Rett syndrome is a neurodevelopmental disorder in which scoliosis is a common orthopedic complication. This explorative study aims to identify predictors for rapid progression of scoliosis in Rett syndrome to enable variable selection for future prediction model development. A univariable logistic regression model was used to identify variables that discriminate between individuals with and without rapid progression of scoliosis (>10Cobb angle/6 months) based on multi-center data. Predictors were identified using univariable logistic regression with OR (95% CI) and AUC (95% CI). Age at inclusion, Cobb angle at baseline and epilepsy have the highest discriminative ability for rapid progression of scoliosis in Rett syndrome.
Keywords: Mecp2 mutations; Rett syndrome; prediction, neuromuscular diseases; scoliosis.