Original Article
Assessment of Abilities and Comorbidities in Children With Cerebral Palsy
Journal of Child Neurology 1-6 ª The Author(s) 2015 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0883073815576792 jcn.sagepub.com
Lidia V. Gabis, MD1,2, Netta Misgav Tsubary, MA1, Odelia Leon, MA1, Arie Ashkenasi, MD1, and Shahar Shefer, PhD1
Abstract This study examines major comorbidities in children with severe cerebral palsy and the feasibility of psychological tests for measuring abilities in a more impaired population. Eighty psychological evaluations of children with cerebral palsy aged 1.8 to 15.4 years (mean ¼ 5.6) were analyzed. Major comorbid disorders were correlated with severity of motor disability. More than half of the cohort were diagnosed with severe cerebral palsy according to the Gross Motor Function Classification System. Multiple subtests were combined in order to assess the intellectual level. Normal intelligence was found in 22.5%, and 41.3% had moderate or severe intellectual impairment. Epilepsy occurred in 32.5% and attention-deficit hyperactivity disorder (ADHD) in 22.5%. Intellectual disability correlated with motor ability and with epilepsy. In a logistic regression model, epilepsy and motor ability score predicted 29.9% of IQ score variance. Intellectual impairment and epilepsy are common comorbidities. Subtests from different scales should be applied and interpreted with caution. Keywords epilepsy, intelligence, cerebral palsy, comorbidities, Gross Motor Function Classification System Received October 21, 2014. Received revised January 20, 2015. Accepted for publication February 02, 2015.
Cerebral palsy is a group of neurologic disorders that appears in infancy as a result of damage to the developing brain.1 Cerebral palsy occurs in 0.2% of live births, with a rising incidence over the last few years.2 Similar to worldwide reports, in Israel cerebral palsy prevalence is 0.2% to 0.4%.3 Cerebral palsy is accompanied by other neurodevelopmental disorders4-6 and cognitive impairment.7 These comorbidities reflect brain injury, which extends beyond the motor tracts.8,9 Although cerebral palsy is not a progressive disorder, new symptoms may appear or alter in severity as the child develops, with additional comorbidities throughout his or her lifetime with a negative impact on function.5,7 According to the Surveillance of Cerebral Palsy in Europe (SCPE), the most common comorbidities are speech and language impairments (71%), followed by severe intellectual impairment (62%), epilepsy (39%), and visual impairment (22%).10 In addition, hearing impairment is a common complication that may exacerbate language difficulties. Social difficulties and autism spectrum disorders are prevalent as well.11 Cerebral palsy can be classified by motor function and by gross motor skills.12 Reliability, consistency, and predictive validity of the Gross Motor Function Classification System (GMFCS) have been established for this widely employed measure.12,13 The subtypes of cerebral palsy have long been recognized to have distinctive associations with various neurodevelopmental disorders.2 For example, individuals with quadriparesis are distinguished from individuals with hemiparesis or diparesis
in relation to the severity of their daily life dysfunction, and the likelihood of suffering from comorbidities. In the Extremely Low Gestational Age Newborns study, children with quadriparesis had a 9-fold higher likelihood to be classified on the Gross Motor Function Classification System as having a high degree of impairment than were children with diparesis as well as a 71% increase in the risk of epilepsy.8,14 Evaluating intellectual abilities is important for determining functional performance and prognosis as well as choosing an appropriate treatment approach.14,15 However, evaluation of cognitive and social levels of function is extremely challenging in view of motor impairment and sensory deficits. To overcome this barrier requires significant adjustments of evaluation tests and alterations of subtests, or assessment through evaluation of daily function.16 Repeatedly, studies attain scoring inferred from these subtests.9,17,18 Therefore, children with motor and sensory deficits are often grouped with children of IQs 3 years old. The children were diagnosed with cerebral palsy between 2006 and 2012 at the Weinberg Child Development Center, Sheba Hospital, Israel.
Data Collection In order to assess the physical impairment of the children, case histories were reviewed and data were collected from each child’s medical file to evaluate their physical and psychological impairment.
Physical Assessments Physical assessments included the following data: weight, gestational age at birth, perinatal complications, a description of the motor impairment, level of motor function (using the Gross Motor Function Classification System), and presence of epilepsy and its severity.
between epilepsy, attention-deficit hyperactivity disorder (ADHD), and cerebral palsy. In order to examine the differences between boys and girls, a t test for independent samples was conducted. In order to examine the differences in birth weight and intelligence between the types of motor impairments (upper and lower limbs, upper limbs, lower limbs) and cerebral palsy subtypes, a 1-way analysis of variance (ANOVA) was conducted along with Tukey post hoc tests. Regression models were used in order to analyze relations between cerebral palsy comorbidities, cognitive performance, and Gross Motor Function Classification System level. Logistic regression, with intellectual impairment as a dichotomous dependent variable, was completed. The variables birth week, birth weight, epilepsy, and quadriplegia were entered in the forward stepwise method.
Results Birth Week and Weight Gestational week at birth ranged from 25 to 42 weeks (mean ¼ 33, standard deviation ¼ 5.6). Moe than a third (37.2%) of the children were born at term (above 37 gestational weeks), whereas 16.3% were born moderately preterm (32-36 weeks), 46.5% were born extremely preterm (below 32 weeks). Birth weight ranged from 700 to 4100 g (mean ¼ 2000 g, standard deviation ¼ 1064), 45.1% of the children were extremely low birth weight (2500 g).
