Investigation of multimorbidity patterns and association rules in patients with type 2 diabetes mellitus using association rules mining algorithm.

ABSTRACT: The issue of multimorbidity in patients with type 2 diabetes mellitus (T2DM) is extremely serious. However, the pattern of multimorbidity, including typical complications, remains unclear. This study aims to explore the current status and influencing factors of multimorbidity in T2DM, with a focus on mining frequent disease combination patterns and strong association rules. Data on 26 diseases were extracted from the electronic medical records of 5,838 hospitalized patients with type 2 diabetes. The chi-square test, Cochran-Armitage trend test, and logistic regression were used for the analysis of influential factors. Association rule mining was employed to explore frequent disease combinations and association rules across the entire population and subgroups stratified by gender, age, and

SUBMITTER: Liu L 

PROVIDER: S-EPMC12267454 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature