AOCCN2017

講演情報

Poster Presentation

[P2-1~135] Poster Presentation 2

2017年5月12日(金) 10:00 〜 15:40 Poster Room A (1F Navis A・B・C)

[P2-58] Factors associated with the outcomes in activity in daily living in children with cerebral palsy

Chia-ling CHEN1, 2 (1.Physical Medicine and Rehabilitation, Chang Gung Memorial Hospital-Linkou, Taiwan., 2.Graduate Institute of Early Intervention, Chang Gung University, Taiwan)

[Introduction]: Enhancing the outcomes in the Activity in daily living (ADL) is an important goal for neurorehabilitation in children with cerebral palsy (CP). Identifying the factors in predicting the outcomes in ADL may allow clinician to early predict the ADL outcome. This study is to identify the factors associated with the outcome in the ADL in children with CP.
[Methodology]: Fifty-six children with CP (3-12 years) were enrolled from an outpatient clinic of a tertiary teaching hospital in this study. Potential predictors were age, sex, Gross Motor Function Classification System (GMFCS) level, Manual Ability Classification System (MACS) level, and cognition, speech, and self-care abilities measured by Comprehensive Developmental Inventory for Infant and Toddlers (CDIIT). ADL outcome was assessed by pediatric functional independence measure (WeeFIM), which consists of Self-care, Mobility, and Cognition domains. A regression analyses was used to establish the relationships between the potential predictors and outcomes. A p<0.05 is considered as significant differences.
[Results]: Regression analyses showed the predicted ADL outcomes in various domains were different (adjusted r2 = 0.55-0.61, p <0.01). Age predicted the outcomes in all domains of WF. GMFCS levels predicted the ADL outcomes in Mobility domains. MACS levels predicted the ADL outcomes in Self-Care, Cognition, and Total domains. Self-care abilities predicted the ADL outcomes in Self-Care, Mobility, and Total domains. The cognition abilities predicted the ADL outcomes in the Cognition and Total domain.
[Conclusions]: The findings may suggest different factor combinations predicted ADL outcomes in various domains. The data provided in this study may allow clinician to identify the children with CP who benefit most from therapy on ADL and plan the treatment strategies for these children.