Observational studyIrish journal of medical science2016
Evaluation of patients diagnosed with essential arterial hypertension through network analysis.
Observational study in Irish journal of medical science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed, 2 citations in OpenAlex.
- Onco-Hem Connectome-Network-Based Phenotyping of Polypharmacy and Drug-Drug Interactions in Onco-Hematological Inpatients.Pharmaceutics · 2026Article
- Clustering drug-drug interaction networks with energy model layouts: community analysis and drug repurposing.Scientific reports · 2016Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEssential 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.
aimsOur 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.
methodsNetwork 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.
resultsDistinct 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.