scholarly journals Aszimmetrikus dimetilarginin: a cardiovascularis betegségek prediktora?

2016 ◽  
Vol 157 (13) ◽  
pp. 483-487
Author(s):  
Balázs Németh ◽  
Péter Kustán ◽  
Ádám Németh ◽  
Zsófia Lenkey ◽  
Attila Cziráki ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Asymmetric Dimethylarginine ◽  
Disease Onset ◽  
Cardiovascular Prevention ◽  
Competitive Inhibitor ◽  
Diabetic Patients ◽  
Artery Disease

Cardiovascular diseases are the most common diseases worldwide. They are responsible for one third of global deaths and they are the leading cause of disability, too. The usage of different levels of prevention in combination with effective risk assessment improved these statistical data. Risk assessment based on classic risk factors has recently been supported with several new markers, such as asymmetric dimethylarginine, which is an endogenous competitive inhibitor of nitric oxide synthase. Elevated levels of asymmetric dimethylarginine have been reported in obese, smoker, hypercholesterolemic, hypertensive and diabetic patients. According to previous studies, asymmetric dimethylarginine is a suitable indicator of endothelial dysfunction, which is held to be the previous state of atherosclerosis. Several researches found positive correlation between higher levels of asymmetric dimethylarginine and coronary artery disease onset, or progression of existing coronary disease. According to a study involving 3000 patients, asymmetric dimethylarginine is an independent risk factor of cardiovascular mortality in patients with coronary artery disease. This article summarizes the role of asymmetric dimethylarginine in prediction of cardiovascular diseases, and underlines its importance in cardiovascular prevention. Orv. Hetil., 2016, 157(13), 483–487.

Poor outcome of diabetic patients with coronary artery disease and coexisting heart failure

2008 ◽  
Vol 7 ◽  
pp. 19-19
Author(s):  
B PONIKOWSKA ◽  
E JANKOWSKA ◽  
K WEGRZYNOWSKATEODORCZYK ◽  
S POWIERZA ◽  
L BORODULINNADZIEJA ◽  
...  
Keyword(s):  
Heart Failure ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Diabetic Patients ◽  
Poor Outcome ◽  
Artery Disease

Evaluation of aortic arch calcification in type 2 diabetic patients

VASA ◽  
2005 ◽  
Vol 34 (2) ◽  
pp. 113-117 ◽  
Author(s):  
Papanas ◽  
Symeonidis ◽  
Maltezos ◽  
Giannakis ◽  
Mavridis ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Aortic Arch ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Insulin Dependence ◽  
Artery Disease ◽  
Type 2 Diabetic ◽  
Aortic Arch Calcification

Background: The purpose of this study is to evaluate the severity of aortic arch calcification among type 2 diabetic patients in association with diabetes duration, diabetic complications, coronary artery disease and presence of cardiovascular risk factors. Patients and methods: This study included 207 type 2 diabetic patients (101 men) with a mean age of 61.5 ± 8.1 years and a mean diabetes duration of 13.9 ± 6.4 years. Aortic arch calcification was assessed by means of posteroanterior chest X-rays. Severity of calcification was graded as follows: grade 0 (no visible calcification), grade 1 (small spots of calcification or single thin calcification of the aortic knob), grade 2 (one or more areas of thick calcification), grade 3 (circular calcification of the aortic knob). Results: Severity of calcification was grade 0 in 84 patients (40.58%), grade 1 in 64 patients (30.92%), grade 2 in 43 patients (20.77%) and grade 3 in 16 patients (7.73%). In simple regression analysis severity of aortic arch calcification was associated with age (p = 0.032), duration of diabetes (p = 0.026), insulin dependence (p = 0.042) and presence of coronary artery disease (p = 0.039), hypertension (p = 0.019), dyslipidaemia (p = 0.029), retinopathy (p = 0.012) and microalbuminuria (p = 0.01). In multiple regression analysis severity of aortic arch calcification was associated with age (p = 0.04), duration of diabetes (p = 0.032) and presence of hypertension (p = 0.024), dyslipidaemia (p = 0.031) and coronary artery disease (p = 0.04), while the association with retinopathy, microalbuminuria and insulin dependence was no longer significant. Conclusions: Severity of aortic arch calcification is associated with age, diabetes duration, diabetic complications (retinopathy, microalbuminuria), coronary artery disease, insulin dependence, and presence of hypertension and dyslipidaemia.

