ArticleDental press journal of orthodontics2025
Phenotypic characterization of Class III malocclusion using three-dimensional analysis on a sample of Yemeni population: a retrospective cross-sectional study.
Article in Dental press journal of orthodontics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionClass III malocclusion is one of the abnormalities in the craniofacial development that can be affected mainly by genetic and environmental components. It is a clinical challenge, due to limited understanding of its etiology. Exploring its prototypical diversity helps to identify its etiological details.
objectiveThis study aimed to characterize Class III malocclusion subgroups depending on the phenotypic characteristics, by using cone beam computed tomography (CBCT) in a selected group of Yemeni subjects.
methodsA retrospective cross-sectional study was performed using 80 pretreatment CBCT of patients (46 males, 34 females), with ages of ≥18 years for males and ≥16 years for females. All cases had Class III malocclusion ranging from mild to severe. The total of 74 measurements were three-dimensionally analyzed using Invivo® 6.0 software. These measurements were categorized into 46 skeletal, 18 dentoalveolar, and 10 soft tissue variables. Principal component analysis (PCA) and cluster analysis (CA) were performed to identify the most common clusters in skeletal Class III malocclusion phenotypes.
resultsThe PCA revealed 8 axis models, which were responsible for 78.9% of the variation of the data produced from the 74 variables. The first four components accounted for 56% of the total variations, explained mainly the sagittal, dental, vertical, and anteroposterior relationships in the data. The CA revealed four skeletal Class III malocclusion phenotypes: C1=32.8%; C2=28.4%; C3=28.4%; and C4=10.4%.
conclusionBased on CBCT, four phenotypes of skeletal Class III malocclusion were identified among Yemeni population. These findings help to provide differential diagnosis that lead to set up an accurate and effective treatment plan.
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