Cerebral palsy (CP) encompasses a heterogeneous group of neurodevelopmental disorders of movement and posture with a broad spectrum of clinical manifestations . CP is among the most common causes of childhood physical disability worldwide with prevalence estimates ranging from 2.0 to 3.5 patients per 1000 live births [8, 15, 21]. Low- and middle-income countries disproportionately bear the majority of the global burden of CP; in fact, 80% of the global prevalence of childhood disability is estimated to be in low-income countries [11, 27].
Population-based studies and disability registers have helped to characterize the etiologies, patterns of limb involvement, and associated comorbidities of CP in high-income countries [4, 25]. However, similar research in low-income countries is lacking . Given the heterogeneous nature of CP, it is likely that the epidemiology of this group of disorders varies considerably across socioeconomic and geographic contexts [5, 6, 9, 11]. The availability, accessibility, and affordability of pediatric orthopaedic and neuromuscular care are limited in low- and middle-income countries, but the functional outcomes associated with this paucity of care are poorly understood . A better understanding of how these children present for care in resource-limited settings is important because it will better characterize the natural history of CP, guide clinical decision-making in austere environments, and aid in the prognostication of children with untreated CP. More accurately describing the functional trajectory of children with untreated CP is an important task, both for minimizing further functional impairment for untreated children as well as understanding how the timing and types of musculoskeletal interventions can impact the degree of disability in patients with CP.
Therefore, we sought (1) to determine the etiologies, motor subtypes, topographic distributions, and functional classifications of a large cohort of Nepali children with untreated CP presenting to a large pediatric rehabilitation center in Nepal; and (2) to compare the Gross Motor Function Classification System (GMFCS), the Manual Ability Classification System (MACS), and the Communication Function Classification System (CFCS) scores of a subset of patients with spastic CP in the Nepali cohort with control subjects from high-income countries.
Patients and Methods
In this prospective, cross-sectional study, we assessed all children with untreated CP presenting for initial evaluation to the Hospital and Rehabilitation Centre for Disabled Children (HRDC) in Nepal. HRDC is a large nonprofit health facility that provides rehabilitative care for children and adolescents with physical disabilities in Nepal. It is in the town of Banepa, approximately 1 hour by car from the Nepali capital, Kathmandu. Statistics from HRDC suggest that 17% of patients presenting for care have a diagnosis of CP, making it the second most common diagnosis seen after clubfoot. Study enrollment occurred from February 2015 to April 2016. Patients were considered untreated if they had no reported or documented history of medical therapy, physiotherapy, or surgical intervention.
All study data are routinely collected at HRDC. When patients with CP are evaluated for the first time, they are seen by an orthopaedic surgeon and a physical therapist specializing in the care of patients with CP. A standardized comprehensive evaluation sheet is used to assess all patients; it includes data on age, sex, home district, labor history, etiology, limb involvement, motor subtype, and multiple functional measures. The CP diagnosis is based on a combination of developmental delay, clinical history, and physical assessment that suggests a clinical phenotype consistent with CP. All providers at HRDC undergo advanced training in the diagnosis and evaluation of children with neurodevelopmental disorders. Their training, in conjunction with a standardized evaluation form, ensure that the diagnosis of CP is consistent and correct after reasonably ruling out other secondary causes of neurodevelopmental delay. Presumed etiologic timing is classified as prenatal, perinatal, or postnatal. In patients with several possible etiologies, the earliest presumed injury is used. Motor subtype and limb involvement are classified according to the Surveillance of Cerebral Palsy in Europe system as spastic unilateral, spastic bilateral, spastic quadriplegic, dyskinetic, ataxic, or mixed . Gross motor function, manual ability, and communication function are assessed using the expanded and revised version of the GMFCS, the MACS, and the CFCS, respectively [10, 14, 20]. These classification systems are graded in order of increasing severity from I to V and are defined according to key functional benchmarks (Table 1).