Cerebral Palsy Subtypes and Epilepsy The clinical subtypes of cerebral palsy and their relative frequency were as follows: quadriplegia 62.4%, right hemiplegia 8%, left hemiplegia 4%, athetoid cerebral palsy 11%, and diplegia 15%. Thus, 73% of the children suffered from severe physical disability. Epilepsy was prevalent in 30 (34%) of the children. Epilepsy was mainly prevalent in quadriplegia (23.8%).
Motor Ability Assessments Cognitive Assessments Cognitive assessments included a battery of subtests from several psychological and cognitive tests. At the time of evaluation, psychologists determined the appropriate test according to the motor capabilities of the child. Several batteries were attempted, until specific subtests could be accomplished. Caregivers’’ questionnaires were obtained from educators and parents. The attempted tests included StanfordBinet Intelligence Scale IV, Kaufman Assessment Battery for Children (K-ABC, Vineland Questionnaire, Bayley test, Peabody Picture Vocabulary Test [PPVT], Wechsler Preschool and Primary Scale of Intelligence, and its revised Hebrew version, the Wechsler Intelligence Scale for Children–Revised 95).
Statistical Analysis Spearman correlations were conducted to examine the associations between the variables birth weight, birth week, intelligence, and motor ability. Chi-square test was conducted to examine the correlations
As expected from cerebral palsy subtypes, the Gross Motor Function Classification System showed that 48.8% of the children were found to be severely impaired (level 5), 18.6% moderately impaired (level 4), 14% mildly impaired (level 3), 11.6% borderline (level 2), and 7% were with minimal disability score (level 1). (Characteristics of the study participants divided according to Gross Motor Function Classification System level are presented in Table 1.)
Birth Weight and the Types of Handicaps and Cerebral Palsy Subtypes Results indicated significant differences in birth weight between the different types of handicaps (F[2, 74] ¼ 3.18, P < .05) and the different cerebral palsy subtypes (F[3, 73] ¼ 4.39, P < .01). Post hoc tests showed that subjects with a lower limb handicap had a lower birth weight (mean ¼ 1750, standard
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Table 1. Characteristics of the Study Participants According to GMFCS Level. GMFCS level Characteristic Age, M (SD) Birth week, M (SD) Birth weight, M (SD) Gender, n (%) Male Female Epilepsy, n (%) ADHD, n (%) ID, n (%)
Normal ¼ 1 (n ¼ 6)
Borderline ¼ 2 (n ¼ 10)
Mild ¼ 3 (n ¼ 12)
Moderate ¼ 4 (n ¼ 16)
Severe ¼ 5 (n ¼ 42)
4.79 (1.96) 34.17 (6.65) 2472 (1195)
4.80 (2.98) 34.25 (5.26) 2344 (1017)
6.76 (3.90) 32.25 (6.15) 1737 (973)
5.69 (3.66) 29.56 (4.27) 1359 (861)
5.69 (2.59) 34.17 (5.43) 2194 (1067)
13 (81) 3 (19) 4 (24) 7 (44) 9 (56)
24 (57) 18 (43) 18 (44) 6 (14) 33 (79)
4 (67) 2 (33) 0 3 (50) 0
4 (40) 6 (60) 2 (20) 3 (30) 2 (20)
5 (42) 7 (58) 4 (33) 4 (33) 7 (58)
Abbreviations: ADHD, attention-deficit hyperactivity disorder; GMFCS, Gross Motor Function Classification System; ID, intellectual disability; M, mean; SD, standard deviation.
deviation ¼ 955) than those with an upper limb handicap (mean ¼ 2816, standard deviation ¼ 1115), and subjects with quadriplegia had a lower birth weight (mean ¼ 1847, standard deviation ¼ 943) than those with hemiplegia (mean ¼ 2816, standard deviation ¼ 1115). (see Table 2: Characteristics of the Study Participants According to Cerebral Palsy Subtypes.)
Intelligence Assessments Normal intelligence was found in 22% of the children, borderline intelligence was found in 17%, mild intellectual disability was found in 22%, moderate in 24%, and severe intellectual disability in 15%. Almost half of the children with quadriplegia were diagnosed with intellectual disability.
Cognitive Assessments The majority of children (70%) were evaluated mainly using the Vineland questionnaire, and 40% were evaluated mainly using the Bayley Scale of Infant Development. Only 10% of the children completed the entire Wechsler Preschool and Primary Scale of Intelligence or Kaufman Assessment Battery for Children tests. (A summary of the level of psychological assessments is depicted in Figure 1.)
Motor Ability and Intelligence Positive correlation was found between motor ability (Gross Motor Function Classification System level) and intelligence (Rs[86] ¼ 0.452, P < .001). In order to examine the differences in intelligence between the different types of handicaps (ie, upper and lower limbs, upper limbs, and lower limbs) and the different cerebral palsy subtypes, an ANOVA was conducted. Results indicated statistically significant differences in intelligence between the different types of handicaps (F[2, 82] ¼ 5.01, P < .01) and the different cerebral palsy subtypes (F[3, 81] ¼ 4.67, P < .01) . Tukey’s post hoc test showed significant differences in intelligence between a quadriplegia (mean ¼ 2.79, standard deviation ¼ 1.31) and upper limbs handicap (mean ¼ 4.1, standard deviation ¼ 1.45) and
Figure 1. Frequency of the various psychological tests in the percentage of children treated in the department between the years 2006 and 2012. Abbreviations: K-ABC, Kaufman Assessment Battery for Children; PEDI, Pediatric Evaluation of Disability Inventory; PPVT, Peabody Picture Vocabulary Test.
hemiplegia (mean ¼ 4.1, standard deviation ¼ 1.45). No statistically significant differences were found with a lower limb handicap.