Evaluation of Malondialdehyde (MDA) in type 2 diabetic Patients with Coronary Artery Disease (CAD)

2014 ◽  
Vol 3 (6) ◽  
Author(s):  
J. Zavar-Reza ◽  
H. Shahmoradi ◽  
A. Mohammadyari ◽  
M. Mohammadbeigi ◽  
R. Hosseini ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Diabetic Patients ◽  
Type 2 Diabetic Patients ◽  
Artery Disease ◽  
Type 2 Diabetic

Screening for Coronary Artery Disease in Asymptomatic Diabetic Patients

2007 ◽  
Vol 3 (1) ◽  
pp. 43
Author(s):  
Joanne D Schuijf ◽  
Jeroen J Bax ◽  
Ernst E van der Wall ◽  
◽  
◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Diabetic Patients ◽  
Artery Disease

1425-P: White Blood Cell Count Predicts Cardiovascular Prognosis in Type 2 Diabetic Patients with Established Coronary Artery Disease

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1425-P
Author(s):  
ATSUHIKO KAWABE ◽  
YUKI NAKATANI ◽  
SHOYA ONO ◽  
YASUSHI MIYASHITA ◽  
MIHOKO MATSUMURA ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Diabetic Patients ◽  
Blood Cell Count ◽  
Type 2 Diabetic Patients ◽  
Established Coronary Artery Disease ◽  
Cardiovascular Prognosis ◽  
Artery Disease ◽  
Type 2 Diabetic

Genetic Interactions Effects of Cardiovascular Disorder Using Computational Models: A Review

2020 ◽  
Vol 9 (3) ◽  
pp. 177-191
Author(s):  
Sridharan Priya ◽  
Radha K. Manavalan
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Cardiovascular Diseases ◽  
Computational Models ◽  
Genetic Interaction ◽  
Association Studies ◽  
Genetic Interactions ◽  
Computational Techniques ◽  
Genome Wide Association Studies ◽  
Artery Disease

Background: The diseases in the heart and blood vessels such as heart attack, Coronary Artery Disease, Myocardial Infarction (MI), High Blood Pressure, and Obesity, are generally referred to as Cardiovascular Diseases (CVD). The risk factors of CVD include gender, age, cholesterol/ LDL, family history, hypertension, smoking, and genetic and environmental factors. Genome- Wide Association Studies (GWAS) focus on identifying the genetic interactions and genetic architectures of CVD. Objective: Genetic interactions or Epistasis infer the interactions between two or more genes where one gene masks the traits of another gene and increases the susceptibility of CVD. To identify the Epistasis relationship through biological or laboratory methods needs an enormous workforce and more cost. Hence, this paper presents the review of various statistical and Machine learning approaches so far proposed to detect genetic interaction effects for the identification of various Cardiovascular diseases such as Coronary Artery Disease (CAD), MI, Hypertension, HDL and Lipid phenotypes data, and Body Mass Index dataset. Conclusion: This study reveals that various computational models identified the candidate genes such as AGT, PAI-1, ACE, PTPN22, MTHR, FAM107B, ZNF107, PON1, PON2, GTF2E1, ADGRB3, and FTO, which play a major role in genetic interactions for the causes of CVDs. The benefits, limitations, and issues of the various computational techniques for the evolution of epistasis responsible for cardiovascular diseases are exhibited.

Ocular circulation in diabetic patients with coronary artery disease

2005 ◽  
Vol 244 (2) ◽  
pp. 163-169 ◽  
Author(s):  
Sayuri Fujioka ◽  
Kaoruko Karashima ◽  
Norikiyo Nishikawa ◽  
Yoshihiro Saito
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Diabetic Patients ◽  
Ocular Circulation ◽  
Artery Disease
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