High Prevalence of Scoliosis in a Large Cohort of Patients with Prader-Willi Syndrome.
Antonino CrinòMichela ArmandoMarco CrostelliOsvaldo MazzaDario BruzzeseAlessio ConvertinoDanilo FintiniSarah BocchiniSara CicconeAlessandro SartorioGraziano GrugniPublished in: Journal of clinical medicine (2022)
The characteristics of scoliosis were investigated in a large cohort of children and adults with Prader-Willi syndrome (PWS), analysing the role of age, gender, puberty, body mass index (BMI), genotype and growth hormone therapy (GHT) on its onset and severity. A retrospective cross-sectional study was performed in 180 patients with genetically confirmed PWS (96 females), aged 17.6 ± 12 years. Eighty-five subjects (47%) were obese. One hundred and fifty subjects (83.3%) were on GHT, while 30 patients had never been treated. Overall, 150 subjects (83.3%) were affected by scoliosis, 80.2% of children and adolescents and 87.8% of adults. A mild degree of scoliosis was observed in 58 patients (38.7%), moderate in 43 (28.7%) and severe in 49 (32.6%). Median age at diagnosis of scoliosis was 6.3 years, while the severe forms were diagnosed earlier (median age: 3.8 years). The cumulative probability at 5 years of age was equal to 0.403 and almost doubled at 15 years. No significant associations were found between scoliosis and genotype, gender, pubertal stage, GHT and BMI. A corset was prescribed to 75 subjects (50%) at a median age of 7.5 years, while 26 subjects (17.3%) underwent surgery at a median age of 13.1 years. Our data indicate that scoliosis is one of the major concerns for PWS patients that increases with age, and therefore suggest the need for regular systematic monitoring of spinal deformity from paediatric age.
Keyphrases
- end stage renal disease
- body mass index
- growth hormone
- newly diagnosed
- ejection fraction
- peritoneal dialysis
- emergency department
- prognostic factors
- metabolic syndrome
- minimally invasive
- young adults
- adipose tissue
- spinal cord
- stem cells
- spinal cord injury
- physical activity
- deep learning
- machine learning
- case report
- artificial intelligence
- bariatric surgery
- cell therapy
- smoking cessation