A total of 206 children with CP were included in the initial cohort to answer the study’s first research question regarding how Nepali children with untreated CP initially present. Children came from 60 (80%) of 75 total districts in Nepal (Fig. 1). The median age of children was 4.0 years (range, 0.25-17 years), and approximately two-thirds of the total cohort were boys (Table 2). Of the original 206 children, 102 were found to have spastic CP and were included in the comparative subset to answer the study’s second research question regarding functional differences between Nepali and high-income children with spastic CP. Children with nonspastic CP or an unknown CP subtype were excluded from the comparative analysis because the systematic review only captured children with spastic CP, and a comparison across subtypes would have been inappropriate. The two reasons for exclusion from the comparative subset were age (n = 19) and subtype other than spastic (n = 85) (Fig. 2).
To obtain control subjects for comparison with the Nepali subjects with spastic CP, we conducted a systematic review of large studies of children with CP from high-income countries. We then conducted a random-effects pooled analysis on the data sets to obtain control functional scores for comparison. This was chosen over raw pooling to account for differing variances across studies of varying sample sizes. A Freeman-Tukey correction was utilized to ensure that studies with proportions of 0 or 1 were not excluded. Although conducting meta-analytic pooling on retrospective data sets has limitations given known biases associated with retrospective data, this strategy was used because (1) the studies were selected on the basis of being approximately representative of the populations in which they were conducted; and (2) alternative methods of obtaining control subjects and primary data were not feasible.
Specifically, we searched the Medline and Cochrane databases for articles from January 2004 to January 2016. This window of time was chosen to accommodate for the increased use of electronic medical records (EMRs) in high-income countries starting in the early 2000s, because we felt that articles published before 2004 may have difficulty with data recording as a result of a lack of EMRs. Search terms were “cerebral palsy” and “GMFCS”, “gross motor”, “motor function”, “MACS”, “manual ability”, “CFCS”, or “communication function”. Search terms were limited to title. We reviewed all studies resulting from this initial search. Inclusion criteria were (1) English language; (2) study conducted in a high-income country, defined by the World Bank as any country with a gross national income per capita above USD 12,475; (3) study sample of at least 50 patients; and (4) inclusion of the GMFCS, MACS, and/or CFCS classifications. Studies were excluded if they (1) did not meet the previously described inclusion criteria; (2) did not stratify by limb involvement; (3) were limited to a specific subset of a study population; (4) were interventional in nature; or (5) were not population-based cross-sectional studies or registry-based studies.
As a result of variations in reporting motor subtype and topographic distribution among the identified studies, only spastic patients were included in the present analysis. Dyskinetic, ataxic, and mixed subtypes were excluded to ensure consistency with our study sample. Given the difficulty in finding studies of children with CP in high-income countries who have not previously been diagnosed or undergone treatment, we were not able to restrict the search to untreated children. One author (DGL) performed the initial search and two authors (KDB, DAS) independently reviewed the results. Disagreements were discussed among all three authors performing the systematic review until consensus was achieved. Abstracted data included GMFCS, MACS, and CFCS scores. These data were aggregated and remained stratified by limb involvement.
A total of 198 unique studies were initially selected (Fig. 3). One hundred ninety were subsequently excluded, leaving eight studies (Table 3) [4, 7, 13, 16, 18, 19, 22, 26]. Only one of the included studies reported all three functional measures . Eight studies provided control data for GMFCS [4, 7, 13, 16, 18, 19, 22, 26]; two studies provided data for MACS [7, 13]; one study provided data for CFCS . Five studies reported results for spastic patients stratified by limb involvement [4, 7, 16, 18, 19]. Three studies did not mention motor subtype [13, 22, 26].
All selected articles underwent a systematic quality assessment using a standardized qualitative abstraction form described by Zaza et al. . This instrument assesses study quality across six categories: description of the population, sampling, measurement, analysis, results interpretation, and other execution issues. Based on our standardized evaluation of the included studies, the risk of confounding was low to moderate for each study given that the included studies were purely descriptive and noninterventional, which precludes any source of bias stemming from comparisons across intervention groups. Any additional sources of bias (such as selection bias from a nonrepresentative sample or information bias from invalid clinical evaluations of subjects) was appropriately controlled for in the included studies. No studies oversampled clinical strata, which would have led to selection bias. Two studies [13, 22] mentioned how recruitment bias might lead to oversampling more severely affected children. Seven of the eight studies relied on trained providers to assess GMFCS, MACS, and CFCS functional classifications [4, 7, 16, 18, 19, 22, 26] and one relied on caregivers .
