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Personalized Medicine for Hypertension: Diagnosis, Prevention and Treatment
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Personalized Medicine for Hypertension: Diagnosis, Prevention and Treatment

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Methodology, Drug and Device Discovery".

Deadline for manuscript submissions: closed (5 February 2023) | Viewed by 6183

Special Issue Editors

Prof. Dr. Meir Nitzan

E-Mail Website
Guest Editor
Department of Physics/Electro-Optics Engineering, Jerusalem College of Technology, Jerusalem, Israel
Interests: blood pressure measurement; oxygen saturation measurement; photoplethysmography; regional blood flow; autonomic nervous activity
Special Issues, Collections and Topics in MDPI journals
Dr. Iddo Ben-Dov

E-Mail Website
Guest Editor
Department of Nephrology & Hypertension, Hadassah Medical Center, Hebrew University of Jerusalem, Jerusalem, Israel
Interests: ambulatory blood pressure monitoring, microRNA; posttranscriptional gene regulation

Special Issue Information

Dear Colleagues,

Current guidelines for hypertension management, which are based on large-scale studies, provide recommendations for the general hypertensive population and for defined subgroups of patients, and medical treatment based on those recommendations successfully reduces the cardiovascular risk of the general hypertensive population. However, blood pressure is the driving force for tissue perfusion, and excessive lowering of the blood pressure can result in the hypoperfusion of vital organs. The optimal degree of blood pressure reduction may depend on demographic, genetic, physiological and clinical characteristics, and it is expected that the individualized diagnosis, prevention and treatment of hypertensive patients would be more effective than the current general management.

This Special Issue invites researchers to submit both reviews and original research manuscripts in the field of personalized or precision medicine in the field of hypertension. The articles may explore physiological or clinical aspects of the personalized management of hypertension as it relates to diagnosis, prevention and treatment. While older terminology of personalized or precision medicine mainly refers to pharmaco-genetic management, this Special Issue also invites manuscripts on hypertension management that relate to other demographic, physiological and clinical characteristics of the individual patient. Manuscripts describing the utilization of advanced analysis techniques in personalized blood pressure medicine, such as machine learning, are particularly welcome.

Prof. Dr. Meir Nitzan
Dr. Iddo Ben-Dov
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Personalized Medicine is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hypertension
  • hypotension
  • personalized diagnosis and treatment
  • precision medicine
  • blood pressure measurement
  • cardiovascular system physiology
  • arterial wall stiffness
  • autonomic dysfunction

Published Papers (2 papers)

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Research

11 pages, 1391 KiB  
Article
Chronic Effects of Effective Oral Cannabidiol Delivery on 24-h Ambulatory Blood Pressure and Vascular Outcomes in Treated and Untreated Hypertension (HYPER-H21-4): Study Protocol for a Randomized, Placebo-Controlled, and Crossover Study
by Marko Kumric, Josko Bozic, Goran Dujic, Josip Vrdoljak and Zeljko Dujic
J. Pers. Med. 2022, 12(7), 1037; https://doi.org/10.3390/jpm12071037 - 24 Jun 2022
Cited by 10 | Viewed by 2808
Abstract
Accumulating data from both human and animal studies suggest that cannabidiol (CBD) may be associated with improved cardiovascular function, markedly with regard to reduction in blood pressure and improved endothelial function. However, there is a lack of randomized studies to support these notions, [...] Read more.
Accumulating data from both human and animal studies suggest that cannabidiol (CBD) may be associated with improved cardiovascular function, markedly with regard to reduction in blood pressure and improved endothelial function. However, there is a lack of randomized studies to support these notions, especially in at-risk populations. The principal aim of this randomized, placebo-controlled, and crossover study is to examine the influence of chronic CBD administration on 24-h blood pressure in individuals with mild or moderate hypertension who are either untreated or receiving standard care therapy. The secondary aims of the study are to determine the safety and tolerability of 5 weeks of CBD administration, and to quantify the effect on arterial stiffness, CBD and vascular health biomarkers, inflammation, heart rate variability, and psychological well-being in both groups of patients. The present single-center study is designed as a triple blind (Participant, Investigator, Outcomes Assessor), placebo-controlled, crossover pilot study in which 70 hypertensive volunteers (aged 40–70 years) will receive DehydraTECH2.0 CBD formulation and placebo in a crossover manner. We believe that comprehensive analyses that will be performed in the present trial will decipher whether CBD is in fact a safe and valuable supplement for patients with treated and untreated hypertension. Full article
(This article belongs to the Special Issue Personalized Medicine for Hypertension: Diagnosis, Prevention and Treatment)
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15 pages, 2609 KiB  
Article
Precision Medicine for Hypertension Patients with Type 2 Diabetes via Reinforcement Learning
by Sang Ho Oh, Su Jin Lee and Jongyoul Park
J. Pers. Med. 2022, 12(1), 87; https://doi.org/10.3390/jpm12010087 - 11 Jan 2022
Cited by 11 | Viewed by 2689
Abstract
Precision medicine is a new approach to understanding health and disease based on patient-specific data such as medical diagnoses; clinical phenotype; biologic investigations such as laboratory studies and imaging; and environmental, demographic, and lifestyle factors. The importance of machine learning techniques in healthcare [...] Read more.
Precision medicine is a new approach to understanding health and disease based on patient-specific data such as medical diagnoses; clinical phenotype; biologic investigations such as laboratory studies and imaging; and environmental, demographic, and lifestyle factors. The importance of machine learning techniques in healthcare has expanded quickly in the last decade owing to the rising availability of vast multi-modality data and developed computational models and algorithms. Reinforcement learning is an appealing method for developing efficient policies in various healthcare areas where the decision-making process is typically defined by a long period or a sequential process. In our research, we leverage the power of reinforcement learning and electronic health records of South Koreans to dynamically recommend treatment prescriptions, which are personalized based on patient information of hypertension. Our proposed reinforcement learning-based treatment recommendation system decides whether to use mono, dual, or triple therapy according to the state of the hypertension patients. We evaluated the performance of our personalized treatment recommendation model by lowering the occurrence of hypertension-related complications and blood pressure levels of patients who followed our model’s recommendation. With our findings, we believe that our proposed hypertension treatment recommendation model could assist doctors in prescribing appropriate antihypertensive medications. Full article
(This article belongs to the Special Issue Personalized Medicine for Hypertension: Diagnosis, Prevention and Treatment)
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