Context Lack of a valid classification of severity of cerebral palsy and the
absence of longitudinal data on which to base an opinion have made it difficult
to consider prognostic issues accurately.
Objective To describe patterns of gross motor development of children with cerebral
palsy by severity, using longitudinal observations, as a basis for prognostic
counseling with parents and for planning clinical management.
Design Longitudinal cohort study of children with cerebral palsy, stratified
by age and severity of motor function and observed serially for up to 4 years
during the period from 1996 to 2001.
Setting Nineteen publicly funded regional children's ambulatory rehabilitation
programs in Ontario.
Participants A total of 657 children aged 1 to 13 years at study onset, representing
the full spectrum of clinical severity of motor impairment in children with
cerebral palsy.
Main Outcome Measures Severity of cerebral palsy, classified with the 5-level Gross Motor
Function Classification System; function, formally assessed with the Gross
Motor Function Measure (GMFM).
Results Based on a total of 2632 GMFM assessments, 5 distinct motor development
curves were created; these describe important and significant differences
in the rates and limits of gross motor development among children with cerebral
palsy by severity. There is substantial within-stratum variation in gross
motor development.
Conclusions Evidence-based prognostication about gross motor progress in children
with cerebral palsy is now possible, providing parents and clinicians with
a means to plan interventions and to judge progress over time. Further work
is needed to describe motor function of adolescents with cerebral palsy.
Cerebral palsy occurs in every to 2/1000 to 2.5/1000 live births.1 It is " . . . an umbrella term covering a group of
non-progressive, but often changing, motor impairment syndromes secondary
to lesions or anomalies of the brain arising in the early stages of development."2 Thus, whatever additional developmental difficulties
individuals with cerebral palsy might have as a result of impairment of the
developing central nervous system, the hallmark of these conditions is a disorder
in the development of gross motor function.
When first told that their child has cerebral palsy (generally in the
child's first 18 months of life), parents usually want to know its severity
and whether their child will ever be able to walk. The evidence on which to
base answers was, until recently, limited to observations about the association
between constellations of reflex and early motor skills at age 2 years and
walking at a later age3; or on motor milestones
such as sitting between the ages of 2 and 4 years and walking at a later age.
However, the findings based on even these simple markers are conflicting.4,5 Crude estimates of the probability
of being able to walk 10 steps unaided at or after age 5 years vary for different
clinical types of cerebral palsy.6 These observations
derive from clinic samples and are likely not representative of the entire
population of children with cerebral palsy.
Cross-sectional studies of motor behavior in children with cerebral
palsy have demonstrated characteristic patterns of motor development according
to severity of the condition,7 although the
descriptions of severity previously used have been crude and unsystematic.
The motor growth curves created by Palisano et al,8
which are based on cross-sectional population data stratified by severity
using the validated Gross Motor Function Classification System (GMFCS) for
cerebral palsy,9 are an important improvement.
This article describes patterns of gross motor development of a community-based
sample of children with cerebral palsy followed up prospectively. We used
the GMFCS to longitudinally create curves charting the rates and limits of
motor function by severity of motor impairment. These curves increase the
prognostic information available to families and clinicians considerably.
This study was made possible through a partnership between the CanChild Centre for Childhood Disability Research at McMaster
University and the 19 publicly funded regional ambulatory children's rehabilitation
programs in Ontario. These programs provide a range of developmental therapies
and services (predominantly physical, occupational, speech-language, and recreational
therapies) by professionals trained and experienced in assessment and management
of childhood disability. Because the centers are publicly funded, each program
serves the majority of eligible children in its area.
The sampling frame was created in early 1996 with 18 of the 19 centers
and 1 hospital-based therapy program in a community without a regional center.
Each center identified all the children who had been diagnosed as having cerebral
palsy and who had been born in or after 1986. Children with neuromotor findings
consistent with cerebral palsy, such as spasticity or reflex abnormalities,
who had not been diagnosed as having cerebral palsy were included in the study.
