ArticleProgress in orthodontics2015
Predicting changes in mandibular length and total anterior facial height using IGF-1, cervical stage, skeletal classification, and gender.
Article in Progress in orthodontics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Craniofacial growth predictors for class II and III malocclusions: A systematic review.Clinical and experimental dental research · 2021Pooled it
- Biomarkers in Body Fluids as Indicators of Skeletal Maturity: A Systematic Review and Meta-analysis.Rambam Maimonides medical journal · 2023Review
- Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe 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.
methodsTwenty-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 number of years each patient was followed up varied between 1 and 5 years resulting in 43 12-month intervals collected from 77 observations. Descriptive, bivariate, and regression analyses were used to analyze this data.
resultsThe linear regression model for predicting the annual mandibular growth rate was significant at p < 0.01 with an R-square value of 0.52. 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 regression model for predicting the annual change in anterior facial height was significant at p < 0.01 with an R-square value of 0.42. We found that the change in IGF-1 level was the only statistically significant predictor of this outcome.
conclusionsThe 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. These factors together explain more of the observed individual variation in growth rate than any of the factors used in isolation.
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