A new risk classification rule for curve progression in adolescent idiopathic scoliosis |
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Authors: | C.F. Lee Daniel Y.T. Fong Kenneth M.C. Cheung Jack C.Y. Cheng Bobby K.W. Ng T.P. Lam Paul S.F. Yip Keith D.K. Luk |
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Affiliation: | 1. School of Nursing, The University of Hong Kong, Pokfulam, Hong Kong SAR, China;2. Department of Orthopaedics and Traumatology, The University of Hong Kong, 5/F Professorial block, Queen Mary Hospital, Pokfulam, Hong Kong SAR, China;3. Department of Orthopaedics and Traumatology, Chinese University of Hong Kong, Hong Kong SAR, China;4. Department of Orthopaedics and Traumatology, Prince of Wales Hospital, Hong Kong SAR, China;5. Department of Social Work and Social Administration, The University of Hong Kong, Hong Kong SAR, China |
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Abstract: |
Background contextPrognostic factors for curve progression of adolescent idiopathic scoliosis (AIS) have been reported previously. There is only one existing rule that classifies AIS patients into two groups by a curvature of 25°.PurposeThis study aimed to develop a more refined risk classification rule for AIS.Study designThis was a retrospective cohort study.Patient sampleWe examined 2,308 untreated AIS patients, aged 10 years and older, who had a Risser sign of 2 and lesser and a curvature less than 30° at presentation.Outcome measuresOutcome was taken as the time to progression to 30°.MethodsPatients' clinical parameters were analyzed by Classification and Regression Tree analysis.ResultsThe new classification rule identified four risk groups of curve progression. Patients with a curvature of 26° and more and less than 18° constituted the highest and lowest risk groups, respectively. The two intermediate groups were identified by the age (11.3 years), menarcheal status, and body height (154 cm).ConclusionsThe risk classification rule only uses information at the first presentation and can aid physicians in deriving an efficient management. |
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Keywords: | Adolescent idiopathic scoliosis Classification and regression tree Classification rule Curve progression Prognostic factors |
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