Prevalence of malocclusions requiring treatment according to the KIG classification : A multipart cross-sectional study over a 20-year period in the district of Viersen/North Rhine.

Gero Stefan Michael Kinzinger Jan Hourfar Jörg Alexander Lisson

Published in: Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie (2024)

The present study confirms existing findings as well as the nationwide data of the National Association of Statutory Health Insurance Dentists (KZBV) from 2020: The sagittal deviations "D" (increased overjet) and "M" (negative overjet) represented the most frequent findings with KIG D4 as the most common classification. The prevalence and age distribution of KIG grades 3-5 requiring treatment corresponded to nationwide comparative data.

Keyphrases

health insurance
machine learning
risk factors
deep learning
electronic health record
healthcare
cross sectional
data analysis