Correlations Between Epilepsy and Intelligence An opposite correlation was found between epilepsy and intelligence (w2[4] ¼17.14, P < .01), whereas 33.3% of the children suffering from epilepsy had severe intellectual disability, and only 15% with a normal level of intelligence had epilepsy. (see Figure 2: Quadriplegia, epilepsy, and attention-deficit hyperactivity disorder (ADHD) according to intelligence level.) In order to examine the differences in intelligence between children with epilepsy and without epilepsy, a t test for independent samples was conducted. Results indicated statistically significant differences in intelligence between children with epilepsy and without epilepsy (t[87] ¼ 3.79, P < .001). The intelligence level of
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Journal of Child Neurology System level and types of handicaps were entered in the second block. The model is significant, R(2, 69) ¼ 14.54, P < .001. The findings indicate that 2 variables have a significant contribution to predicting IQ. The highest predictor of IQ is motor ability, explaining 18.8% of the variance in the IQ variable, and the second variable is epilepsy, explaining 10.9% of the variance in the IQ variable. The other variables were not found to contribute to the explanation of the IQ level. (see Table 3 Multivariable Regression Model Predicting IQ.)
Gender Differences Figure 2. Quadriplegia, epilepsy, and attention-deficit hyperactivity disorder (ADHD) according to intelligence level.
Table 2. Characteristics of the Study Participants According to Cerebral Palsy Subtypes.
Discussion
Cerebral palsy subtype Quadriplegia (n ¼ 49)
Hemiplegia (n ¼ 9)
Athetoid (n ¼ 6)
Diplegia (n ¼ 13)
Birth week, 32.46 (5.41) 35.80 (5.98) 37.17 (5.74) 31.85 (4.67) M (SD) 1847 (943) 2816 (1115) 2935 (1355) 1750 (955) Birth weight, M (SD) Epilepsy, n 20 (23.8) 3 (3.6) 4 (4.8) 2 (2.4) (%) ADHD, n 11 (12.9) 4 (4.8) 3 (3.5) 4 (4.8) (%) ID, n (%) 40 (47.1) 2 (2.4) 4 (4.8) 6 (7.1) Abbreviations: ADHD, attention-deficit hyperactivity disorder; GMFCS, Gross Motor Function Classification System; ID, intellectual disability; M, mean; SD, standard deviation.
Table 3. Multivariable Regression Model Predicting IQ. Model 1 Variable
t
b
SE
Model 2 B
b
t
SE
No significant differences were found between boys and girls in birth weight, birth week, intelligence, and motor ability.
B
Epilepsy 2.93** 0.33 0.32 0.94 1.83* 0.19 0.3 0.55 Motor ability 4.29*** 0.45 0.12 0.5 R2 0.11 0.3 F change 8.57** 18.39*** Abbreviation: IQ, Intelligence Quotient; SE, standard error. *P < .05, **P < .01, ***P < .001.
children with epilepsy (mean ¼ 2.37, standard deviation ¼ 1.30) was lower than the intelligence level of children without epilepsy (mean ¼ 3.46, standard deviation ¼ 1.28). In order to determine factors that are independently associated with IQ, multivariable regression analysis in a forward stepwise method was performed, with age as mediating variable and IQ as dependent variable. The variables birth week, birth weight, gender, epilepsy, and quadriplegia were entered in the first block, and the variables Gross Motor Function Classification
Many studies emphasize recognizing and managing cerebral palsy comorbidities and assessing their impact on long-term prognosis and level of function. Previous studies have determined the prevalence of comorbidities in cerebral palsy children, yet without thoroughly examining the correlation between different cerebral palsy comorbidities or testing the association between cerebral palsy comorbidities and cognitive performance.4,6 Our study focused on the more impaired population of children with cerebral palsy (more than 50% with Gross Motor Function Classification System levels 4 and 5). In our study cohort, only half of etiologies of cerebral palsy were related to prematurity; the others were due to hypoxic-ischemic encephalopathy at birth and additional reasons. As expected, a higher level of motor ability was associated with a higher level of intelligence, and incidence of epilepsy correlated inversely with intelligence. Epilepsy was found in more handicapped individuals (33%), and 79% of children with Gross Motor Function Classification System level 5 had intellectual disability. Upper motor disability predicted better intelligence. Both epilepsy and Gross Motor Function Classification System level predicted 29.9% of the IQ score variance. ADHD was prevalent in 22.5% of the children. The intelligence level of children without ADHD was lower than the intelligence level of children with ADHD; it is plausible that ADHD was underestimated in more impaired children. This is the first paper assessing comorbidities in the more impaired children with cerebral palsy in Israel. The results are comparable with associated impairments reported in the United States. As stressed before, the impact of comorbidities is significant and influences the function and participation of children with motor difficulties, and as such it is essential to assess, address, and follow the presence of intellectual impairment, epilepsy and behavior. However, assessment of abilities in this population is extremely challenging.
Psychological Assessments The most useful tests in assessing function and abilities were based on observations and caregiver’s reports in a natural
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setting; the Vineland Adaptive Behavior Scales with parents and teachers, Bayley Scale of Infant Development, and parts of Wechsler Preschool and Primary Scale of Intelligence and Wechsler Intelligence Scale for Children–Revised 95 in the highly functioning individuals. As previously established, intellectual impairment is prevalent in children with cerebral palsy; thus, cognitive assessment should be an essential part of cerebral palsy evaluation and research. With higher burden of neurologic disability, such as quadriplegic cerebral palsy, the prevalence of intellectual disability and epilepsy is much higher than other subtypes. Although most studies on cerebral palsy comorbidities acknowledge that cognitive assessment is important for determining prognosis, as well as planning and providing services, they confirm that these assessments are still unsatisfactory.14 Previous studies examining the prevalence of comorbidities in children with cerebral palsy have demonstrated limited ability in revealing the relationship between cerebral palsy comorbidities and cognitive performance.4,6 Furthermore, there is a paucity of data, which warrants further studies in the more impaired individuals with cerebral palsy. Identification of specific tests that are reliable and applicable to children with cerebral palsy and testing of common comorbidities will help attain more realistic expectations, will improve the effectiveness of targeted cerebral palsy interventions, and may eventually result in improvements of global function and abilities. Acknowledgments The authors thank the ‘‘Tzaad Kadima’’ Association for its cooperation.