We compared differences in functional classification scores between the Nepali group and scores obtained from the systematic review with calculated differences in proportions for independent samples. Specifically, the proportion of control subjects from the systematic review having functional classification scores of I or II, accounting for the random-effects variance, was compared with the corresponding proportion of Nepali children having scores of I or II. Functional scores were analyzed as binary outcomes (that is, I or II versus III, IV, or V) instead of ordinal outcomes because we felt that having excellent or good function (I or II) versus poor function (III through V) was a more useful indicator of functional status. We excluded children from the Nepali sample and high-income control subjects with motor subtypes other than spastic CP from the comparative analysis to ensure compatible comparisons across subtype. We excluded patients who were younger than 2 years old from this analysis because the functional classification instruments we used are not validated in children younger than 2 years.
Descriptive statistics were used to present sample characteristics. Statistical significance was determined by a two-sided type I error rate of α ≤ 0.05. Data analyses were performed using STATA 14.1 (StataCorp, College Station, TX, USA).
All Nepali families provided written informed consent to participate. Ethical approval was granted by the Nepal Health Research Council (Kathmandu, Nepal). Institutional review board exemption was granted by the institutional review board of the Children’s Hospital of Philadelphia (Philadelphia, PA, USA).
The majority of Nepali patients had perinatal or postnatal CP etiologies and half had spastic CP. The presumed etiology was prematurity in 17 of 206 patients (8%), whereas perinatal and postnatal etiologies were the etiology in 141 patients (69%). The most common perinatal and postnatal etiologies were anoxia (n = 100 [49%]) and infection (n = 21 [10%]), respectively. Stratified by motor subtype, 104 patients (50%) had spastic CP, 39 (19%) were dyskinetic, and 44 (21%) were either ataxic or mixed. Fifty-four patients (26%) had hemiplegia, 57 (28%) had diplegia, and 89 (43%) had triplegia or quadriplegia.
Children with spastic hemiplegia from high-income countries were more likely to have better GMFCS and MACS scores than those children in Nepal, although no motor functional differences were seen in children with spastic diplegia and quadriplegia. A total of 1842 high-income children were compared with 102 Nepali children (Table 4). After random-effects pooling, 96% (95% confidence interval [CI], 92%-99%) of children with spastic hemiplegia from high-income countries had GMFCS scores of I or II, which was more than the corresponding proportion of children from Nepal (78%; 95% CI, 62%-89%) (Fig. 4). Similarly, 83% (95% CI, 77%-88%) of children with spastic hemiplegia from high-income countries had MACS scores of I or II relative to 50% (95% CI, 32%-68%) of children from Nepal. However, children with spastic hemiplegia from high-income countries were less likely to have a CFCS score of I or II (67% [95% CI, 51%-80%] versus 97% [95% CI, 87%-99%]). No differences in GMFCS, MACS, or CFCS scores were seen in children with spastic diplegia or quadriplegia. Complete descriptive statistics for age and sex were not routinely reported by the studies identified by systematic review, precluding a comparison of the Nepali sample’s age and sex distributions with those from the systematic review, thereby precluding any comparisons in relation to the Nepali sample. However, some studies reported wide age ranges (unstratified by subtype or functional classification) consistent with the Nepali sample, thereby minimizing the risk of classification bias resulting from age differences.
Socioeconomic factors likely influence the functional severity of children with CP, leading to disparities between impairment and disability. A better understanding of how socioeconomic status affects functional status in children with CP, especially in low-resource settings, will not only highlight the importance of targeted interventions to preserve functional status, but also more clearly define the natural history of this complex set of disorders. This prospective observational study aimed to (1) characterize the clinical characteristics of children with untreated CP presenting for care in Nepal; and (2) compare the functional severity of these children with a sample of children with CP from high-income countries. To these ends, we evaluated 206 children with untreated CP presenting for initial evaluation to a large pediatric rehabilitation hospital in Nepal and compared the functional severity of a subset of 102 Nepali children with spastic CP with that of a control sample derived from a systematic review of children with CP from high-income countries.
