353

.061

− .770

< 0.01

0.593

Multiple linear regression (backward modeling)

Step 1

Constant

-26.115

25.688

 

.324

0.827

ROM

.383

.422

.119

.377

MAS

.077

.049

.402

.133

TIS Static

− .717

.627

− .253

.269

TIS Dynamic

− .261

.167

− .379

.137

TIS Coordination

.326

.326

.198

.332

Somatosensorial

.170

.102

.261

.114

Visual

− .006

.011

− .101

.565

Vestibular

− .010

.010

− .172

.353

Step 2

Constant

-25.029

25.123

 

.333

0.823

ROM

.321

.400

.100

.434

MAS

.082

.047

.431

.096

TIS Static

− .630

.597

− .222

.306

TIS Dynamic

− .284

.159

− .412

.093

TIS Coordination

.348

.318

.212

.288

Somatosensorial

.190

.095

.290

.061

Vestibular

− .014

.008

− .239

.101

Step 3

Constant

-5.803

7.305

 

.437

0.816

MAS

.073

.045

.379

.122

TIS Static

− .573

.587

− .202

.342

TIS Dynamic

− .325

.149

− .471

.043

TIS Coordination

.276

.302

.168

.372

Somatosensorial

.200

.093

.305

.045

Vestibular

− .016

.007

− .284

.035

Step 4

Constant

-4.386

7.109

 

.545

0.808

MAS

.045

.033

.237

.188

TIS Static

− .519

.581

− .183

.383

TIS Dynamic

− .329

.149

− .477

.039

SOM

.199

.092

.304

.045

VEST

− .018

.007

− .324

.011

Step 5

Constant

-2.131

6.611

 

.751

0.800

MAS

.047

.033

.245

.171

TIS Dynamic

− .412

.116

− .598

.002

Somatosensorial

.146

.070

.223

.047

Vestibular

− .017

.006

− .303

.014

Step 6

Constant

-2.303

6.768

 

.737

0.789

TIS dynamic

− .541

.073

− .785

.000

Somatosensorial

.166

.071

.254

.028

Vestibular

− .021

.006

− .361

.003

GMFM-E

Simple linear regression

Constant

19.283

10.274

 

.073

 

TIS Total

3.806

.578

.809

.000

0.654

Multiple linear regression (backward modeling)

Step 1

Constant

506.467

245.737

 

.056

0.850

ROM

-7.381

4.037

− .223

.086

MAS

.231

.465

.117

.627

TIS Static

9.097

5.996

.311

.149

TIS Dynamic

5.593

1.598

.789

.003

TIS Coordination

-3.246

3.121

− .192

.314

Somatosensorial

− .504

.976

− .075

.613

Visual

− .126

.101

− .197

.234

Vestibular

.024

.098

.041

.811

Step 2

Constant

525.323

226.652

 

.033

0.850

ROM

-7.839

3.471

− .237

.037

MAS

.198

.432

.100

.653

TIS Static

9.211

5.809

.315

.131

TIS Dynamic

5.487

1.494

.774

.002

TIS Coordination

-3.443

2.929

− .203

.256

Somatosensorial

− .395

.843

− .059

.645

Visual

− .110

.077

− .173

.170

Step 3

Constant

545.094

217.542

 

.022

0.848

ROM

-7.962

3.383

− .241

.030

TIS Static

9.176

5.680

.314

.124

TIS Dynamic

5.224

1.349

.737

.001

TIS Coordination

-4.338

2.130

− .256

.057

Somatosensorial

− .416

.823

− .062

.619

Visual

− .128

.065

− .201

.064

Step 4

Constant

512.333

203.569

 

.021

0.846

ROM

-7.940

3.316

− .240

.027

TIS Static

7.471

4.482

.256

.112

TIS Dynamic

5.400

1.277

.762

.0001

TIS Coordination

-4.168

2.061

− .246

.057

Visual

− .127

.063

− .199

.060

Step 5

Constant

490.822

212.004

 

.031

0.823

ROM

-6.924

3.402

− .209

.045

TIS Dynamic

6.927

.929

.977

.0001

TIS Coordination

-4.055

2.150

− .240

.074

Visual

− .165

.062

− .259

.014

GMFM-E: gross motor function measure E section, mTUG: Modifed Timed Up and Go Test, TIS: Trunk impairment scale.
B: unstandardized regression coefficient; Std. Error B: standardized error of Beta; ß: standardized regression coefficient; R2: coefficient of determination.

Discussion

According to our results, lower limb impairment and trunk control plays important role on PC and functional mobility in children with CP. The use of objective and valid evaluations in studies has become important with the increasing significance ascribed to evidence-based applications [20]. PC can be easily evaluated in an objective way by using the CDP that provides significant quantitative data on the vestibular, visual and somatosensory systems as gold standard and is important for the clinical evaluation of children [21].

When the CDP, SOT strategy analyzes' results were evaluated, the ankle movements, which the first movement pattern that the body applies to control its perpendicular status while the hip strategy is used for control in a more unstable state, in the majority of children with CP (n = 23) were found to be abnormal. Our results show that children with CP cannot adapt their body movements to changing environmental conditions and have poor PC. The use of the hip strategy when the ankle strategy is not effective results in increasing the risk of falls as it is inadequate in providing balance in unstable surfaces in children and also increases energy consumption [23].