Author Contributions LG wrote the initial draft with cooperation from OL and SS, AA reviewed the final draft, and NT was in charge of the evaluation team.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors received no financial support for the research, authorship, and/or publication of this article.
Ethical Approval This study was approved by Tel Hashomer IRB (Helsinki) committee (approval number 8121-10-SMC).
References 1. Volpe JJ. Neurology of the Newborn. 5th ed. Philadelphia: Elsevier; 2008. 2. O’shea TM, Allred EN, Dammann O, Hirtz D, Kuban KCK, Paneth N, ... & ELGAN Study Investigators. The ELGAN study of the brain and related disorders in extremely low gestational age newborns. Early Human Devel. 2009;85(11):719-725.
3. CBS, Children with special needs in pre-primary education, by type of disability and type of setting. Education, 2010 (Statistical Abstract of Israel). 4. Bax M, Goldstein M, Rosenbaum P, Leviton A, Paneth N, Dan B, ... & Damiano D. Proposed definition and classification of cerebral palsy. Dev Med Child Neurol. 2005;47(8): 571-576. 5. Morris C. Definition and classification of cerebral palsy: a historical perspective. Dev Med Child Neurol Suppl. 2007;109: 3-7. 6. The definition and classification of cerebral palsy. Dev Med Child Neurol. 2007;49(suppl 109):1-44. 7. Sankar C, Mundkur N. Cerebral palsy-definition, classification, etiology and early diagnosis. Indian J Pediatr. 2005;72: 865-868. 8. Wallace SJ. Epilepsy in cerebral palsy. Dev Med Child Neurol. 2001;43(10):713-717. 9. Muter V, Taylor S, Vargha-Khadem F. A longitudinal study of early intellectual development in hemiplegic children. Neuropsychologia. 1997;35:289-298. 10. Prevalence and characteristics of children with cerebral palsy in Europe. Dev Med Child Neurol. 2002;44:633-640. 11. Venter A, Schirm N, Joubert G, Fock JM. Profile of children diagnosed with cerebral palsy at Universitas Hospital, Bloemfontein, 1991-2001. SA Fam Pract. 2006;48(3):15. 12. Rosenbaum PL, Palisano RJ, Bartlett DJ, Galuppi BE, Russell DJ. Development of the gross motor function classification system for cerebral palsy. Dev Med Child Neurol. 2008;50(4): 249-253. 13. Wood E, Rosenbaum P. The Gross Motor Function Classification System for cerebral palsy: a study of reliability and stability over time. Dev Med Child Neurol. 2000;42:292-296. 14. Pruitt DW, Tsai T. Common medical comorbidities associated with cerebral palsy. Phys Med Rehabil Clin N Am. 2009;20: 453-467. 15. Cans C, Dolk H, Platt MJ, Colver A, Prasauskiene A, & Ra¨gelohMann IK. Recommendations from the SCPE collaborative group for defining and classifying cerebral palsy. Dev Med Child Neurol. 2007;49(s109):35-38. 16. Shevell MI, Dagenais L, Hall N. Comorbidities in cerebral palsy and their relationship to neurologic subtype and GMFCS level. Neurology. 2009;72:2090-2096. 17. Sigurdardottir S, Eiriksdottir A, Gunnarsdottir E, Meintema M, Arnadottir U, Vik T. Cognitive profile in young Icelandic children with cerebral palsy. Dev Med Child Neurol. 2008;50(5), 357-362. 18. Pueyo-Benito R, Vendrell-Gomez P. Neuropsychology of cerebral palsy [in Spanish]. Rev Neurol. 2002;34:1080-1087. 19. Surman G, Newdick H, Johnson A. Cerebral palsy rates among low-birthweight infants fell in the 1990s. Dev Med Child Neurol. 2003;45:456-462. 20. Carlsson M, Hagberg G, Olsson I. Clinical and aetiological aspects of epilepsy in children with cerebral palsy. Dev Med Child Neurol. 2003;45:371-376. 21. Himmelmann K, Hagberg G, Wiklund LM, Eek MN, & Uvebrant P. Dyskinetic cerebral palsy: a population-based study of children
Downloaded from jcn.sagepub.com at CARLETON UNIV on May 9, 2015
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Journal of Child Neurology
born between 1991 and 1998. Dev Med Child Neurol. 2007;49(4): 246-251. 22. Andersen GL, Irgens LM, Haagaas I, Skranes JS, Meberg AE, Vik T. Cerebral palsy in Norway: prevalence, subtypes and severity. Eur J Paediat Neurol. 2008;12(1):4-13. 23. Dahlgren Sandberg A. Reading and spelling abilities in children with severe speech impairments and cerebral palsy at
6, 9, and 12 years of age in relation to cognitive development: a longitudinal study. Dev Med Child Neurol. 2006;48: 629-634. 24. Pueyo R, Junque´ C, Vendrell P, Narberhaus A, Segarra D. Raven’s Coloured Progressive Matrices as a measure of cognitive functioning in Cerebral Palsy. J Intellect Disabil Res. 2008;52(5), 437-445.
