Abstract
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 (>10 (Formula presented.) Cobb 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.
| Original language | English |
|---|---|
| Pages (from-to) | 126-133 |
| Number of pages | 8 |
| Journal | Developmental Neurorehabilitation |
| Volume | 27 |
| Issue number | 3-4 |
| Early online date | 1 Jun 2024 |
| DOIs | |
| Publication status | Published - 2024 |
Keywords
- Mecp2 mutations
- prediction, neuromuscular diseases
- Rett syndrome
- scoliosis
- MANAGEMENT
- PROFILE
- FUSION
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