Subgrouping patients with ischemic heart disease by means of the Markov cluster algorithm.

ABSTRACT: Ischemic heart disease (IHD) is heterogeneous with respect to onset, burden of symptoms, and disease progression. We hypothesized that unsupervised clustering analysis could facilitate identification of distinct and clinically relevant multimorbidity clusters. We included IHD patients who underwent coronary angiography (CAG) or coronary computed tomography angiography (CCTA) between 2004 and 2016 and used the earliest procedure as the index date. Patient health records were obtained from the Danish National Patient Registry, the Danish National Prescription Registry, and two in-hospital laboratory database systems. Genetic data were obtained from the Copenhagen Hospital Biobank. Using registered pre-index diagnosis codes (n = 3046), patients were clustered by application of the Markov Clus

SUBMITTER: Haue AD 

PROVIDER: S-EPMC12381225 | biostudies-literature | 2025 Aug

REPOSITORIES: biostudies-literature