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Assessment of Abilities and Comorbidities in Children With Cerebral Palsy
Journal of Child Neurology 1-6 ª The Author(s) 2015 Reprints and permission: sagepub.com/journalsPermissions.nav DOI: 10.1177/0883073815576792 jcn.sagepub.com
Lidia V. Gabis, MD1,2, Netta Misgav Tsubary, MA1, Odelia Leon, MA1, Arie Ashkenasi, MD1, and Shahar Shefer, PhD1
Abstract This study examines major comorbidities in children with severe cerebral palsy and the feasibility of psychological tests for measuring abilities in a more impaired population. Eighty psychological evaluations of children with cerebral palsy aged 1.8 to 15.4 years (mean ¼ 5.6) were analyzed. Major comorbid disorders were correlated with severity of motor disability. More than half of the cohort were diagnosed with severe cerebral palsy according to the Gross Motor Function Classification System. Multiple subtests were combined in order to assess the intellectual level. Normal intelligence was found in 22.5%, and 41.3% had moderate or severe intellectual impairment. Epilepsy occurred in 32.5% and attention-deficit hyperactivity disorder (ADHD) in 22.5%. Intellectual disability correlated with motor ability and with epilepsy. In a logistic regression model, epilepsy and motor ability score predicted 29.9% of IQ score variance. Intellectual impairment and epilepsy are common comorbidities. Subtests from different scales should be applied and interpreted with caution. Keywords epilepsy, intelligence, cerebral palsy, comorbidities, Gross Motor Function Classification System Received October 21, 2014. Received revised January 20, 2015. Accepted for publication February 02, 2015.
Cerebral palsy is a group of neurologic disorders that appears in infancy as a result of damage to the developing brain.1 Cerebral palsy occurs in 0.2% of live births, with a rising incidence over the last few years.2 Similar to worldwide reports, in Israel cerebral palsy prevalence is 0.2% to 0.4%.3 Cerebral palsy is accompanied by other neurodevelopmental disorders4-6 and cognitive impairment.7 These comorbidities reflect brain injury, which extends beyond the motor tracts.8,9 Although cerebral palsy is not a progressive disorder, new symptoms may appear or alter in severity as the child develops, with additional comorbidities throughout his or her lifetime with a negative impact on function.5,7 According to the Surveillance of Cerebral Palsy in Europe (SCPE), the most common comorbidities are speech and language impairments (71%), followed by severe intellectual impairment (62%), epilepsy (39%), and visual impairment (22%).10 In addition, hearing impairment is a common complication that may exacerbate language difficulties. Social difficulties and autism spectrum disorders are prevalent as well.11 Cerebral palsy can be classified by motor function and by gross motor skills.12 Reliability, consistency, and predictive validity of the Gross Motor Function Classification System (GMFCS) have been established for this widely employed measure.12,13 The subtypes of cerebral palsy have long been recognized to have distinctive associations with various neurodevelopmental disorders.2 For example, individuals with quadriparesis are distinguished from individuals with hemiparesis or diparesis
in relation to the severity of their daily life dysfunction, and the likelihood of suffering from comorbidities. In the Extremely Low Gestational Age Newborns study, children with quadriparesis had a 9-fold higher likelihood to be classified on the Gross Motor Function Classification System as having a high degree of impairment than were children with diparesis as well as a 71% increase in the risk of epilepsy.8,14 Evaluating intellectual abilities is important for determining functional performance and prognosis as well as choosing an appropriate treatment approach.14,15 However, evaluation of cognitive and social levels of function is extremely challenging in view of motor impairment and sensory deficits. To overcome this barrier requires significant adjustments of evaluation tests and alterations of subtests, or assessment through evaluation of daily function.16 Repeatedly, studies attain scoring inferred from these subtests.9,17,18 Therefore, children with motor and sensory deficits are often grouped with children of IQs 3 years old. The children were diagnosed with cerebral palsy between 2006 and 2012 at the Weinberg Child Development Center, Sheba Hospital, Israel.
Data Collection In order to assess the physical impairment of the children, case histories were reviewed and data were collected from each child’s medical file to evaluate their physical and psychological impairment.
Physical Assessments Physical assessments included the following data: weight, gestational age at birth, perinatal complications, a description of the motor impairment, level of motor function (using the Gross Motor Function Classification System), and presence of epilepsy and its severity.
between epilepsy, attention-deficit hyperactivity disorder (ADHD), and cerebral palsy. In order to examine the differences between boys and girls, a t test for independent samples was conducted. In order to examine the differences in birth weight and intelligence between the types of motor impairments (upper and lower limbs, upper limbs, lower limbs) and cerebral palsy subtypes, a 1-way analysis of variance (ANOVA) was conducted along with Tukey post hoc tests. Regression models were used in order to analyze relations between cerebral palsy comorbidities, cognitive performance, and Gross Motor Function Classification System level. Logistic regression, with intellectual impairment as a dichotomous dependent variable, was completed. The variables birth week, birth weight, epilepsy, and quadriplegia were entered in the forward stepwise method.
Results Birth Week and Weight Gestational week at birth ranged from 25 to 42 weeks (mean ¼ 33, standard deviation ¼ 5.6). Moe than a third (37.2%) of the children were born at term (above 37 gestational weeks), whereas 16.3% were born moderately preterm (32-36 weeks), 46.5% were born extremely preterm (below 32 weeks). Birth weight ranged from 700 to 4100 g (mean ¼ 2000 g, standard deviation ¼ 1064), 45.1% of the children were extremely low birth weight (2500 g).
Cerebral Palsy Subtypes and Epilepsy The clinical subtypes of cerebral palsy and their relative frequency were as follows: quadriplegia 62.4%, right hemiplegia 8%, left hemiplegia 4%, athetoid cerebral palsy 11%, and diplegia 15%. Thus, 73% of the children suffered from severe physical disability. Epilepsy was prevalent in 30 (34%) of the children. Epilepsy was mainly prevalent in quadriplegia (23.8%).
