Causal Effects of Motor Control on Gait Kinematics After Orthopedic Surgery in Cerebral Palsy: A Machine-Learning Approach.

ABSTRACT:

Background

Altered motor control is common in cerebral palsy (CP). Understanding how altered motor control affects movement and treatment outcomes is important but challenging due to complex interactions with other neuromuscular impairments. While regression can be used to examine associations between impairments and movement, causal modeling provides a mathematical framework to specify assumed causal relationships, identify covariates that may introduce bias, and test model plausibility. The goal of this research was to quantify the causal effects of altered motor control and other impairments on gait, before and after single-event multi-level orthopedic surgery (SEMLS).

Methods

We evaluated the impact of SEMLS on change in Gait Deviation Index (ΔGDI) between gait analyses.

SUBMITTER: Steele KM 

PROVIDER: S-EPMC9204855 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature