Σφακιανάκης Αλέξανδρος
ΩτοΡινοΛαρυγγολόγος
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Τρίτη 17 Οκτωβρίου 2017

A Case-Control Study of Body Composition, Prevalence, and Curve Severity of the Patients With Adolescent Idiopathic Scoliosis in the East Part of China

Publication date: November 2017
Source:Spine Deformity, Volume 5, Issue 6
Author(s): Yu Zheng, Yini Dang, Yan Yang, Ning Sun, Tao Wang, Huabo Li, Lijie Zhang, Chengqi He, M.S. Wong
ObjectiveThe purpose of the study is to investigate the characteristics of prevalence and curve severity in patients with adolescent idiopathic scoliosis (AIS) and the body composition alterations between the patients with AIS and healthy controls.MethodsInformation on the study sample was obtained from a screening database. The AIS cohort was paired with an age- and gender-matched healthy cohort. The stratification of BMI and curve severity was conducted according to the criteria developed by the US Centers for Disease Control and Prevention and the Scoliosis Research Society. The prevalence and curve severity of the patients with AIS were investigated. Multigroup comparison of body composition parameters was conducted according to BMI between the patients with AIS and healthy controls.ResultsA total of 1,202 patients with AIS and an age- and gender-matched cohort were recruited from local schools. The underweight cases had the highest prevalence of AIS and significantly higher Cobb angle compared with the other three BMI subgroups. Although the patients with AIS had lower body weight, body fat mass, percentage of body fat, and fat-free mass compared with healthy controls, converse results were observed in the underweight cases after stratification according to BMI.ConclusionBased on the sporadic body composition of the patients with AIS observed in the current study, it is predictable that the pathophysiological alterations may be different before and after the onset of scoliosis. Well-designed human or animal studies for underweight patients would be helpful to reveal the mechanisms of pathophysiological alterations and better predict the development of AIS.



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