Jennepher Downs1, Ian Torode, Kingsley Wong, Carolyn Ellaway, Elizabeth J Elliott, John Christodoulou, Peter Jacoby, Margaret R Thomson, Maree T Izatt, Geoffrey N Askin, Bruce I McPhee, Corinne Bridge, Peter Cundy, Helen Leonard. 1. *Telethon Kids Institute, The University of Western Australia, Perth, WA, Australia; School of Physiotherapy and Exercise Science, Curtin University, Perth, WA, Australia †Department of Orthopaedics, Royal Children's Hospital, Melbourne, VIC, Australia ‡Telethon Kids Institute, The University of Western Australia, Perth, WA, Australia §Disciplines of Genetic Medicine and Paediatrics and Child Health, The University of Sydney, Western Sydney Genetics Program, The Children's Hospital at Westmead, Sydney, NSW, Australia ¶Discipline of Paediatrics and Child Health, The University of Sydney, The Children's Hospital at Westmead, Sydney, NSW, Australia; The Sydney Children's Hospitals Network (Westmead), Sydney, NSW, Australia ||Department of Radiology, Princess Margaret Hospital for Children, Perth, WA, Australia **Paediatric Spine Research Group, Queensland University of Technology and Mater Health Services, Brisbane, QLD, Australia ††Department of Surgery, University of Queensland, Brisbane, QLD, Australia ‡‡Department of Orthopaedics, The Children's Hospital at Westmead, Sydney, NSW, Australia §§Discipline of Orthopaedics and Trauma, University of Adelaide, Adelaide, SA, Australia; Department of Orthopaedic Surgery, Women's and Children's Hospital, Adelaide, SA, Australia.
Abstract
STUDY DESIGN: Population-based longitudinal observational study. OBJECTIVE: To describe the prevalence of scoliosis in Rett syndrome, structural characteristics and progression, taking into account the influences of age, genotype, and ambulatory status. SUMMARY OF BACKGROUND DATA: Scoliosis is the most common orthopedic comorbidity in Rett syndrome yet very little is known about its natural history and influencing factors such as age, genotype, and ambulatory status. METHODS: The infrastructure of the Australian Rett Syndrome Database was used to identify all cases with confirmed Rett syndrome in Australia and collect data on genotype and walking status. We identified radiological records and described the Cobb angle of each curve. Time to event analysis was used to estimate the median age of onset of scoliosis and the log-rank test to compare by mutation type. Latent class group analysis was used to identify groups for the trajectory of walking status over time and a multilevel linear model used to assess trajectories of scoliosis development by mutation type and walking status. We used a logistic regression model to estimate the probability of developing a scoliosis with a Cobb angle >60° at 16 years in relation to Cobb angle and walking status at 10 years of age. RESULTS: The median age of scoliosis onset was 11 years with earliest onset in those with a p.Arg255 mutation or large deletion. Scoliosis was progressive for all mutation types except for those with the p.Arg306Cys mutation. Scoliosis progression was reduced when there was capacity to walk independently or with assistance. Cobb angle and walking ability at age 10 can be reliably used to identify those who will develop a very severe scoliosis by age 16. CONCLUSION: These data on prognosis of scoliosis inform clinical decision making about the likelihood of progression to very severe scoliosis and the need for surgical management. LEVEL OF EVIDENCE: 4.
STUDY DESIGN: Population-based longitudinal observational study. OBJECTIVE: To describe the prevalence of scoliosis in Rett syndrome, structural characteristics and progression, taking into account the influences of age, genotype, and ambulatory status. SUMMARY OF BACKGROUND DATA: Scoliosis is the most common orthopedic comorbidity in Rett syndrome yet very little is known about its natural history and influencing factors such as age, genotype, and ambulatory status. METHODS: The infrastructure of the Australian Rett Syndrome Database was used to identify all cases with confirmed Rett syndrome in Australia and collect data on genotype and walking status. We identified radiological records and described the Cobb angle of each curve. Time to event analysis was used to estimate the median age of onset of scoliosis and the log-rank test to compare by mutation type. Latent class group analysis was used to identify groups for the trajectory of walking status over time and a multilevel linear model used to assess trajectories of scoliosis development by mutation type and walking status. We used a logistic regression model to estimate the probability of developing a scoliosis with a Cobb angle >60° at 16 years in relation to Cobb angle and walking status at 10 years of age. RESULTS: The median age of scoliosis onset was 11 years with earliest onset in those with a p.Arg255 mutation or large deletion. Scoliosis was progressive for all mutation types except for those with the p.Arg306Cys mutation. Scoliosis progression was reduced when there was capacity to walk independently or with assistance. Cobb angle and walking ability at age 10 can be reliably used to identify those who will develop a very severe scoliosis by age 16. CONCLUSION: These data on prognosis of scoliosis inform clinical decision making about the likelihood of progression to very severe scoliosis and the need for surgical management. LEVEL OF EVIDENCE: 4.
Authors: Jenny Downs; Peter Jacoby; Helen Leonard; Amy Epstein; Nada Murphy; Elise Davis; Dinah Reddihough; Andrew Whitehouse; Katrina Williams Journal: Qual Life Res Date: 2018-11-20 Impact factor: 4.147
Authors: Alberto Romano; Elena Ippolito; Camilla Risoli; Edoardo Malerba; Martina Favetta; Andrea Sancesario; Meir Lotan; Daniel Sender Moran Journal: J Clin Med Date: 2022-01-22 Impact factor: 4.241
Authors: Walter E Kaufmann; Jennifer L Stallworth; David B Everman; Steven A Skinner Journal: Expert Opin Orphan Drugs Date: 2016-09-10 Impact factor: 0.694