Our study has multiple limitations. Most importantly, our study may be subject to ascertainment bias given that children in the study sample may not accurately represent the entire population with CP in Nepal. We may have missed patients who did not present to a mobile camp or the main treatment center because they received care at another institution, were unaware of available services, were unable to access care, were kept away from accessing care by their caregivers, or felt that no care was needed or that nothing could be done to help. We feel that this will not detract from our study conclusions because our aim was not to characterize the epidemiology of CP in Nepal overall, but rather to understand the range of disability and impairments among those who actually present for treatment. Moreover, subjects in our study were from 60 of 75 districts in Nepal. Characterizing the epidemiology of CP in Nepal as a whole would require a large community-based and resource-intensive study, which, to our knowledge, has never been conducted and because of resource constraints, this seems unlikely to occur. Indeed, the risk of ascertainment bias is present among the studies identified by the systematic review, because children with less severe disease may be less likely to present for care and participate in CP studies. More than 600 patients per year are given a presumptive diagnosis of CP during HRDC screening camps, which reach > 20 districts around Nepal; this suggests that there are many children with CP who have yet to be evaluated throughout the country.
Relying on control subjects derived from a systematic review has limitations relative to using primary data. Importantly, there are issues with generalizability of the systematic review data both within and between high-income countries. First, it is possible that each individual study may not represent an unbiased estimation of the population in which each was conducted. For example, two studies [13, 22] mentioned the possibility of ascertainment bias leading to oversampling more severely affected children; however, one would expect such bias to shift our findings toward a false-negative finding rather than a false-positive. Second, it is also possible that the pooled estimates may not be representative of high-income countries as a whole given wide variability across countries in terms of health systems, pediatric health care, and research infrastructure. However, we believe this was adequately controlled for based on our strict inclusion and exclusion criteria ensuring that all studies were reasonably representative of the greater population of children with CP in their respective regions. It is also important to recognize that large primary data sets of children with CP in high-income countries are not readily available, so the current methodology was deemed appropriate to answer the previously posed research questions. A second limitation of the systematic review approach is the quality of the control subjects is dependent on the quality of the studies themselves. Based on our study quality assessment, the risk of confounding within our systematic review was low given that all included studies were purely descriptive and noninterventional. Another source of possible bias stemming from the systematic review is possible variation in subtype classification and functional classification by different raters; however, all included studies relied on the same classification scores, which have been shown to have high interrater reliability [10, 14, 23]. As a result, we do not believe any of the aforementioned limitations substantially undermine our study findings.
A third limitation in our study is that misdiagnosis is possible in the Nepali cohort. However, we believe the risk of this affecting our results is minimal. Among the Nepali cohort, a rigorous effort was made to reasonably rule out secondary causes of neurodevelopmental delay. The diagnosis was made based on relevant historic and physical examination findings that were most consistent with CP after reasonably ruling out other secondary sources of neurodevelopmental delay. We believe the risk of including children with alternative diagnoses in our study is low, and the possibility of this affecting our results is low given that all providers at HRDC are well trained in the evaluation of pediatric neurodevelopmental disorders and a standardized approach to each patient is used to reasonably rule out other secondary sources of neurodevelopmental delay.
A fourth limitation in our study is possible selection bias in how we addressed the second research question. Although our study involved 206 children with CP, only 102 of those met inclusion criteria (spastic CP and age > 2 years) for the comparative analysis to address the second research question. These 102 should be representative of children presenting for care with spastic CP in Nepal but may not be representative of children with any subtype of CP given that children with mixed, ataxic, hypotonic, and unknown subtypes were excluded. As one might expect given the study setting, there were a number of incomplete data points. In the Nepali cohort, the following data were missing: GMFCS level in one patient, MACS level in one patient, and CFCS levels in 18 patients. Missing data may be associated with transfer bias and is an important limitation in this study. In most clinical research settings, patients who have missing data may have worse health status or are not doing as well as fully accounted for. Of note, only one patient had missing data for each of our comparisons of GMFCS and MACS, which allowed us to answer our first and second research questions with a nearly complete data set. Missing data was a larger issue in our CFCS comparison and may therefore be associated with a higher degree of bias. Additionally, given that only one study from the systematic review reported CFCS scores, we had a smaller sample of high-income children for CFCS comparison. This may be associated with a loss of statistical power and a higher rate of β error, although we were still able to identify differences in patients with hemiplegia.