Motor Ability Assessments Cognitive Assessments Cognitive assessments included a battery of subtests from several psychological and cognitive tests. At the time of evaluation, psychologists determined the appropriate test according to the motor capabilities of the child. Several batteries were attempted, until specific subtests could be accomplished. Caregivers’’ questionnaires were obtained from educators and parents. The attempted tests included StanfordBinet Intelligence Scale IV, Kaufman Assessment Battery for Children (K-ABC, Vineland Questionnaire, Bayley test, Peabody Picture Vocabulary Test [PPVT], Wechsler Preschool and Primary Scale of Intelligence, and its revised Hebrew version, the Wechsler Intelligence Scale for Children–Revised 95).
Statistical Analysis Spearman correlations were conducted to examine the associations between the variables birth weight, birth week, intelligence, and motor ability. Chi-square test was conducted to examine the correlations
As expected from cerebral palsy subtypes, the Gross Motor Function Classification System showed that 48.8% of the children were found to be severely impaired (level 5), 18.6% moderately impaired (level 4), 14% mildly impaired (level 3), 11.6% borderline (level 2), and 7% were with minimal disability score (level 1). (Characteristics of the study participants divided according to Gross Motor Function Classification System level are presented in Table 1.)
Birth Weight and the Types of Handicaps and Cerebral Palsy Subtypes Results indicated significant differences in birth weight between the different types of handicaps (F[2, 74] ¼ 3.18, P < .05) and the different cerebral palsy subtypes (F[3, 73] ¼ 4.39, P < .01). Post hoc tests showed that subjects with a lower limb handicap had a lower birth weight (mean ¼ 1750, standard
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Table 1. Characteristics of the Study Participants According to GMFCS Level. GMFCS level Characteristic Age, M (SD) Birth week, M (SD) Birth weight, M (SD) Gender, n (%) Male Female Epilepsy, n (%) ADHD, n (%) ID, n (%)
Normal ¼ 1 (n ¼ 6)
Borderline ¼ 2 (n ¼ 10)
Mild ¼ 3 (n ¼ 12)
Moderate ¼ 4 (n ¼ 16)
Severe ¼ 5 (n ¼ 42)
4.79 (1.96) 34.17 (6.65) 2472 (1195)
4.80 (2.98) 34.25 (5.26) 2344 (1017)
6.76 (3.90) 32.25 (6.15) 1737 (973)
5.69 (3.66) 29.56 (4.27) 1359 (861)
5.69 (2.59) 34.17 (5.43) 2194 (1067)
13 (81) 3 (19) 4 (24) 7 (44) 9 (56)
24 (57) 18 (43) 18 (44) 6 (14) 33 (79)
4 (67) 2 (33) 0 3 (50) 0
4 (40) 6 (60) 2 (20) 3 (30) 2 (20)
5 (42) 7 (58) 4 (33) 4 (33) 7 (58)
Abbreviations: ADHD, attention-deficit hyperactivity disorder; GMFCS, Gross Motor Function Classification System; ID, intellectual disability; M, mean; SD, standard deviation.
deviation ¼ 955) than those with an upper limb handicap (mean ¼ 2816, standard deviation ¼ 1115), and subjects with quadriplegia had a lower birth weight (mean ¼ 1847, standard deviation ¼ 943) than those with hemiplegia (mean ¼ 2816, standard deviation ¼ 1115). (see Table 2: Characteristics of the Study Participants According to Cerebral Palsy Subtypes.)
Intelligence Assessments Normal intelligence was found in 22% of the children, borderline intelligence was found in 17%, mild intellectual disability was found in 22%, moderate in 24%, and severe intellectual disability in 15%. Almost half of the children with quadriplegia were diagnosed with intellectual disability.
Cognitive Assessments The majority of children (70%) were evaluated mainly using the Vineland questionnaire, and 40% were evaluated mainly using the Bayley Scale of Infant Development. Only 10% of the children completed the entire Wechsler Preschool and Primary Scale of Intelligence or Kaufman Assessment Battery for Children tests. (A summary of the level of psychological assessments is depicted in Figure 1.)
Motor Ability and Intelligence Positive correlation was found between motor ability (Gross Motor Function Classification System level) and intelligence (Rs[86] ¼ 0.452, P < .001). In order to examine the differences in intelligence between the different types of handicaps (ie, upper and lower limbs, upper limbs, and lower limbs) and the different cerebral palsy subtypes, an ANOVA was conducted. Results indicated statistically significant differences in intelligence between the different types of handicaps (F[2, 82] ¼ 5.01, P < .01) and the different cerebral palsy subtypes (F[3, 81] ¼ 4.67, P < .01) . Tukey’s post hoc test showed significant differences in intelligence between a quadriplegia (mean ¼ 2.79, standard deviation ¼ 1.31) and upper limbs handicap (mean ¼ 4.1, standard deviation ¼ 1.45) and
Figure 1. Frequency of the various psychological tests in the percentage of children treated in the department between the years 2006 and 2012. Abbreviations: K-ABC, Kaufman Assessment Battery for Children; PEDI, Pediatric Evaluation of Disability Inventory; PPVT, Peabody Picture Vocabulary Test.
hemiplegia (mean ¼ 4.1, standard deviation ¼ 1.45). No statistically significant differences were found with a lower limb handicap.