Children with other neuromotor disabilities, such as spina bifida or muscle
diseases, were excluded. Children were also excluded if they had selective
dorsal rhizotomy,10 had received botulinum
toxin injections in the lower limbs for spasticity management,11,12
or were receiving intrathecal baclofen.13 At
the time the study started, it was not yet known how these relatively new
interventions might affect gross motor function. None of these interventions
was readily available in Ontario at the time of the study. To the best of
our knowledge, no children were receiving hyperbaric oxygen therapy, an intervention
that has since been shown to be of no added value for children with cerebral
palsy.14
Sample size calculations were performed using data from Scrutton and
Rosenbaum.7 Based on the Gross Motor Function
Measure-88 (GMFM-88) and estimated score limits for a 10-year-old in each
GMFCS stratum (98-100, 90-95, 60-80, 12-50 and <10), a sample of 150 children
per GMFCS stratum would provide a power of 0.85.
Of the sampling frame containing 2108 children, 1304 were stratified
by age and GMFCS level and were randomly selected. Our target was 15 children
in each combination of birth year and severity level. An initial sample was
drawn from children with known severity level. We also drew a second random
sample from those children whose severity level was initially unknown. Based
on the required quota for each stratum, the centers established the severity
level for a specified set of children. Once the level of a child in this set
became known, he/she was added to the study sample for the appropriate stratum
(Table 1).
Each of the sample sizes was calculated to achieve equal sampling fractions
for children with initially known or unknown severity. We oversampled for
each age and GMFCS stratum to try to achieve at least 15 children per predefined
cell. A total of 366 children were ineligible or unavailable for various reasons.
Of the remaining 938 children, 721 (77%) families consented and 682 (94.5%)
provided data; 657 had fully useable data, after excluding children without
cerebral palsy (Figure 1). The children
ranged in age from 1 to 13 years at study entry.
At the first assessment, therapists reported the distribution of the
child's cerebral palsy as it was reported in the child's clinic chart (hemisyndrome,
diplegia, triplegia, or quadriplegia). They also included any terms that had
been used to describe the diagnosis. When no formal diagnosis had been given
to the child, therapists were asked whether the child's motor behavior and
patterns "looked like" cerebral palsy. Males (n = 369) comprised 56% of the
group. Topographical distribution of cerebral palsy included 217 (33.0%) leg-dominant
children, 62 (9.4%) 3 limb-dominant, 263 (40.0%) 4 limb-dominant, 98 (15.3
%) hemisyndromes, and 17 (2.8%) unknown.
Severity of cerebral palsy was based solely on GMFCS level, which is
a reliable and valid system that classifies children with cerebral palsy by
their age-specific gross motor activity.8,9,15
The GMFCS describes the major functional characteristics of children with
cerebral palsy in each level within the following age windows: prior to second
birthday; between age 2 years and fourth birthday; between age 4 years and
sixth birthday; and between ages 6 and 12 years.
The outlines the main
abilities of children aged 6 to 12 years in each GMFCS level. Use of the GMFCS
requires familiarity with the child, but is not a test and requires no formal
training.
Motor function was assessed with the GMFM.16
The GMFM is a widely used, criterion-referenced, clinical observation tool
with a scale from 0-100 that was developed and validated for children with
cerebral palsy or Down syndrome.17 It has excellent
reliability and demonstrated ability to evaluate meaningful change in gross
motor function in children diagnosed as having cerebral palsy.16,18,19
The GMFM was not designed to compare the function of children with cerebral
palsy to typically developing children. It measures gross motor function in
lying and rolling, crawling and kneeling, sitting, standing, and walk-run-jump
activities. It can be used with any child or adolescent diagnosed as having
cerebral palsy. It focuses on the extent of achievement of a variety of gross
motor activities (mainly mobility skills and activities requiring postural
control such as sitting, kneeling, and standing on 1 foot) that a typically
developing 5-year-old could accomplish. For data analyses, we used scores
derived from the GMFM-66, a measure with interval levels that was developed
by Rasch analysis of the original 88-item scale (GMFM-88).18-20
Procedures and Quality Control
The ethics review boards of Hamilton Health Sciences Corp, the Bloorview
MacMillan Centre (Toronto, Ontario), and the Thames Valley Children's Centre
(London, Ontario) approved the study. It was centrally managed at CanChild, with a site coordinator in each center, who was responsible
for the day-to-day management of data collection. Before beginning to assess
children, all therapists were trained on the administration and scoring of
the GMFM.21 Their reliability was assessed
against a criterion tape at the end of training and reassessed annually over
the 4 years of data collection to ensure that they continued to score the
measure reliably.
