ArticleBMC medical informatics and decision making2021
Identifying drug-related attributes to personalise antihypertensive agents: the outcome report of patients receiving metoprolol therapy.
Article in BMC medical informatics and decision making, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning-Based Multicohort (RIGIPREV) Study.Journal of medical Internet research · 2024Article
- Predicting miRNA-Disease Associations by Combining Graph and Hypergraph Convolutional Network.Interdisciplinary sciences, computational life sciences · 2024Article
- A comparative study of antihypertensive drugs prediction models for the elderly based on machine learning algorithms.Frontiers in cardiovascular medicine · 2022Article
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Authors and funding
8 authors.
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Abstract
backgroundCurrently, numerous antihypertensive drugs from different pharmacological classes are available; however, blood pressure control is achieved in only less than a third of patients treated for hypertension. Moreover, providing optimal and personalised treatment for hypertension is challenging. Therefore, in this study, we propose a 'drug-related attributes' sensitive spectrum. This novel concept can assist clinicians in selecting an optimal antihypertensive drug and improve blood pressure control after examining the attributes of a patient.
methodsWe collected clinical data on attributes related to hypertension and its therapy of inpatients from West China Hospital who received metoprolol therapy and constructed the sensitive spectrum using data-visualisation tools.
resultsOur analysis revealed that haematocrit, haemoglobin, serum creatinine, serum cystatin C, serum urea, age, sex, systolic pressure, diastolic pressure, pulse pressure, and heart rate are metoprolol-related attributes.
conclusionOur study showed that all metoprolol-related attributes identified are reasonable and helpful in improving the personalisation of metoprolol therapy. The proposed drug-related attributes spectrum can help personalise antihypertensive medication. Moreover, data-visualisation tools can be effectively used to mine the drug-related attributes sensitive spectrum.
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