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44 active trials for Scoliosis

Scoliosis Tele-Screening Test

A new Scoliosis Tele-Screening Test (STS-Test) was developed by a study group of the "Scoliosis Research and Treatment Association Turkey". It will be sent to the families of schoolchildren by e-mail in Turkey. Participants with moderate and high risk for scoliosis according to the result of this test will be invited to the physical examination by the scoliosis specialists, if it is not possible, they will be evaluated via tele-medicine. Participants with moderate and high risks will be invited to the physical examination to the centers designated as research centers. Families who could not reach these centers will be asked to take pictures of their children according to the given instruction. They will be asked to send this photo to the researchers by e-mail. The researchers will be evaluated the TRACE and Adams' test from the photo and sent their opinions to the parents via e-mail. If this virtual analysis made by the expert suggests a suspicion of scoliosis, it will be recommended to see a specialist as soon as possible. The aim of this study is to evaluate the validity and reliability of this novel scoliosis tele-screening test. A secondary aim is to investigate the coherence of this new test between scoliosis physician and parent when applied to the same child. Specificity, sensitivity, negative predictive value, positive predictive value, and test accuracy will be calculated for the Scoliosis Tele-Screening Test. Correlation between STS-Test and Trace, Adams' test, and physician diagnosis will be analyzed.

Start: November 2020
Prospective Multicenter Evaluation of a New Predictive Model for the Progression of Adolescent Idiopathic Scoliosis

Scoliosis is a three-dimensional deformity affecting the orientation and position of the spine. Locally, the shape of the vertebra is also affected. The most common form is adolescent idiopathic scoliosis (AIS) with a prevalence of 1-3% affecting primarily young adolescent females. AIS can either be treated using a brace and in some cases necessitate surgical correction to prevent progressive deformity. Risk factors for progression include female gender, curve magnitude and location, skeletal maturity and growth velocity. However, these risk factors have been shown to be inconsistent in predicting curve progression. Over the past 6 years, the investigators have developed a predictive model of the final Cobb angle in AIS based on 3D spinal parameters. This analysis was based on a prospective cohort of 195 patients that were enrolled upon their initial visit and followed until maturity. This predictive model has a determination coefficient of 0.702. The proposed new study aims at refining and testing the external validity of this model in a larger cohort. The next step towards using the new model in the clinical setting is to redesign the model and to externally validate the model by measuring the agreement between the new method and the traditional Cobb angle at maturity in a larger multicenter study. The objective of this study is to characterize the risk of scoliosis progression based on local three-dimensional vertebral and pelvic measurements present on initial evaluation. Three-dimensional reconstructions will be derived from stereo-radiographs acquired with a new biplanar low-dose radiographic system installed in all 8 clinical sites (EOS system, EOS-Imaging, Paris). These calibrated radiographs will then be used to reconstruct the vertebrae and intervertebral disks at each level as well as the geometry of the pelvis. A series of local and regional parameters will then be calculated from these 3D reconstructions. Correlation analysis will help determine if intervertebral disk wedging, vertebral wedging, transverse plane rotation or pelvic geometry can be used as early predictors of curve progression in AIS. Identifying a new 3D measure of scoliosis associated with rapid curve progression could help predict which curves need early treatment to prevent further progression. The ultimate goal of this research project will be to validate this new predictive model and finally transfer this new predictive tool in the hands of clinicians treating AIS.

Start: May 2014