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Orthopaedic Proceedings
Vol. 91-B, Issue SUPP_III | Pages 484 - 485
1 Sep 2009
Tan K Moe MM Vaithinathan R Wong H
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Introduction: The natural history of idiopathic scoliosis is not well understood. Previous reports focused on characteristics of curve progression pre-defined at 5–6 degrees. However, the absolute curve magnitude at skeletal maturity is more predictive of long-term curve behavior rather than progression of defined magnitude over shorter periods of growth. It is generally agreed that curves < 30 degrees are unlikely to progress after skeletal maturity. Hence, defining factors that influence curve progression to an absolute magnitude of ≥30 degrees at skeletal maturity significantly aids clinical decision-making.

Methods: Of 279 patients with idiopathic scoliosis detected by school screening of 72,699 adolescents, 186 fulfilled the study criteria and were followed up to skeletal maturity. Initial age, gender, pubertal status and initial curve magnitude were used as predictive factors for curve progression to ≥30 degrees at skeletal maturity. Uni and multivariate, logistic regression and receiver operating characteristic (ROC) analysis was performed.

Results: Curve magnitude at first presentation was the most important predictive factor for curve progression to ≥30 degrees at skeletal maturity. An initial curve of 25 degrees had the best ROC of 0.8 with a positive predictive value of 68% and a negative predictive value of 92% for progression to ≥30 degrees at skeletal maturity. The highest risk was a pre-pubertal female < 12 years of age with a Cobb of ≥25 degrees at presentation; with an 82% chance of progression to a Cobb of ≥30 degrees. Probability of progression to ≥30 degrees was defined by 1/(1 + exp (−z)). [z = −3.709 + 0.931(Gender) + 0.825(Puberty) + 3.314(Cobb) + 0.171(Age)].

Conclusions: Initial curve magnitude is the most important independent predictor of long-term curve progression past skeletal maturity. An initial Cobb of 25 degrees is an important threshold. Combined with other factors, we identify patient profiles with high or low risk for progression.