A fifth limitation in our study is that global classification scores in this study (GMFCS, MACS, and CFCS) may lack the sensitivity to assess the subtle benefits that treatment affords. The Functional Mobility Scale (FMS)  could be a possibly more sensitive means of assessing functional impairment in this population in relation to changes after potential intervention. Additionally, many of the interventions used by pediatricians, orthopaedic surgeons, and physiatrists aim to maintain function and prevent decline. Studies of older adolescents and adults in this cohort may be better suited to differentiate these subtleties and changes associated with interventions. Two important data points not recorded in this study were (1) the severity of individual limb involvement; and (2) the degree to which neurologic versus orthopaedic conditions contributed to functional outcomes. In light of these two missing data points, the reader should be cognizant of the fact we were unable to account for the degree of disparity within groups (eg, mild versus severe hemiplegia). Furthermore, we were unable to evaluate whether the disparities in functional severity between our two study cohorts were the result of neurologic or orthopaedic conditions. These factors do not limit our findings but are areas in which additional work can be done to delineate differences in functional severity across socioeconomic groups.
Our first research question involved characterizing the etiologies, motor subtypes, topographic distributions, and functional classifications of a cohort of Nepali children with untreated CP presenting to a large pediatric rehabilitation center in Nepal. To that end, we found that 30% of Nepali children had GMFCS scores of IV or V and 8% had MACS scores of IV or V. We also found that 52% of children had a perinatal etiology and 17% were the result of postnatal etiologies. These findings correspond to other similar studies of children with CP in Africa [3, 17]. In one study of 135 children with CP attending a tertiary hospital in Uganda , spastic hemiplegic or diplegic subtypes comprised 69.6% of all children, whereas that proportion was 50% in our study. The authors used modified versions of the GMFCS and MACS and found that 31% of children had gross motor function corresponding to GMFCS IV or V and 38% of children had fine motor function corresponding to MACS IV or V. In a separate study of 68 children with CP attending a referral hospital in Botswana , 82% of children had spastic CP and 57% of all children had GMFCS scores of IV or V. The authors further found that 28% of patients with CP were either the result of hypoxic events and 25% were associated with infections, leading the authors to conclude that over half of the children with CP had potentially preventable causes. Lastly, a large retrospective single-center study of CP from HRDC found that 79.2% of patients with CP were associated with perinatal or postnatal events, which is similar to our findings . Overall, the wide variability in these findings suggests that rehabilitation centers in low-income areas such as Nepal need to be prepared to manage a wide spectrum of CP manifestations across age ranges. Furthermore, providers in these settings must be trained in the management of CP with the expectation that functional disability may vary widely despite greater similarity in motor impairment. Given the high rate of perinatal and postnatal events contributing to the burden of CP in our study, improvements in antenatal health care and increased availability of safe perinatal and postnatal care would likely prevent many new diagnoses of CP.
To address our second research question, we conducted a systematic review of children with spastic CP in high-income countries and compared those control subjects with a subset of patients in our study with spastic CP. We identified substantial disparities in the motor functional severity of children with spastic hemiplegic CP between the Nepal and high-income settings. These findings suggest that children with CP in low-income settings like Nepal have greater functional disability despite similar or less motor impairment. It is possible that there are relatively fewer Nepali children with profound neurologic impairments because of the lack of access to sophisticated medical services, leading to a lower survival rate for these children in early childhood compared with children with similar degrees of impairment in high-income settings. It is well recognized that although the neurologic impairment in CP remains static, secondary musculoskeletal problems often progress with growth and development. By extension, motor function may decline more rapidly in low-income settings compared with economically developed countries where many services are available to address these impairments and maintain or enhance function. The finding that Nepali children with spastic hemiplegia—a condition with relatively less impairment than spastic diplegia or quadriplegia—had more disability despite similar motor impairment relative to children in high-income countries suggests that untreated early hemiplegic CP leads to greater disability than previously thought. Only two studies to our knowledge have directly compared the differences in CP between low- and high-income settings [6, 9]. Our findings are consistent with a comparison of preschool-aged children with CP in Australia and Bangladesh, which demonstrated that Australian children had better gross motor function and fewer cognitive impairments than Bangladeshi children . Our findings are also consistent with a systematic review of CP in Africa that reported that a larger proportion of children with GMFCS scores of IV or V are seen in African care centers compared with European or North American cohorts . A large, prospective, parallel study conducted in low- and high-income regions simultaneously, either between countries or within a single country, may help to clarify the degree of disparity between disability and impairment across socioeconomic and geographic regions.
