Evaluation of patients diagnosed with essential arterial hypertension through network analysis.

Abstract

Essential hypertension is a chronic pathology that causes long-term complications due to late diagnosis of patients, the inability to control the disease through medication, or due to the complexity of associated risk factors. Our study sets out to identify specific patterns of response to arterial hypertension treatment, by taking into consideration the multiple connections between risk factors in a relevant population of hypertensive patients. Network science is an emerging paradigm, branching over multiple aspects of physical, biological and social phenomena. One such branch, which has brought significant contributions to medical science, is the field of network medicine. To apply this methodology, we create a complex network of hypertensive patients based on their common medical conditions. Consequently, we obtain a community-based representation which pinpoints specific-and previously uncharted-patterns of hypertension development. This approach creates incentives for evaluating patient's treatment efficacy, by considering its network topological position. Distinct clusters of patients with common properties have emerged for each study group (group A-treated with nebivolol, group B-treated with perindopril and group C-treated with candesartan cilexetil). Therefore, our network-based clustering allows for a better treatment assessment.