To track individual gross motor development, children younger than 6
years were assessed with the GMFM-66 approximately every 6 months, and older
children were assessed every 9 to 12 months. This timing was based on previous
observations that led us to expect more rapid change in gross motor development
in the preschool years.8 On each occasion,
therapists were also asked to classify the child's current GMFCS level.
To estimate the parameters of a nonlinear model of motor development,
nonlinear mixed-effects modelling22 was used
for children in each of the 5 GMFCS levels. Importantly, in addition to describing
the average pattern of development in each level, this analysis allows for
orderly variations in the patterns of development. The degree of individual
variations was estimated and individual motor development curves were fitted
for each child. The model has 2 parameters—the estimated rate and limit
of motor development—that have straightforward clinical interpretations.
The model assumes that children have GMFM-66 scores near zero at birth. Subsequently,
children are expected to acquire gross motor abilities rapidly, with the rate
of development slowing as they approach the limit of their potential.7,8 Based on clinical experience, the rate
and limit of motor development are expected to vary substantially. Initial
inspection of the data suggested that this model might fit these children
well.
Over the course of the study, 657 children had a total of 2632 GMFM
assessments, or an average of 4 observations per child. From these data, 5
distinct and significantly different motor growth curves, which described
patterns of gross motor development by GMFCS level, were created (Figure 2 and Figure 3). Parameter estimates for the average GMFM-66 curve in
each level are reported in Table 2.
As expected, the estimated limit of development decreased as severity of impairment
increased. Confidence intervals (95% CIs) for the limit parameters are tight
and confirm that each level of severity is significantly different from the
adjacent levels. For clinical purposes, the estimated variances in limit for
each level have been used to construct intervals that are expected to encompass
50% of the limits in the population. These individual differences in limit
are plotted in Figure 2. The 95%
CIs are conceptually different from and unrelated to the 50% bands. The 95%
CIs provide an estimate of the precision of the point estimates of the mean
limits, while the 50% bands provide clinical information about the degree
to which individuals are expected to vary around that mean.
To enhance interpretation, the rate parameters from the nonlinear growth
models have been transformed to age-90, the age in years by which children
are expected to reach 90% of their motor development potential. Smaller values
(in years) indicate faster progress toward motor development limits. Age-90
data in Table 2 suggest a trend
for a faster progression to the limit as severity of impairment increases.
However, the 95% CIs indicate that children in levels III through V progress
significantly faster than children in level I, but children in level II do
not progress faster than children in level I. An earlier (younger) age-90
does not indicate "better" developmental progress—only that a child
is closer to his/her limit, whatever that limit may be. To aid in clinical
interpretation, the variation in age-90 (50% range) is reported as the interval
expected to encompass 50% of age-90 in the population. Positive correlations
between limit and age-90 suggest that there is a tendency for children with
lower motor development potential to reach their limit more quickly (ie, have
a lower age-90) than children with higher potentials, even within GMFCS levels.
The estimates of the average patterns of motor development in each stratum
and the degree of individual differences around them (Table 2) have straightforward clinical interpretations when combined
with knowledge of children's initial GMFCS level. Thus, for example, the model
predicts that the expected limit of a child's potential in level III is 54.3
points on the GMFM-66 (ie, the level III mean), with 50% of children's limits
being between 48.5 and 60.0 points. In terms of the rate of development, children
in level III are expected to have reached about 90% of their potential by
about age 3.7 years. The positive correlation between limit and age-90 for
children in level III suggests that a young child, who is performing at a
higher level than expected on the basis of the average level III curve, is
likely to level off sooner than his/her peers. A substantial amount of prognostic
information can thus be derived on the basis of a single GMFM-66 assessment.
The model incorporates possible classification errors within the GMFCS because
these findings are based on children's initial classification with no effort
to verify the child's "true" level if that happens to have changed over time.
The residual SDs in Table 2
provide an indication of the degree to which the model fits for each GMFCS
level, and are a measure of how much each child's GMFM-66 score can be expected
to vary around their true ability over time. There is a suggestion in Table 2 that SDs from the model predictions
are larger in levels I and V than the middle levels. The raw residual SDs
were plotted against predicted values and against children's ages in each
GMFCS stratum to address the adequacy of the model fit. This revealed no tendency
for the model errors to be systematically related to predicted value or age.
The residual SDs in Table 2 suggest
that the size of the expected within-child errors may be related to the GMFCS,
which supports the use of separate models for each stratum.
To illustrate the clinical interpretation of these curves, 4 selected
GMFM-66 items have been identified on the ordinate of the curves (Figure 3). The GMFM item 21 (diamond A) assesses
whether a child can lift and maintain his/her head in a vertical position
with trunk support by a therapist while sitting. A child with a GMFM-66 score
of 16 would be expected to have a 50% chance of achieving this task.8 This is something that would be seen relatively early
in life among children in GMFCS levels I through IV, and only (on average)
at about age 2 years in children in level V. The GMFM-66 item 24 (diamond
B) assesses whether when in a sitting position on a mat, a child can maintain
sitting unsupported by his/her arms for 3 seconds. Children would be expected
to have a 50% chance of being successful at this task at an average GMFM-66
score of 32 points. This task would be relatively easily achieved by children
in GMFCS levels I through III, much later in children in level IV, and rarely
by children in level V. The GMFM-66 item 69 (diamond C) measures a child's
ability to walk forward 10 steps unsupported, a task associated with a mean
GMFM-66 score of 56, and achievable (50% chance) predominantly by children
in GMFCS levels I and II. Finally, the task of walking down 4 steps alternating
feet with arms free, which is GMFM-66 item 87 (diamond D), will be observed
at an average GMFM-66 score of 81 points, and probably only by children in
GMFCS level I.
The patterns of motor development in children with cerebral palsy are
the first to be based on longitudinal observations. They were created using
a valid classification system of functional abilities and limitations of children
with cerebral palsy and a systematic evaluation of gross motor function with
an evaluative clinical instrument (GMFM). Data were collected from a large
stratified random sample of children diagnosed as having cerebral palsy, who
were receiving a range of accepted medical, orthopedic, and developmental
therapy services. We believe the sample is representative of the population
of children with cerebral palsy in Ontario, with results generalizable to
populations elsewhere receiving similar types of mixed developmental therapies.
It is not clear whether children who are currently receiving newer therapeutic
modalities (selective dorsal rhizotomy,10 botulinum
toxin,11,12 intrathecal baclofen13) might perform substantially better than the children
involved in this study, and if so, whether this would limit the generalizability
of our findings. It should be noted that all of these recent therapeutic innovations
are used only with highly selected subgroups of children with cerebral palsy,
and that even the best results apply only to those specific groups and not
to the whole population.