In summary, our study found that Nepali children with spastic hemiplegic CP had greater disability despite similar impairment compared with control subjects from high-income countries. These findings suggest that children with CP in low-income settings like Nepal who survive through early childhood, despite limited to no access to health services, may have greater motor disability than their counterparts in high-income countries with similar clinical diagnoses and similar degrees of neurologic impairment. This suggests that there is a substantial opportunity to improve motor function and manual ability with age- and condition-appropriate interventions (such as physical therapy, orthotics, and surgical management). Our study highlights the large population of children with untreated CP in Nepal that likely exists in other low-income regions around the world. This population represents a substantial disease burden that would be amenable to various medical and surgical therapies if they were available. Health system changes and policy initiatives should be designed to improve and expand CP care in low-income regions such as Nepal. Large, cross-sectional, nation- or region-wide studies are needed to determine the degree of disparity between disability and impairment between high- and low-income countries. Tracking differences between treated and untreated children in low-income settings would help to clarify the effect of various therapies in this vulnerable population. Similar studies between different low-income regions (such as South Asia versus sub-Saharan Africa) would be helpful to better elucidate the unique socioeconomic and geographic factors affecting the epidemiology of CP in low-income settings as well as the degree to which medical and surgical interventions may impact functional status on a population level. Additionally, longitudinal studies capturing children as they become young adults will be helpful to elucidate differences in the rates of functional decline in low- versus high-income countries. CP registers in low-income countries, similar to those that currently exist in high-income countries [24, 25], would be helpful in better understanding the epidemiology of CP in resource-limited settings.
1. Banskota B, Shrestha S, Rajbhandari T, Banskota A, Spiegel D. A snapshot of 1001 children presenting with cerebral palsy to a children's disability hospital. J Nepal Heal Res Counc. 2015;13:31–37.
2. Bax M, Goldstein M, Rosenbaum P, Leviton A, Paneth N. Proposed definition and classification of cerebral palsy. Dev Med Child Neurol. 2005:571–576.
3. Bearden DR, Monokwane B, Khurana E, Baier J, Baranov E, Westmoreland K, Mazhani L, Steenhoff AP. Pediatric cerebral palsy in Botswana: etiology, outcomes, and comorbidities. Pediatr Neurol. 2015;59:23–29.
4. Beckung E, Carlsson G, Carlsdotter S, Uvebrant P. The natural history of gross motor development in children with cerebral palsy aged 1 to 15 years. Dev Med Child Neurol. 2007;49:751–756.
5. Belonwu R, Gwarzo G, Adeleke S. Cerebral palsy in Kano, Nigeria–a review. Niger J Med. 2009;18:186–189.
6. Benfer K, Jordan R, Bandaranayake S, Finn C, Ware R, Boyd R. Motor severity in children with cerebral palsy studied in a high-resource and low-resource country. Pediatrics. 2014:e1594–e1602.
7. Carnahan KD, Arner M, Hägglund G. Association between gross motor function (GMFCS) and manual ability (MACS) in children with cerebral palsy. A population-based study of 359 children. BMC Musculoskelet Disord. 2007;8:50.
8. Colver A, Fairhurst C, Pharoah POD. Cerebral palsy. Lancet. 2014;383:1240–1249.
9. Donald KA, Samia P, Kakooza-Mwesige A, Bearden D. Pediatric cerebral palsy in Africa: a systematic review. Semin Pediatr Neurol. 2014;21:30–35.
10. Eliasson A, Krumlinde-Sundholm L, Rösblad B, Beckung E, Arner M, Ohrvall A, Rosenbaum P. The Manual Ability Classification System (MACS) for children with cerebral palsy: scale development and evidence of validity and reliability. Dev Med Child Neurol. 2006;48:549–554.
11. Gladstone M. A review of the incidence and prevalence, types and aetiology of childhood cerebral palsy in resource-poor settings. Ann Trop Paediatr. 2010;30:181–196.
