The comorbidity network in older adults with atrial fibrillation: a Danish nationwide cohort study

Abstract

Abstract Introduction Individuals affected by atrial fibrillation (AF) often present with multiple comorbidities that challenge their clinical management and worsen the prognosis. Characterizing the network structure of comorbid chronic conditions in AF patients may provide insights to better tailor medical and care management. Purpose To examine and compare the network structure of comorbidities in older people with and without AF. Methods Cross-sectional data derived from the Danish National Patient Register (period 2012–2017) were examined. Patients 60+ years old by 1. January 2017 with AF were selected and matched by age and sex to non-AF controls. Chronic conditions coded according to the International Classification of Diseases, 10th revision were retrieved and grouped into 60 clinically relevant disease categories for old age. Network analysis was applied to construct the disease networks and the centrality index of expected influence was measured to estimate the disease interconnectedness in each network. The difference in network structure and disease centrality between AF and non-AF patients was formally assessed through network comparison tests. Results A total of 96,117 AF patients (72 years old; 45% women) were identified and matched with 96,117 non-AF controls. The most prevalent chronic conditions in AF were hypertension (55.1%), large bowel diseases (36.4%) and ischemic heart disease (36.0%). A significant difference of global network structure was observed between AF and non-AF patients (p<0.001) (Figure1). Chronic obstructive pulmonary disease, depression, inflammatory arthropathy, chronic kidney disease and peripheral neuropathy had a higher connectivity with other diseases in the AF vs. non-AF patients (p<0.001). By contrast, hypertension, heart failure and stroke were more interconnected in the non-AF patients (p<0.001). Among AF patients, network differences were further observed between age categories (60–79 vs 80+ years) in male and female subgroups. Conclusions Older AF patients exhibited a complex network structure of chronic conditions that differed from age- and sex- matched non-AF patients. The network-based identification of highly co-morbid diseases in AF can improve our understanding of AF-related chronic conditions and potentially enhance prioritization and a personalized care for older patients with AF. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union's Horizon 2020 research and innovation programme