Causal treatment effects of gait‐analysis‐informed surgery on the Gait Outcomes Assessment List in children with cerebral palsy

AIM: To estimate the effect of surgery on parent-reported gait outcomes as measured using the Gait Outcomes Assessment List (GOAL) questionnaire in a cohort undergoing surgery guided by instrumented gait analysis. METHOD: This was an observational study (n = 146 individuals, 59 females [40%], median age 7 years 10 months [interquartile range 6 years to 10 years 10 months]) classified in Gross Motor Function Classification System levels I-III). The X-Learner was used to estimate the causal treatment effect on treated individuals. The X-Learner is an advanced machine learning framework designed to estimate causal and heterogeneous treatment effects while controlling for confounding and minimizing bias. Changes in parent-reported GOAL domains were compared with objective measures (Gait Deviation Index, walking speed, energy consumption); heterogeneous treatment effects were explored. RESULTS: Significant positive causal treatment effects were observed in gait pattern and appearance, and use of braces and mobility aids (+10 points). Moderate effects were observed for body image and self-esteem, and pain, discomfort, and fatigue (+5 points). Functional domains (activities of daily living and independence; gait function and mobility; physical activities, sports, and recreation) showed only small positive effects or slightly negative effects. Gait pattern and appearance was positively correlated with the Gait Deviation Index; however, GOAL items related to walking speed and fatigue showed no association with laboratory-measured analogs. INTERPRETATION: Surgery guided by instrumented gait analysis substantially improved gait appearance and comfort. Clinicians should manage expectations regarding improvements in functional mobility. The disconnect between subjective patient-reported outcome measures and objective measures highlights the complexity of quantifying a treatment's full impact.