For example, following selective dorsal rhizotomy, the reported improvements
in gross motor function are statistically significantly greater than those
seen with physical therapy alone, but the actual measured GMFM-66 changes
are still quite modest (mean measured added benefit in GMFM-66 change scores
in the [selective dorsal rhizotomy plus therapy] group was 2.6)23
and are unlikely to be associated with a change of GMFCS level. Similarly,
while the effects of botulinum toxin injections have been well described,11,12 the mean measured change on the GMFM-88
was in the range of about 3%. Intrathecal baclofen is increasingly being used
for the management of spasticity in individuals with cerebral palsy. Although
individuals have shown improvements in spasticity and pain relief after receiving
intrathecal baclofen, its effect on measured change in gross motor function
is limited.24 These comments are in no way
meant to minimize the effectiveness of these interventions for specific subgroups
of children with cerebral palsy, but rather to note that at this time these
interventions do not, on average, have a major impact on function as assessed
with the GMFM.
We expect that the findings from our study will help parents understand
the outlook for their child's gross motor function, because an evidence-based
estimate can now be made about gross motor prognosis based on age and GMFCS
level. The data should prove equally useful to clinicians planning interventions,
enabling clinicians and parents to make informed decisions about the most
appropriate therapy goals for children. The curves also provide an effective
way to assess whether a child's motor progress is consistent with patterns
observed in children of similar age and severity.
Because the GMFM-66 assessments of children reported here were specifically
made without the use of aids, such as walkers or crutches, these patterns
of gross motor development probably represent the lower limit of what children
in each level can, on average, accomplish in gross motor function. Furthermore,
the curves appear to reach plateaus by about age 7 years. Children, on average,
reach about 90% of their motor function (as measured by the GMFM-66) by around
age 5 years or younger, depending on their GMFCS level.
However, the curves reveal nothing about the quality of motor control
used to accomplish the activities, which is an aspect of motor development
that appears to emerge later in childhood.25
Nor do the curves show how children apply their motor function in the context
of activity or participation in daily life, as formulated in the World Health
Organization's recent International Classification of Functioning,
Disability and Health model.26 Furthermore,
the GMFM-66 assesses observed independent achievement of motor function tasks,
but does not (at least in this study) attempt to evaluate the ways in which
children's function is performed with or might be enhanced through the addition
of augmentative and technical interventions such as aids, orthoses, or the
use of powered mobility to increase day-to-day independence.27
Children may change and improve their gross motor performance over the developing
years through increased balance, stamina, energy efficiency, and quality of
motor control—all features that are important and should be evaluated,
but are beyond the scope of the GMFM-66.
Thus, it is extremely important that parents, physicians, therapists,
program managers, third-party payers, and other decision makers not assume
further therapy is unhelpful or unnecessary when the curves appear to level
off. Continuing efforts should be made to address ways both to increase independent
activity and to promote participation of children with disabilities, as well
as to address secondary impairments that may arise. It should also be remembered
that the children in the present study were receiving a range of contemporary
developmental therapy services that we believe are representative of the therapies
provided in the Western world. It is likely that as new therapies emerge,
patterns of motor development in children diagnosed as having cerebral palsy
may change and modifications to these models will be needed. We believe that
the motor development curves will have important applications for the evaluation
of specific interventions by permitting analysis of the extent to which these
interventions improve a child's gross motor function beyond what is predicted
based on age and GMFCS level.
Based on our previous work, an assumption of this study was that GMFCS
levels are stable over time, making prognostication meaningful. Wood and Rosenbaum15 demonstrated an overall reliability of GMFCS over
time (from age <2 years to >12 years) of 0.79, with higher values when
one tracked the consistency of GMFCS levels from age 2 to 4 years to age 12
years (0.82) or from age 4 to 6 years to age 12 years (0.87). Children in
our study were allocated to a GMFCS level at entry to the study, and data
were analyzed according to that initial assignment. This was done to reflect
the clinical reality that parents seek prognostication about their child's
outlook from the time the disability is first diagnosed. As development progresses,
children may be reclassified. If this occurs, it is important for clinicians
to reformulate the prognosis, based on the most recent assessment of a child's
motor activities and GMFCS stratum.
