Palisano R J, Hanna S E, Rosenbaum P L, Russell D J, Walter S D, Wood E P, Raina P S, Galuppi B E
Department of Rehabilitation Sciences, MCP Hahnemann University, Mail Stop 502, 245 N 15th St, Philadelphia, PA 19102-1192, USA.
Phys Ther. 2000 Oct;80(10):974-85.
Development of gross motor function in children with cerebral palsy (CP) has not been documented. The purposes of this study were to examine a model of gross motor function in children with CP and to apply the model to construct gross motor function curves for each of the 5 levels of the Gross Motor Function Classification System (GMFCS).
A stratified sample of 586 children with CP, 1 to 12 years of age, who reside in Ontario, Canada, and are known to rehabilitation centers participated.
Subjects were classified using the GMFCS, and gross motor function was measured with the Gross Motor Function Measure (GMFM). Four models were examined to construct curves that described the nonlinear relationship between age and gross motor function.
The model in which both the limit parameter (maximum GMFM score) and the rate parameter (rate at which the maximum GMFM score is approached) vary for each GMFCS level explained 83% of the variation in GMFM scores. The predicted maximum GMFM scores differed among the 5 curves (level I=96.8, level II=89.3, level III=61.3, level IV=36.1, and level V=12.9). The rate at which children at level II approached their maximum GMFM score was slower than the rates for levels I and III. The correlation between GMFCS levels and GMFM scores was (.91. Logistic regression, used to estimate the probability that children with CP are able to achieve gross motor milestones based on their GMFM total scores, suggests that distinctions between GMFCS levels are clinically meaningful.
Classification of children with CP based on functional abilities and limitations is predictive of gross motor function, whereas age alone is a poor predictor. Evaluation of gross motor function of children with CP by comparison with children of the same age and GMFCS level has implications for decision making and interpretation of intervention outcomes.
脑瘫(CP)患儿粗大运动功能的发展情况尚无文献记载。本研究的目的是检验CP患儿粗大运动功能模型,并应用该模型为粗大运动功能分类系统(GMFCS)的5个级别构建粗大运动功能曲线。
选取了586名年龄在1至12岁之间、居住在加拿大安大略省且为康复中心所知的CP患儿作为分层样本参与研究。
使用GMFCS对研究对象进行分类,并用粗大运动功能测量量表(GMFM)测量粗大运动功能。检验了4种模型以构建描述年龄与粗大运动功能之间非线性关系的曲线。
在该模型中,每个GMFCS级别下的极限参数(最大GMFM分数)和速率参数(接近最大GMFM分数的速率)均有所不同,该模型解释了GMFM分数变异的83%。5条曲线的预测最大GMFM分数各不相同(I级=96.8,II级=89.3,III级=61.3,IV级=36.1,V级=12.9)。II级患儿接近其最大GMFM分数的速率比I级和III级患儿慢。GMFCS级别与GMFM分数之间的相关性为0.91。逻辑回归用于根据GMFM总分估计CP患儿能够达到粗大运动里程碑的概率,这表明GMFCS级别之间的差异具有临床意义。
基于功能能力和限制对CP患儿进行分类可预测粗大运动功能,而仅年龄则是较差的预测指标。通过与同年龄和GMFCS级别的儿童进行比较来评估CP患儿的粗大运动功能,对决策制定和干预结果的解释具有重要意义。