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Medicina
Special Issues
Cardiovascular Diseases and Type 2 Diabetes: 2nd Edition
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Cardiovascular Diseases and Type 2 Diabetes: 2nd Edition

A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Endocrinology".

Deadline for manuscript submissions: 10 February 2025 | Viewed by 2389

Special Issue Editor

Dr. Cristina Tudoran

E-Mail Website
Guest Editor
Department VII, Internal Medicine II, Discipline of Cardiology, University of Medicine and Pharmacy “Victor Babes” Timisoara, 300041 Timisoara, Romania
Interests: clinical cardiology; pulmonary hypertension; heart failure; post-acute COVID-19 syndrome; arterial hypertension
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cardiovascular diseases and type 2 diabetes mellitus are among the most widespread pathologies in our society and their prevalence increases with advancing age. These pathologies are associated with increased morbidity and mortality and are responsible for most hospital admissions, and at the same time extending the duration of hospitalization for other conditions.

The relationship between these two pathologies is bidirectional. On the one hand, type 2 diabetes mellitus represents an independent risk factor for atherosclerosis, peripheral and coronary artery disease, and systemic hypertension, intervening through multiple pathways in the pathophysiology of cardiovascular diseases. In particular, diabetes mellitus type 2 determines that endothelial dysfunction is responsible for the development of new cardiovascular complications or may aggravate pre-existing pathologies. On the other hand, the coexistence of cardiovascular diseases represents a challenge for the management of diabetes mellitus, increasing the risk for developing other systemic complications among which the renal and neurological ones are the most significant.

In this Special Issue, we focus on the interrelation between cardiovascular pathologies and diabetes mellitus type 2. We are interested in original research or review articles describing pathophysiological mechanisms, clinical approaches, new diagnostic techniques, or therapeutic options.

Dr. Cristina Tudoran
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. Medicina 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 2200 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

  • acute and chronic coronary syndrome
  • endothelial dysfunction
  • arterial hypertension
  • heart failure
  • insulin resistance
  • diabetes mellitus type 2

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Related Special Issue

Published Papers (1 paper)

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Research

16 pages, 2436 KiB  
Article
Cardiovascular Risk Factors as Independent Predictors of Diabetic Retinopathy in Type II Diabetes Mellitus: The Development of a Predictive Model
by Cristian Dan Roşu, Melania Lavinia Bratu, Emil Robert Stoicescu, Roxana Iacob, Ovidiu Alin Hațegan, Laura Andreea Ghenciu and Sorin Lucian Bolintineanu
Medicina 2024, 60(10), 1617; https://doi.org/10.3390/medicina60101617 - 2 Oct 2024
Viewed by 1456
Abstract
Background: Diabetic retinopathy (DR) is a leading cause of blindness in patients with type 2 diabetes mellitus (T2DM). Cardiovascular risk factors, such as hypertension, obesity, and dyslipidemia, may play a crucial role in the development and progression of DR, though the evidence [...] Read more.
Background: Diabetic retinopathy (DR) is a leading cause of blindness in patients with type 2 diabetes mellitus (T2DM). Cardiovascular risk factors, such as hypertension, obesity, and dyslipidemia, may play a crucial role in the development and progression of DR, though the evidence remains mixed. This study aimed to assess cardiovascular risk factors as independent predictors of DR and to develop a predictive model for DR progression in T2DM patients. Methods: A retrospective cross-sectional study was conducted on 377 patients with T2DM who underwent a comprehensive eye exam. Clinical data, including blood pressure, lipid profile, BMI, and smoking status, were collected. DR staging was determined through fundus photography and classified as No DR, Non-Proliferative DR (NPDR), and Mild, Moderate, Severe, or Proliferative DR (PDR). A Multivariate Logistic Regression was used to evaluate the association between cardiovascular risk factors and DR presence. Several machine learning models, including Random Forest, XGBoost, and Support Vector Machines, were applied to assess the predictive value of cardiovascular risk factors and identify key predictors. Model performance was evaluated using accuracy, precision, recall, and ROC-AUC. Results: The prevalence of DR in the cohort was 41.6%, with 34.5% having NPDR and 7.1% having PDR. A multivariate analysis identified systolic blood pressure (SBP), LDL cholesterol, and body mass index (BMI) as independent predictors of DR progression (p < 0.05). The Random Forest model showed a moderate predictive ability, with an AUC of 0.62 for distinguishing between the presence and absence of DR XGBoost showing a better performance, featuring a ROC-AUC of 0.68, while SBP, HDL cholesterol, and BMI were consistently identified as the most important predictors across models. After tuning, the XGBoost model showed a notable improvement, with an ROC-AUC of 0.72. Conclusions: Cardiovascular risk factors, particularly BP and BMI, play a significant role in the progression of DR in patients with T2DM. The predictive models, especially XGBoost, showed moderate accuracy in identifying DR stages, suggesting that integrating these risk factors into clinical practice may improve early detection and intervention strategies for DR. Full article
(This article belongs to the Special Issue Cardiovascular Diseases and Type 2 Diabetes: 2nd Edition)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: LDL vs TG/HDL fir cardiovascular risk assessment in clinical practice
Authors: Dragos Cozma
Affiliation: University of Medicine and Pharmacy Victor Babes Timisoara

Title: Cardiovascular risk assessment and interdisciplinary management in patients with type 2 diabetes mellitus
Authors: Laura Gaita
Affiliation: Victor Babeș University of Medicine and Pharmacy

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