The present data can be used to explore the creation of motor growth
curves for children with different distributions of cerebral palsy, as has
been done by others.28 These analyses are currently
under way. However, there is reason to believe that in the absence of a systematic,
protocol-driven classification of the topographical components of cerebral
palsy, reliability of such categorizations is relatively poor.29
For the same reason, we have not yet analyzed the findings according to the
form of motor impairment (spastic, dystonic, ataxic, or mixed), which has
been described elsewhere.30 In fact, approximately
76% of the children in this study were described as having spastic cerebral
palsy, with much smaller numbers in the other subgroups.
The curves describe patterns for groups of children. There is within-stratum
variation in motor development, which is based on other aspects of each child's
functional status.31,32 More research
is needed to understand, and to be able to measure accurately, the impact
of factors such as a child's visual ability, cognitive capacity, motivation,
parental encouragement, and the contribution of therapies that might be associated
with individual variation in progress. It will also be important to continue
to follow the motor development of these children through adolescence, because
much remains to be learned about the impact of puberty and the demands of
secondary school on motor function and activity of adolescents with cerebral
palsy. Finally, we expect that research by our group and others will provide
validation of the accuracy and utility of these curves.
Box. Gross Motor Function Classification System Levels for Children With Cerebral Palsy Between the Ages of 6 and 12
Years
Level I
Walks without restrictions; limitations in more advanced gross motor
skills
Level II
Walks without assistive devices; limitations in walking outdoors and
in the community
Level III
Walks with assistive mobility devices; limitations in walking outdoors
and in the community
Level IV
Self-mobility with limitations; children are transported or use power mobility outdoors and in the community
Level V
Self-mobility is severely limited even with the use of assistive technology
1.Stanley FJ, Blair E, Alberman E. Cerebral Palsies: Epidemiology & Causal Pathways. London, England: Mac Keith Press; 2000:29.
2.Mutch LW, Alberman E, Hagberg B, Kodama K, Velickovic MV. Cerebral palsy epidemiology.
Dev Med Child Neurol.1992;34:547-555.Google Scholar 3.Bleck EE. Locomotor prognosis in cerebral palsy.
Dev Med Child Neurol.1975;17:18-25.Google Scholar 4.Molnar GE, Gordon SV. Predictive value of clinical signs for early prognostication of motor
function in cerebral palsy.
Arch Phys Med Rehabil.1974;57:153-158.Google Scholar 5.Watt JM, Robertson CM, Grace MG. Early prognosis for ambulation of neonatal intensive care survivors
with cerebral palsy.
Dev Med Child Neurol.1989;31:766-773.Google Scholar 6.Crothers B, Paine RS. Natural History of Cerebral Palsy. Cambridge, Mass: Harvard University Press; 1959.
7.Scrutton D, Rosenbaum PL. The locomotor development of children with cerebral palsy. In: Connolly K, Forssberg H, eds. Neurophysiology
and Neuropsychology of Motor Development. London: Mac Keith Press;
1997:101-123.
8.Palisano RJ, Hanna SE, Rosenbaum PL.
et al. Validation of a model of gross motor function for children with cerebral
palsy.
Phys Ther.2000;80:974-985.Google Scholar 9.Palisano RJ, Rosenbaum PL, Walter SD, Russell DJ, Wood EP, Galuppi BE. Development and reliability of a system to classify gross motor function
in children with cerebral palsy.
Dev Med Child Neurol.1997;39:214-223.Google Scholar 10.Steinbok P. Outcomes after selective dorsal rhizotomy for spastic cerebral palsy.
Childs Nerv Syst.2001;17:1-18.Google Scholar 11.Mall V, Heinen F, Kirschner J.
et al. Evaluation of botulinum toxin.
J Child Neurol.2000;15:214-217.Google Scholar 12.Kirschner J, Linder M, Berweck S.
et al. Treatment of
pes equines in cerebral palsy
with botulinum toxin A and functional benefit according to gross motor function
measure.