The body's position in space can be maintained with the coordinated operation of these systems. Deficiencies in this system lead to disorders in PC strategies [23]. Inadequacies of the neural structures result in a disturbance of the order of muscle contradiction in the strategies, one of the most important PC disorders in children with CP. The results of current study show that children with CP have difficulties in maintaining balance in different positions. A significant proportion of children with CP showed impaired somatosensory information and anomalies in strategies in SOT-4 together with impaired balance between the hip and ankle strategies. According to studies, the somatosensory loss results in an increase in hip strategy even when the ankle strategy can be effective [24]. Wingert et al. reported bilateral proprioception loss in children with CP. Damages to the neural connections and sensory receptors also affect postural strategies [25]. Tedroff et al. found more variability in the muscle activation patterns in children with CP than children in the control group similar to our findings and emphasized that this is often found in distal muscles that require an ankle strategy [26]. In addition, they reported an anomaly of the strategies to be a general phenomenon in CP, independent of the complexity of motor skills. The postural strategy anomaly seen in all children with CP that participated in our study except one complies with this information. The strategy findings in our study conducted with CDP are similar to the results obtained by Tedroff et al. with the electromyographic method [26]. Findings in our study and others show that lesions that affect the motor cortex and the corticospinal tract such as seen in CP damage control of the distal leg muscles.

The TIS which evaluates the trunk movements in accordance with real life and therefore provides an important clinical data [14] was used in this study and the deficiency in trunk control is reported to cause activity limitations and participation restriction. It will also affect all activities involving mobility, and limit fields of daily living such as education and social communication [27]. When we compared the findings related to functional movement and the level of body effect, a significant relationship was observed between the all subscales and the total scores of TIS and mTUG. These data reveal the relationship between trunk effect and functionality, and the critical role of the trunk in the organization of postural reactions. Similar to our findings, Verheyden et al. revealed that trunk control measurements are related to balance, walking and functional skills and that the control of the body is an important indicator for daily living activities in various studies they have conducted [28]. This relationship between functional movement tests and trunk control is supported with studies showing that the body has a multi-layered role in the control of straight posture during walking [29]. Additionally, Balzer et al reported the trunk control is strongest predictor of the gait and correlation with mTUG [30], moreover, according to Cankarturan et al. trunk control is one of the predictors of functional mobility (GMFM-B) in non-ambulatory children with CP [31]; Kallem at al. investigated the relationship between trunk control and functionality in children with CP [27]; their study included both ambulatory and non-ambulatory children putting together with our findings, regardless to severity of CP, trunk control is one of strong predictor of functional mobility.

We concluded that the abduction and external rotation limitations of the affected lower extremity are associated with balance and vestibular responses. This suggests that the adduction and internal rotation position that is referred to as the general lower limb posture in children with CP, is one of the reasons of the balance problems in these children. The relationship of the ankle dorsiflexion limitation with vestibular responses can be associated with the impaired ankle strategy. The impairment in ankle biomechanical sequence created by CP could therefore change the strategy responses and creates a differentiation in the efficiency of the balance reactions. We found that hip flexion is associated with the displacement of the COG laterally in the SOT-5 where the eyes were closed and the support surface is moving. We think that, this effect may be one of the reasons underlying the weight transfer problems. The problem associated with the weight transfer appearing in the position where the visual effect was eliminated suggest not only a biomechanical problem, but also a sensory problem as described as Mishra et al. investigated relationship between functional mobility and sensory processing [32] and according to Jovellar-Isiegas et al., sensorial dysfunction affects participation into the life [33].

We found that the spasticity and ROM limitations in the hip region are associated with the proximal responses. This finding reveals the influence of the proximal effect in CP and the fact that the hip and the trunk are integrated as a dynamic system. We believe that the relationship of the hip external rotation and extension limitations with somatosensory data creates a sensory disorder in posture with the internal rotation and flexion of hip that commonly seen in CP gait [34] may leads to loss of balance.

The main limitation of this study is lack of comparing parameters among GMFCS levels CP clinical types, therefore in future studies, it is recommended to compare different types and levels of CP.

Conclusion

Lower limb impairment and trunk control plays important role on PC and functional mobility, therefore it is important including these parameters into the physiotherapy and rehabilitation aiming to improve functional mobility.

Declarations

Ethical Approval

Ethical approval was obtained from the Hacettepe University ethical committee (Decision no: HEK11/105) according to principles of the Declaration of Helsinki, and the parents of participant children gave written informed consent to participate.

Consent for publication

All authors (1) made substantial contributions to the acquisition, analysis, and interpretation of data; 2) drafted or revised it the work critically for important intellectual content; (3) approved the version to be published; and (4) agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Availability of data and materials

All authors declare that all data and materials and software application or custom code support their published claims and comply with feld standards.

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Funding

Not applicable

Authors' contributions

First author: Data collection, data analysis, reporting

Second author: Data interpretation

Third author: Conceptualization, editing

Acknowledgements

Not applicable

Conflict of interest

The authors declare no competing interests.

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