Correlations Between Epilepsy and Intelligence An opposite correlation was found between epilepsy and intelligence (w2[4] ¼17.14, P < .01), whereas 33.3% of the children suffering from epilepsy had severe intellectual disability, and only 15% with a normal level of intelligence had epilepsy. (see Figure 2: Quadriplegia, epilepsy, and attention-deficit hyperactivity disorder (ADHD) according to intelligence level.) In order to examine the differences in intelligence between children with epilepsy and without epilepsy, a t test for independent samples was conducted. Results indicated statistically significant differences in intelligence between children with epilepsy and without epilepsy (t[87] ¼ 3.79, P < .001). The intelligence level of
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Journal of Child Neurology System level and types of handicaps were entered in the second block. The model is significant, R(2, 69) ¼ 14.54, P < .001. The findings indicate that 2 variables have a significant contribution to predicting IQ. The highest predictor of IQ is motor ability, explaining 18.8% of the variance in the IQ variable, and the second variable is epilepsy, explaining 10.9% of the variance in the IQ variable. The other variables were not found to contribute to the explanation of the IQ level. (see Table 3 Multivariable Regression Model Predicting IQ.)
Gender Differences Figure 2. Quadriplegia, epilepsy, and attention-deficit hyperactivity disorder (ADHD) according to intelligence level.
Table 2. Characteristics of the Study Participants According to Cerebral Palsy Subtypes.
Discussion
Cerebral palsy subtype Quadriplegia (n ¼ 49)
Hemiplegia (n ¼ 9)
Athetoid (n ¼ 6)
Diplegia (n ¼ 13)
Birth week, 32.46 (5.41) 35.80 (5.98) 37.17 (5.74) 31.85 (4.67) M (SD) 1847 (943) 2816 (1115) 2935 (1355) 1750 (955) Birth weight, M (SD) Epilepsy, n 20 (23.8) 3 (3.6) 4 (4.8) 2 (2.4) (%) ADHD, n 11 (12.9) 4 (4.8) 3 (3.5) 4 (4.8) (%) ID, n (%) 40 (47.1) 2 (2.4) 4 (4.8) 6 (7.1) Abbreviations: ADHD, attention-deficit hyperactivity disorder; GMFCS, Gross Motor Function Classification System; ID, intellectual disability; M, mean; SD, standard deviation.
Table 3. Multivariable Regression Model Predicting IQ. Model 1 Variable
t
b
SE
Model 2 B
b
t
SE
No significant differences were found between boys and girls in birth weight, birth week, intelligence, and motor ability.
B
Epilepsy 2.93** 0.33 0.32 0.94 1.83* 0.19 0.3 0.55 Motor ability 4.29*** 0.45 0.12 0.5 R2 0.11 0.3 F change 8.57** 18.39*** Abbreviation: IQ, Intelligence Quotient; SE, standard error. *P < .05, **P < .01, ***P < .001.
children with epilepsy (mean ¼ 2.37, standard deviation ¼ 1.30) was lower than the intelligence level of children without epilepsy (mean ¼ 3.46, standard deviation ¼ 1.28). In order to determine factors that are independently associated with IQ, multivariable regression analysis in a forward stepwise method was performed, with age as mediating variable and IQ as dependent variable. The variables birth week, birth weight, gender, epilepsy, and quadriplegia were entered in the first block, and the variables Gross Motor Function Classification
Many studies emphasize recognizing and managing cerebral palsy comorbidities and assessing their impact on long-term prognosis and level of function. Previous studies have determined the prevalence of comorbidities in cerebral palsy children, yet without thoroughly examining the correlation between different cerebral palsy comorbidities or testing the association between cerebral palsy comorbidities and cognitive performance.4,6 Our study focused on the more impaired population of children with cerebral palsy (more than 50% with Gross Motor Function Classification System levels 4 and 5). In our study cohort, only half of etiologies of cerebral palsy were related to prematurity; the others were due to hypoxic-ischemic encephalopathy at birth and additional reasons. As expected, a higher level of motor ability was associated with a higher level of intelligence, and incidence of epilepsy correlated inversely with intelligence. Epilepsy was found in more handicapped individuals (33%), and 79% of children with Gross Motor Function Classification System level 5 had intellectual disability. Upper motor disability predicted better intelligence. Both epilepsy and Gross Motor Function Classification System level predicted 29.9% of the IQ score variance. ADHD was prevalent in 22.5% of the children. The intelligence level of children without ADHD was lower than the intelligence level of children with ADHD; it is plausible that ADHD was underestimated in more impaired children. This is the first paper assessing comorbidities in the more impaired children with cerebral palsy in Israel. The results are comparable with associated impairments reported in the United States. As stressed before, the impact of comorbidities is significant and influences the function and participation of children with motor difficulties, and as such it is essential to assess, address, and follow the presence of intellectual impairment, epilepsy and behavior. However, assessment of abilities in this population is extremely challenging.
Psychological Assessments The most useful tests in assessing function and abilities were based on observations and caregiver’s reports in a natural
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setting; the Vineland Adaptive Behavior Scales with parents and teachers, Bayley Scale of Infant Development, and parts of Wechsler Preschool and Primary Scale of Intelligence and Wechsler Intelligence Scale for Children–Revised 95 in the highly functioning individuals. As previously established, intellectual impairment is prevalent in children with cerebral palsy; thus, cognitive assessment should be an essential part of cerebral palsy evaluation and research. With higher burden of neurologic disability, such as quadriplegic cerebral palsy, the prevalence of intellectual disability and epilepsy is much higher than other subtypes. Although most studies on cerebral palsy comorbidities acknowledge that cognitive assessment is important for determining prognosis, as well as planning and providing services, they confirm that these assessments are still unsatisfactory.14 Previous studies examining the prevalence of comorbidities in children with cerebral palsy have demonstrated limited ability in revealing the relationship between cerebral palsy comorbidities and cognitive performance.4,6 Furthermore, there is a paucity of data, which warrants further studies in the more impaired individuals with cerebral palsy. Identification of specific tests that are reliable and applicable to children with cerebral palsy and testing of common comorbidities will help attain more realistic expectations, will improve the effectiveness of targeted cerebral palsy interventions, and may eventually result in improvements of global function and abilities. Acknowledgments The authors thank the ‘‘Tzaad Kadima’’ Association for its cooperation.
