Ontology highlight
ABSTRACT: Aims
Accurate identification of individuals with maturity-onset diabetes of the young (MODY) can support precision diabetes management. However, diagnosing MODY is challenging due to overlapping clinical features with type 2 diabetes. We aimed to develop a prediction model for identifying Chinese with high likelihood of MODY for further genetic testing.Methods
We developed a logistic regression model using clinical data from an unselected cohort of 1021 Chinese with young-onset (age at diagnosis ≤ 40) non-type 1 diabetes enrolled in the Hong Kong Diabetes Register, 1.9% (n = 19) of whom had MODY (GCK-, HNF1A-, HNF4A- and HNF1B-MODY) by molecular confirmation. We validated the model in an independent local cohort of 822 Chinese with young-onset non-type 1 diabetes. We compar
SUBMITTER: Tsoi STF
PROVIDER: S-EPMC12445802 | biostudies-literature | 2025 Sep
REPOSITORIES: biostudies-literature