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基于人群的记录监测对脑瘫患儿粗大运动功能分类的可行性和可靠性。

Feasibility and reliability of classifying gross motor function among children with cerebral palsy using population-based record surveillance.

机构信息

Waisman Center, Department of Kinesiology, University of Wisconsin, Madison, WI 53706-1532, USA.

出版信息

Paediatr Perinat Epidemiol. 2011 Jan;25(1):88-96. doi: 10.1111/j.1365-3016.2010.01164.x. Epub 2010 Oct 18.

Abstract

For conditions with wide-ranging consequences, such as cerebral palsy (CP), population-based surveillance provides an estimate of the prevalence of case status but only the broadest understanding of the impact of the condition on children, families or society. Beyond case status, information regarding health, functional skills and participation is necessary to fully appreciate the consequences of the condition. The purpose of this study was to assess the feasibility and reliability of enhancing population-based surveillance by classifying gross motor function (GMF) from information available in medical records of children with CP. We assessed inter-rater reliability of two GMF classification methods, one the Gross Motor Function Classification System (GMFCS) and the other a 3-category classification of walking ability: (1) independently, (2) with handheld mobility device, or (3) limited or none. Two qualified clinicians independently reviewed abstracted evaluations from medical records of 8-year-old children residing in southeast Wisconsin, USA who were identified as having CP (n = 154) through the Centers for Disease Control and Prevention's Autism and Developmental Disabilities Monitoring Network. Ninety per cent (n = 138) of the children with CP had information in the record after age 4 years and 108 (70%) had adequate descriptions of gross motor skills to classify using the GMFCS. Agreement was achieved on 75.0% of the GMFCS ratings (simple kappa = 0.67, 95% confidence interval [95% CI 0.57, 0.78], weighted kappa = 0.83, [95% CI 0.77, 0.89]). Among case children for whom walking ability could be classified (n = 117), approximately half walked independently without devices and one-third had limited or no walking ability. Across walking ability categories, agreement was reached for 94% (simple kappa = 0.90, [95% CI 0.82, 0.96], weighted kappa = 0.94, [95% CI 0.89, 0.98]). Classifying GMF in the context of active records-based surveillance is feasible and reliable. Future surveillance efforts that include functional level among children with cerebral palsy may provide important information for monitoring the impact of the condition for programmatic and policy purposes.

摘要

对于后果广泛的疾病,如脑瘫(CP),基于人群的监测提供了病例状态的流行率估计,但仅能大致了解该疾病对儿童、家庭或社会的影响。除病例状态外,还需要有关健康、功能技能和参与情况的信息,才能全面了解该疾病的后果。本研究旨在评估通过对脑瘫儿童病历中可用信息进行粗大运动功能(GMF)分类,增强基于人群的监测的可行性和可靠性。我们评估了两种 GMF 分类方法的组内可靠性,一种是粗大运动功能分类系统(GMFCS),另一种是步行能力的三分类:(1)独立分类,(2)使用手持移动设备,或(3)受限或无法行走。两名合格的临床医生独立审查了居住在美国威斯康星州东南部的 8 岁儿童的病历摘录评估,这些儿童通过疾病控制和预防中心的自闭症和发育障碍监测网络被确定为患有 CP(n=154)。90%(n=138)的 CP 儿童在 4 岁后有记录中的信息,108 名(70%)有足够的粗大运动技能描述,可以使用 GMFCS 进行分类。GMFCS 评级达成了 75.0%的一致性(简单kappa=0.67,95%置信区间[95%CI 0.57,0.78],加权kappa=0.83,[95%CI 0.77,0.89])。在可以对步行能力进行分类的病例儿童中(n=117),大约一半可以独立行走且无需使用设备,三分之一的儿童步行能力有限或无法行走。在步行能力分类中,达成了 94%的一致性(简单kappa=0.90,[95%CI 0.82,0.96],加权kappa=0.94,[95%CI 0.89,0.98])。在基于主动记录的监测背景下对 GMF 进行分类是可行且可靠的。未来包括脑瘫儿童功能水平的监测工作可能会为计划和政策目的监测该疾病的影响提供重要信息。

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