Eur J Neurol.In press.Google Scholar 13.Almeida GL, Campbell SK, Girolami G, Penn R, Corcos DM. Multidimensional assessment of motor function in a child with cerebral
palsy following intrathecal administration of baclofen.
Phys Ther.1997;77:751-764.Google Scholar 14.Collet JP, Vanasse M, Marois P.
et al. Hyperbaric oxygen for children with cerebral palsy.
Lancet.2001;357:582-586.Google Scholar 15.Wood EP, Rosenbaum PL. The Gross Motor Function Classification System for cerebral palsy.
Dev Med Child Neurol.2000;42:292-296.Google Scholar 16.Russell DJ, Rosenbaum PL, Cadman DT.
et al. The gross motor function measure.
Dev Med Child Neurol.1989;31:341-352.Google Scholar 17.Russell D, Palisano R, Walter S.
et al. Evaluating motor function in children with Down syndrome.
Dev Med Child Neurol.1998;40:693-701.Google Scholar 18.Russell DJ, Avery L, Rosenbaum PR, Raina P, Walter SD, Palisano RJ. Improved scaling of the gross motor function measure for children with
cerebral palsy.
Phys Ther.2000;80:873-885.Google Scholar 19.Russell DJ, Rosenbaum PL, Avery L, Lane M. Gross Motor Function Measure (GMFM-66 and GMFM-88)
User's Manual: Clinics in Developmental Medicine, No. 159. London, England: Mac Keith Press; 2002.
20.Avery L, Russell D, Raina P, Rosenbaum P, Walter S. Rasch analysis of the gross motor function measure.
Arch Phys Med Rehabil.In press.Google Scholar 21.Russell DJ, Rosenbaum PL, Lane M.
et al. Training users in the gross motor function measure.
Phys Ther.1994;74:630-636.Google Scholar 22.Pinheiro JC, Bates DM. Mixed Effects Models in S and S-PLUS. New York, NY: Springer; 2000.
23.McLaughlin J, Bjornson K, Temkin N.
et al. Selective dorsal rhizotomy: meta-analysis of three randomized controlled
trials.
Dev Med Child Neurol.2002;44:17-25.Google Scholar 24.Butler C, Campbell S. Evidence of the effects of intrathecal baclofen for spastic and dystonic
cerebral palsy: AACPDM Treatment Outcomes Committee Review Panel.
Dev Med Child Neurol.2000;42:634-645.Google Scholar 25.Boyce W, Gowland C, Rosenbaum P.
et al. The gross motor performance measure: validity and responsiveness of
a measure of quality of movement.
Phys Ther.1995;75:603-613.Google Scholar 26.World Health Organization.
International Classification of Functioning, Disability
and Health. Geneva, Switzerland: World Health Organization; 2001. Available at: http://www3.who.int/icf/icftemplate.cfm. Accessibility verified August
26, 2002. 27.Butler C. Augmentative mobility: why do it?
Phys Med Rehabil Clin North Am.1991;2:801-816.Google Scholar 28.Beckung E, Carlsson G, Uvebrant P, Carlsdottor Not Available. The natural history of gross motor function in children with cerebral
palsy in western Sweden.
Dev Med Child Neurol.2001;43(suppl 89):27.Google Scholar 29.Blair E, Stanley F. Interobserver agreement in the classsification of cerebral palsy.
Dev Med Child Neurol.1985;27:615-622.Google Scholar 30.Cans C. Surveillance of cerebral palsy in Europe: a collaboration of cerebral
palsy surveys and registers.
Dev Med Child Neurol.2000;42:816-824.Google Scholar 31.Kennes J, Rosenbaum PL, Hanna SE.
et al. Health status of school-aged children with cerebral palsy.
Dev Med Child Neurol.2002;44:240-247.Google Scholar 32.Bartlett DJ, Palisano RJ. A multivariate model of determinants of motor change for children with
cerebral palsy.
Phys Ther.2000;80:598-614.Google Scholar