Identification of Predictors for Progression of Scoliosis in Rett Syndrome

J. E. Weeda; S. M.J. van Kuijk; M. P. van den Berg; C. H.G. Bastiaenen; H. E. Borst; L. W. van Rhijn; R. A. de Bie

doi:10.1080/17518423.2024.2365794

Identification of Predictors for Progression of Scoliosis in Rett Syndrome

J. E. Weeda^*, S. M.J. van Kuijk, M. P. van den Berg, C. H.G. Bastiaenen, H. E. Borst, L. W. van Rhijn, R. A. de Bie

^*Corresponding author for this work

Regenerative Medicine and Stem Cells

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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	22 Jun 2024
DOIs	https://doi.org/10.1080/17518423.2024.2365794
Publication status	Published - Jul 2024

Keywords

Mecp2 mutations
prediction, neuromuscular diseases
Rett syndrome
scoliosis

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10.1080/17518423.2024.2365794Licence: CC BY-NC-ND

Identification of Predictors for Progression of Scoliosis in Rett SyndromeFinal published version, 1.1 MBLicence: CC BY-NC-ND

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title = "Identification of Predictors for Progression of Scoliosis in Rett Syndrome",

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.",

keywords = "Mecp2 mutations, prediction, neuromuscular diseases, Rett syndrome, scoliosis",

author = "Weeda, {J. E.} and {van Kuijk}, {S. M.J.} and {van den Berg}, {M. P.} and Bastiaenen, {C. H.G.} and Borst, {H. E.} and {van Rhijn}, {L. W.} and {de Bie}, {R. A.}",

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year = "2024",

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doi = "10.1080/17518423.2024.2365794",

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AU - Weeda, J. E.

AU - van Kuijk, S. M.J.

AU - van den Berg, M. P.

AU - Bastiaenen, C. H.G.

AU - Borst, H. E.

AU - van Rhijn, L. W.

AU - de Bie, R. A.

PY - 2024/7

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AB - 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.

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Identification of Predictors for Progression of Scoliosis in Rett Syndrome

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Keywords

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