12. Graham H, Harvey A, Rodda J, Nattrass G, Pirpiris M. The Functional Mobility Scale (FMS). J Pediatr Orthop. 2004;24:514–520.
13. Hidecker MJC, Ho NT, Dodge N, Hurvitz EA, Slaughter J, Workinger MS, Kent RD, Rosenbaum P, Lenski M, Messaros BM, Vanderbeek SB, Deroos S, Paneth N. Inter-relationships of functional status in cerebral palsy: analyzing gross motor function, manual ability, and communication function classification systems in children. Dev Med Child Neurol. 2012;54:737–742.
14. Hidecker MJC, Paneth N, Rosenbaum PL, Kent RD, Lillie J, Eulenberg JB, Chester K, Johnson B, Michalsen L, Evatt M, Taylor K. Developing and validating the Communication Function Classification System for individuals with cerebral palsy. Dev Med Child Neurol. 2011;53:704–710.
15. Hollung SJ, Vik T, Wiik R, Bakken IJ, Andersen GL. Completeness and correctness of cerebral palsy diagnoses in two health registers: implications for estimating prevalence. Dev Med Child Neurol. 2017;59:402–406.
16. Howard J, Soo B, Graham HK, Boyd RN, Reid S, Lanigan A, Wolfe R, Reddihough DS. Cerebral palsy in Victoria: motor types, topography and gross motor function. J Paediatr Child Health. 2005;41:479–483.
17. Kakooza-Mwesige A, Forssberg H, Eliasson AC, Tumwine JK. Cerebral palsy in children in Kampala, Uganda: clinical subtypes, motor function and co-morbidities. BMC Res Notes. 2015;8:166.
18. Liu WY, Hou YJ, Wong AMK, Lin PS, Lin YH, Chen CL. Relationships between gross motor functions and health-related quality of life of Taiwanese children with cerebral palsy. Am J Phys Med Rehabil. 2009;88:473–483.
19. Ostensjø S, Carlberg EB, Vøllestad NK. Motor impairments in young children with cerebral palsy: relationship to gross motor function and everyday activities. Dev Med Child Neurol. 2004;46:580–589.
20. Palisano R, Rosenbaum P, Walter S, Russell D, Wood E, Galuppi B. Development and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997;39:214–223.
21. Reddihough DS, Collins KJ. The epidemiology and causes of cerebral palsy. Aust J Physiother. 2003;49:7–12.
22. Romeo DMM, Cioni M, Battaglia LR, Palermo F, Mazzone D. Spectrum of gross motor and cognitive functions in children with cerebral palsy: gender differences. Eur J Paediatr Neurol. 2011;15:53–58.
23. Sellier E, Horber V, Krageloh-Mann I, De La Crz J, Cans C. Interrater reliability study of cerebral palsy diagnosis. neurological subtype and gross motor function. Dev Med Child Neurol. 2012;54:1–2.
24. Smits DW, Gorter JW, Hanna SE, Dallmeijer AJ, van Eck M, Roebroeck ME, Vos RC, Ketelaar M. Longitudinal development of gross motor function among Dutch children and young adults with cerebral palsy: an investigation of motor growth curves. Dev Med Child Neurol. 2013;55:378–384.
25. Surveillance of Cerebral Palsy in Europe. Surveillance of cerebral palsy in Europe : a collaboration of cerebral palsy surveys and registers. Surveillance of Cerebral Palsy in Europe (SCPE). Dev Med Child Neurol. 2000;42:816–824.
26. Voorman JM, Dallmeijer AJ, Knol DL, Lankhorst GJ, Becher JG. Prospective longitudinal study of gross motor function in children with cerebral palsy. Arch Phys Med Rehabil. 2007;88:871–876.
© 2019 Lippincott Williams & Wilkins LWW
28. Zaza S, Wright-De Aguero LK, Briss PA, Truman BI, Hopkins DP, Hennessy MH, Sosin DM, Anderson L, Carande-Kulis VG, Teutsch SM, Pappaioanou M. Data collection instrument and procedure for systematic reviews in the Guide to Community Preventive Services. Task Force on Community Preventive Services. Am J Prev Med. 2000;18:44–74.