![]() ![]() The proposed method which combines IGF-1 levels with information that is readily available to clinicians can be used to predict the timing and intensity of the growth spurt. We found that the change in IGF-1 level was the only statistically significant predictor of this outcome. The regression model for predicting the annual change in anterior facial height was significant at pā<ā0.01 with an R-square value of 0.42. We found that the average IGF-1 level for the interval, the change in IGF-1 level, and the presence of a skeletal class III pattern were statistically significant predictors of mandibular growth. The linear regression model for predicting the annual mandibular growth rate was significant at pā<ā0.01 with an R-square value of 0.52. Descriptive, bivariate, and regression analyses were used to analyze this data. The number of years each patient was followed up varied between 1 and 5 years resulting in 43 12-month intervals collected from 77 observations. Twenty-five orthodontic patients (12 females and 13 males) had their cervical stages, blood-spot IGF-1 levels, and cephalometric parameters measured at 1-year intervals. The purpose of this study was to predict the annual growth rate of the mandible and total anterior facial height using IGF-1 levels together with cervical stage, skeletal classification, and gender. ![]()
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