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Clinical Advances in Preventive Cardiology
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Clinical Advances in Preventive Cardiology

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Cardiology".

Deadline for manuscript submissions: 28 July 2024 | Viewed by 1035

Special Issue Editor

Dr. Jani T. Tikkanen

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Guest Editor
1. Medical Research Center Oulu, Oulu University Hospital, University of Oulu, Oulu, Finland
2. Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
Interests: electrocardiography; prevention; sudden cardiac death; artificial intelligence; metabolic health

Special Issue Information

Dear Colleagues,

The landscape of cardiology is witnessing a pivotal shift towards a more proactive approach to combating cardiovascular diseases (CVD), the leading cause of mortality globally. This Special Issue, entitled "Clinical Advances in Preventive Cardiology", is dedicated to exploring the forefront of prevention in cardiovascular health. With early detection becoming increasingly feasible, we delve into the transformative role of artificial intelligence, advanced imaging techniques, and various prediction models in identifying actionable insights before the onset of clinical symptoms.

This Special Issue also seeks evidence of the importance of early preventive actions and strategies in metabolic health in extending the health span and reducing the burden of CVD. It aims to showcase the latest research and developments in this field, including the most effective measures for primary prevention. We will explore how lifestyle modifications, pharmacological interventions, and innovative technologies are synergizing to redefine preventive cardiology.

Our goal is to provide a comprehensive overview of current trends, challenges, and opportunities for preventing CVD. We invite contributions that shed light on novel approaches, clinical trials, and observational studies that advance our understanding. This issue aspires to be inspirational for cardiologists, researchers, and healthcare professionals in their relentless pursuit of extending and enhancing cardiovascular health.

We look forward to your insightful submissions and to advancing the field of preventive cardiology together.

Dr. Jani T. Tikkanen
Guest Editor

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 Clinical Medicine is an international peer-reviewed open access semimonthly 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

  • prevention
  • coronary artery disease
  • sudden cardiac death
  • arrhythmias
  • atrial fibrillation
  • artificial intelligence
  • prediction models
  • healthspan
  • interventions

Published Papers (2 papers)

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Research

12 pages, 979 KiB  
Article
Risk Factors and Modifiers for Cardiovascular Disease Assessment of Patients with Heterozygous Familial Hypercholesterolaemia
by Richard Malone, Sarah Savage, Vivion Crowley, Martina Hennessy, Patricia O’Connor and Cormac Kennedy
J. Clin. Med. 2024, 13(8), 2270; https://doi.org/10.3390/jcm13082270 - 14 Apr 2024
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Abstract
Background: The assessment of the risk of cardiovascular disease (CVD) in patients with heterozygous familial hypercholesterolemia (HeFH) is determined by conventional risk factors. However, factors modifying CVD, or risk modifiers, beyond conventional risk factors may inform their CVD risk assessment and the [...] Read more.
Background: The assessment of the risk of cardiovascular disease (CVD) in patients with heterozygous familial hypercholesterolemia (HeFH) is determined by conventional risk factors. However, factors modifying CVD, or risk modifiers, beyond conventional risk factors may inform their CVD risk assessment and the subsequent use of new therapies. This work identifies and characterises patients within a lipid clinic cohort with regards to conventional CVD risk factors and risk modifiers with a focus on those with HeFH. Methods: A study of consecutive adult patients attending our specialist lipid clinic was performed over a six-month period. The patient data recorded included demographics, clinical characteristics, risk factors and risk modifiers, biochemical profiles and genetic testing results. Risk modifiers were identified based on ESC/EAS guidance, and those with HeFH were compared to those without. Results: A total of 370 patients were included. Of these, 98 HeFH patients were identified (26%). Then, 52% of HeFH patients were stratified into the very-high risk category due to the presence of CVD risk factors. Risk modifiers were present in 73%. These included a family history of premature CVD (56%), obesity (28%), a sedentary lifestyle (13%) and a major psychiatric disorder (12%). Compared to the rest of the cohort, those with HeFH were less likely to have hypertension and more likely to have a family history of premature CVD. Conclusions: Half of patients with HeFH are categorised as having very high CV risk. Consideration of risk modifiers, particularly a family history of premature CV disease, increases this very-high-risk category further. This may have implications for the clinical application and access to novel treatments. Full article
(This article belongs to the Special Issue Clinical Advances in Preventive Cardiology)
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13 pages, 2463 KiB  
Article
Navigating the Landscape of Cardiovascular Risk Scores: A Comparative Analysis of Eight Risk Prediction Models in a High-Risk Cohort in Lithuania
by Petras Navickas, Laura Lukavičiūtė, Sigita Glaveckaitė, Arvydas Baranauskas, Agnė Šatrauskienė, Jolita Badarienė and Aleksandras Laucevičius
J. Clin. Med. 2024, 13(6), 1806; https://doi.org/10.3390/jcm13061806 - 21 Mar 2024
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Abstract
Background: Numerous cardiovascular risk prediction models (RPM) have been developed, however, agreement studies between these models are scarce. We aimed to assess the inter-model agreement between eight RPMs: assessing cardiovascular risk using SIGN, the Australian CVD risk score (AusCVDRisk), the Framingham Risk Score [...] Read more.
Background: Numerous cardiovascular risk prediction models (RPM) have been developed, however, agreement studies between these models are scarce. We aimed to assess the inter-model agreement between eight RPMs: assessing cardiovascular risk using SIGN, the Australian CVD risk score (AusCVDRisk), the Framingham Risk Score for Hard Coronary Heart Disease, the Multi-Ethnic Study of Atherosclerosis risk score, the Pooled Cohort Equation (PCE), the QRISK3 cardiovascular risk calculator, the Reynolds Risk Score, and Systematic Coronary Risk Evaluation-2 (SCORE2). Methods: A cross-sectional study was conducted on 11,174 40–65-year-old individuals with diagnosed metabolic syndrome from a single tertiary university hospital in Lithuania. Cardiovascular risk was calculated using the eight RPMs, and the results were categorized into high, intermediate, and low-risk groups. Inter-model agreement was quantified using Cohen’s Kappa coefficients. Results: The study revealed significant heterogeneity in risk categorizations with only 1.49% of cases where all models agree on the risk category. SCORE2 predominantly categorized participants as high-risk (67.39%), while the PCE identified the majority as low-risk (62.03%). Cohen’s Kappa coefficients ranged from −0.09 to 0.64, indicating varying degrees of inter-model agreement. Conclusions: The choice of RPM can substantially influence clinical decision-making and patient management. The PCE and AusCVDRisk models exhibited the highest degree of agreement while the SCORE2 model consistently exhibited low agreement with other models. Full article
(This article belongs to the Special Issue Clinical Advances in Preventive Cardiology)
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