Author Contributions LG wrote the initial draft with cooperation from OL and SS, AA reviewed the final draft, and NT was in charge of the evaluation team.
Declaration of Conflicting Interests The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding The authors received no financial support for the research, authorship, and/or publication of this article.
Ethical Approval This study was approved by Tel Hashomer IRB (Helsinki) committee (approval number 8121-10-SMC).
References 1. Volpe JJ. Neurology of the Newborn. 5th ed. Philadelphia: Elsevier; 2008. 2. O’shea TM, Allred EN, Dammann O, Hirtz D, Kuban KCK, Paneth N, ... & ELGAN Study Investigators. The ELGAN study of the brain and related disorders in extremely low gestational age newborns. Early Human Devel. 2009;85(11):719-725.
3. CBS, Children with special needs in pre-primary education, by type of disability and type of setting. Education, 2010 (Statistical Abstract of Israel). 4. Bax M, Goldstein M, Rosenbaum P, Leviton A, Paneth N, Dan B, ... & Damiano D. Proposed definition and classification of cerebral palsy. Dev Med Child Neurol. 2005;47(8): 571-576. 5. Morris C. Definition and classification of cerebral palsy: a historical perspective. Dev Med Child Neurol Suppl. 2007;109: 3-7. 6. The definition and classification of cerebral palsy. Dev Med Child Neurol. 2007;49(suppl 109):1-44. 7. Sankar C, Mundkur N. Cerebral palsy-definition, classification, etiology and early diagnosis. Indian J Pediatr. 2005;72: 865-868. 8. Wallace SJ. Epilepsy in cerebral palsy. Dev Med Child Neurol. 2001;43(10):713-717. 9. Muter V, Taylor S, Vargha-Khadem F. A longitudinal study of early intellectual development in hemiplegic children. Neuropsychologia. 1997;35:289-298. 10. Prevalence and characteristics of children with cerebral palsy in Europe. Dev Med Child Neurol. 2002;44:633-640. 11. Venter A, Schirm N, Joubert G, Fock JM. Profile of children diagnosed with cerebral palsy at Universitas Hospital, Bloemfontein, 1991-2001. SA Fam Pract. 2006;48(3):15. 12. Rosenbaum PL, Palisano RJ, Bartlett DJ, Galuppi BE, Russell DJ. Development of the gross motor function classification system for cerebral palsy. Dev Med Child Neurol. 2008;50(4): 249-253. 13. Wood E, Rosenbaum P. The Gross Motor Function Classification System for cerebral palsy: a study of reliability and stability over time. Dev Med Child Neurol. 2000;42:292-296. 14. Pruitt DW, Tsai T. Common medical comorbidities associated with cerebral palsy. Phys Med Rehabil Clin N Am. 2009;20: 453-467. 15. Cans C, Dolk H, Platt MJ, Colver A, Prasauskiene A, & Ra¨gelohMann IK. Recommendations from the SCPE collaborative group for defining and classifying cerebral palsy. Dev Med Child Neurol. 2007;49(s109):35-38. 16. Shevell MI, Dagenais L, Hall N. Comorbidities in cerebral palsy and their relationship to neurologic subtype and GMFCS level. Neurology. 2009;72:2090-2096. 17. Sigurdardottir S, Eiriksdottir A, Gunnarsdottir E, Meintema M, Arnadottir U, Vik T. Cognitive profile in young Icelandic children with cerebral palsy. Dev Med Child Neurol. 2008;50(5), 357-362. 18. Pueyo-Benito R, Vendrell-Gomez P. Neuropsychology of cerebral palsy [in Spanish]. Rev Neurol. 2002;34:1080-1087. 19. Surman G, Newdick H, Johnson A. Cerebral palsy rates among low-birthweight infants fell in the 1990s. Dev Med Child Neurol. 2003;45:456-462. 20. Carlsson M, Hagberg G, Olsson I. Clinical and aetiological aspects of epilepsy in children with cerebral palsy. Dev Med Child Neurol. 2003;45:371-376. 21. Himmelmann K, Hagberg G, Wiklund LM, Eek MN, & Uvebrant P. Dyskinetic cerebral palsy: a population-based study of children
Downloaded from jcn.sagepub.com at CARLETON UNIV on May 9, 2015
6
Journal of Child Neurology
born between 1991 and 1998. Dev Med Child Neurol. 2007;49(4): 246-251. 22. Andersen GL, Irgens LM, Haagaas I, Skranes JS, Meberg AE, Vik T. Cerebral palsy in Norway: prevalence, subtypes and severity. Eur J Paediat Neurol. 2008;12(1):4-13. 23. Dahlgren Sandberg A. Reading and spelling abilities in children with severe speech impairments and cerebral palsy at
6, 9, and 12 years of age in relation to cognitive development: a longitudinal study. Dev Med Child Neurol. 2006;48: 629-634. 24. Pueyo R, Junque´ C, Vendrell P, Narberhaus A, Segarra D. Raven’s Coloured Progressive Matrices as a measure of cognitive functioning in Cerebral Palsy. J Intellect Disabil Res. 2008;52(5), 437-445.
Downloaded from jcn.sagepub.com at CARLETON UNIV on May 9, 2015
