Ki Hyuk Sung, MD Department of Orthopaedic Surgery Seoul National University Bundang Hospital

1. Rate of correction after asymmetrical physeal suppression in valgus deformity: Analysis using a Linear mixed model application Ki Hyuk Sung, MD Department of Orthopaedic Surgery Seoul National University Bundang Hospital

2. Introduction • Coronal angular deformity of the lower limb is a common finding in growing children • Permanent (irreversible) hemiepiphysiodesis • Temporary (reversible) hemiepiphysiodesis using staples, percutaneous screws, or a tension band plate (eight-plate)

6. Introduction • Measuring the rate of correction is necessary to predict the time to end point • The rate of angular correction has been calculated simply by averaging. • Other factors (age, surgical method, direction of deformity, etiology, physis) must be considered while estimating the rate of correction

7. Introduction • A linear mixed model (LMM) is useful in settings where multiple correlated measurements are made on the same statistical units • LMM consists of fixed effects and random effects • Estimation of the correction rate by using a mixed model application may confer more practical information to clinicians

8. Purpose • To estimate the rate of angular correction after asymmetrical physeal suppression • To analyze the factors that influence the rate of correction by using a linear mixed model application

9. Material and methods

10. Inclusion criteria • Patients with valgus angular deformity of the lower limb who underwent asymmetrical physeal suppression • A minimum follow-up of 3 months

11. Exclusion criteria • Patients who visited our hospital less than two times • Patients who had inadequate preoperative or postoperative radiographs available for review • Patients who underwent any other bony procedures such as an osteotomy

12. Radiographic measurements

13. Building a linear mixed model • Three groups • Distal femoral, proximal tibial, and distal tibial • The rate of angular correction was adjusted by multiple factors by using LMM • Age, gender, and surgical method as the fixed effects • Each subject as the random effect

14. Individual pattern of correction rate

16. Building a linear mixed model • The estimates were fitted using the restricted maximum likelihood estimation (REML) method • The final model • Age and surgical method specific rate • Sex and surgical method specific intercept

17. Statistical Methods • Univariate analysis • LMM was used to model the correction rates and assess covariate effects. • Multivariate analysis • For the final model to examine the significantly contributing factor to the rate of valgus deformity correction • R (Version 2.13.1) using nlme package

18. Results

19. Patients’Demographics

20. Univariate analysis of the correction rate for distal femur

21. Univariate analysis of the correction rate for proximal tibia

22. Univariate analysis of the correction rate for distal tibia

23. Multivariate analysis of the correction rate for distal femur

24. Multivariate analysis of the correction rate for proximal tibia

25. Multivariate analysis of the correction rate for distal tibia

27. Conclusion • Asymmetrical physeal suppression with staples, percutaneous transphyseal screws, and permanent method all are effective methods for treating valgus deformity in growing children.

28. Conclusion • When we treat valgus deformity in growing children, we should take into consideration the fact that the rate of correction at the distal femur is lower in older children.

29. Thank you for your attention!