ArticleClinical oral investigations2025
Gender- and age-dependent prevalence of malocclusions requiring orthodontic treatment according to the KIG classification. A cross-sectional study over a 20-year-period from the district of Viersen/North rhine.
Article in Clinical oral investigations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimPatients with statutory health insurance (SHI) in Germany must undergo an assessment of orthodontic treatment need using the KIG classification system since 2002. Recent studies have shown that the prevalence of anomalies is not homogeneous when categorised according to patient age at treatment begin. The aim of this study was to analyse the KIG classifications over a period of 20 years to determine whether there is also a gender-specific prevalence. PATIENTS AND
methodsBetween 2002 and 2021, n = 4940 statutorily insured patients before the age of 18 presented themselves for an orthodontic consultation. Out of these, n = 3701 showed a treatment indication according to current SHI guidelines. The KIG classification was based on the highest existing KIG grade observed in these patients without multiple classifications. The patient cohort was then divided into 3 groups according to gender and chronological age, representing early (PG 1), main (PG 2) and late (PG 3) treatment.
resultsN = 1934 (52.2%, mean age 11.00 ± 2.28 years) of the patients were female, n = 1767 (47.8%, mean age 11.44 ± 2.23 years) male. Out of those, n = 1109 and thus 30.0% of the total collective had the KIG classification D and 43.1% (n = 1595) combined sagittal classifications D + M. Regarding treatment period, the classification K was the most frequent in PG 1, D in PG 2 and E in PG 3 for both genders, and the combination D + M in all groups. Regarding the age at treatment begin, there were different peak values for males and females. Females reached D + M, O + T, B + K and E + P as well as the KIG classifications D, M, O, T, B and K earlier than males, but even age distributions occurred for E and P. The percentage gender distribution in the various age groups showed the opposite trend: In females, there was a decrease in PG 3 compared to PG 1 for all 4 KIG combinations and for 7 of 8 individual anomalies, while it was vice versa in males.
conclusionsThis study was the first to analyse the KIG classification for gender-specific differences and their possible age dependency over a period of 20 years and confirms that the distribution of KIG classifications requiring treatment is not homogeneous, but age-and gender-dependent. CLINICAL RELEVANCE: The study results on gender- and age-specific differences in the KIG classification can be regarded as a step towards personalised medicine in orthodontics.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.