Hypohyperodontia in a sample of Chinese population: a retrospective study

Hypohyperdontia prevalence is 0.66%, within the global range (0.002% to 3.1%) with no gender bias. Typically diagnosed in mixed dentition, most cases are bimaxillary involvement. Isolated posterior involvement is rare. ST and agenesis patterns mirror isolated anomalies. Early panoramic screening in suspected cases facilitates timely multidisciplinary management to prevent functional and aesthetic complications.

Authors

Institutions

Publication Details

Journal
BMC Oral Health
Published
2025-12-01
DOI
https://doi.org/10.1186/s12903-025-07213-6
Primary Topic
dental development and anomalies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hypohyperodontia in a sample of Chinese population: a retrospective study

Xiaojie Zhou, Guoxia Yu, Shuang Li
BMC Oral Health
dental development and anomalies
article

Hypohyperodontia in a sample of Chinese population: a retrospective study

Xiaojie Zhou, Guoxia Yu, Shuang Li
article en

Abstract

Hypohyperdontia prevalence is 0.66%, within the global range (0.002% to 3.1%) with no gender bias. Typically diagnosed in mixed dentition, most cases are bimaxillary involvement. Isolated posterior involvement is rare. ST and agenesis patterns mirror isolated anomalies. Early panoramic screening in suspected cases facilitates timely multidisciplinary management to prevent functional and aesthetic complications.

BMC Oral HealthVol. 25(1)
Beijing Children’s Hospital (CN)
Openalex Percentile: Top 66%
dental development and anomalies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.