Abstract
Multimorbidity has great impact on health care. We constructed multimorbidity networks in the general population, extracted subnets focused on common chronic conditions and analysed type 2 diabetes mellitus (T2DM) comorbidity network. We used electronic records from 3,135,948 adult people in Catalonia, Spain (539,909 with T2DM), with at least 2 coexistent chronic conditions within the study period (2006–2017). We constructed networks from odds-ratio estimates adjusted by age and sex and considered connections with OR > 1.2 and p-value < 1e-5. Directed networks and trajectories were derived from temporal associations. Interactive networks are freely available in a website with the option to customize characteristics and subnets. The more connected conditions in T2DM undirected network were: complicated hypertension and atherosclerosis/peripheral vascular disease (degree: 32), cholecystitis/cholelithiasis, retinopathy and peripheral neuritis/neuropathy (degree: 31). T2DM has moderate number of connections and centrality but is associated with conditions with high scores in the multimorbidity network (neuropathy, anaemia and digestive diseases), and severe conditions with poor prognosis. The strongest associations from T2DM directed networks were to retinopathy (OR: 23.8), glomerulonephritis/nephrosis (OR: 3.4), peripheral neuritis/neuropathy (OR: 2.7) and pancreas cancer (OR: 2.4). Temporal associations showed the relevance of retinopathy in the progression to complicated hypertension, cerebrovascular disease, ischemic heart disease and organ failure.
Highlights
Multimorbidity is the simultaneous presence of two or more chronic medical conditions[1]
We only considered a temporal association for probabilities below 40% or above 60% that a disease was diagnosed previously or afterward another one
We included the information of 3,135,948 patients with multimorbidity; 539,909 of them with type 2 diabetes mellitus (T2DM) (Fig. 1)
Summary
Multimorbidity is the simultaneous presence of two or more chronic medical conditions[1]. The prevalence is higher in older people and low socioeconomic situations[3] It is associated with a poorer quality of life, more disability[4] and patient safety incidents[5] and a greater, almost exponential, increase in health care costs[6]. Hidalgo et al studied phenotypic networks and found that patients with diseases highly connected tend to die sooner[7]. This tool has been used to identify comorbidity associated with hypertension[8], chronic pulmonary obstructive disease[9] or mental disease[10] and to compare multimorbidity by gender[11]. We aimed to construct the multimorbidity network in the general population, extract subnets focused on the most common chronic health conditions, construct an interactive website openly available to visualize the networks and analyse T2DM comorbidity network
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