Lipoprotein Metabolism Indicators in Young Patients With Arterial Hypertension

Aim. To assess the prospects of using artificial intelligence technologies in predicting the outcomes and risks of cardiovascular diseases (CVD) in patients with hypertension (HTN).Material and methods. A software application was created for data mining from respondent profiles in a semi-automatic mode; libraries with data preprocessing were analyzed. We analyzed the main and additional parameters (35) of CVD risk factors in 2131 people as a part of ESSE-RF study (2014-2019). To create a forecasting model, a high-level language Python 2.7 was used using object-oriented programming and exception handling with multithreading support. Using randomization, learning (n=488) and test (n=245) samples were formed, which included data from patients with an established diagnosis of HTN.Results. The prevalence of HTN among subjects was 34,39%. There were following significant factors for predicting CVD: anthropometric parameters, smoking, biochemical profile (total cholesterol, ApoA, ApoB, glucose, D-dimer, C-reactive protein). As a result of a 5-year follow-up, CVD was found in 235 people (32,06%) with HTN and 187 people (13,38%) without HTN; mortality rates were 1,27% in subjects with HTN and 1,12% — without HTN. The absolute mortality risk among participants with HTN (0,037) was significantly higher (p<0,05) than in patients without HTN (0,017). To create a neural network (NN), the basic Sequential model from the Keras library was used. During machine learning, 26 variables important for the CVD development were used as input and 9 neurons — as output, which corresponded to the number of established cardiovascular events. The created NN had a predictive value of up to 97,9%, which exceeded the SCORE value (34,9%).Conclusion. The data obtained indicate the importance of risk factor phenotyping using anthropometric markers and biochemical profile for determining their significance in the top 20 predictors of CVD. The Python-based machine learning provides CVD prediction according to standard risk assessments.

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Machine learning for predicting the outcomes and risks of cardiovascular diseases in patients with hypertension: results of ESSE-RF in the Primorsky Krai

Невзорова

Плехова

Priseko

et al. 2020

Russ J Cardiol

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Contents of matrix metalloproteinase type 2 (MMP-2) and complexes MMP-9/TIMP-1, MMP-2/TIMP-2, and total cholesterol in practically healthy people and patients with hypertension

Chepurnova,

Knysh,

Yushchuk

et al. 2023

Russian Journal of Immunology

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Arterial hypertension (AH) is the most common age-associated disease among the working population. Polyetiology of AH requires a more thorough definition and study of its predictors aiming for understanding the role of external influences, as well as detection of genetic polymorphisms at early stages, in order to limit their implementation. The scientific reviews discuss the important role of abnormal vascular remodeling in the pathogenesis of hypertension. The main factor of such alterations is the rearrangement of extracellular matrix due to matrix metalloproteinases (MMP), the zinc-dependent enzymes with a wide substrate specificity. In addition, in more than 70% of cases, AH is combined with lipid metabolism disorders, including an increase in cholesterol levels. These mechanisms should be taken into account when assessing risk factors for development of cardiovascular accidents. The role of MMP-2 and the complexes MMP- 9/ TIMP- 1, MMP-2/TIMP-2 in pathogenesis of vascular restructuring is insufficiently described in the review articles. The article presents our results of studying the system of proteolytic enzymes and the level of total cholesterol in 110 practically healthy people and 90 persons with AH aged 18 to 74 years old. The levels of MMP-2, MMP-9/ TIMP- 1, MMP-2/TIMP-2 complexes in blood serum were studied by the sandwich variant of ELISA technique. Statistical processing of the obtained data was carried out using the analytical software IBM SPSS Statistics, v. 22.0.1. It was found that in the groups of women, regardless of the presence, or absence of pathology, the level of total cholesterol is higher if compared with male subjects. MMP-2 values were low both in the general group of practically healthy people, regardless of gender, and in the group of men with hypertension. Proteolytic activity of MMP-2 shows a broader substrate activity in women with hypertension. In the group of practically healthy men and women, we have registered lower levels of the studied MMP complexes and their tissue inhibitors. An imbalance in the proteolysis/antiproteolysis system is observed both in the group of hypertensive women with more pronounced effects upon migration, proliferation and apoptosis of smooth muscle cells, endothelial and inflammatory cells, thus determining formation of intima and arterial remodeling, as well as in the group of men with hypertension with predominance of remodeling factors that affects the rigidity of vascular wall.

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Lipoprotein Metabolism Indicators in Young Patients With Arterial Hypertension

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Machine learning for predicting the outcomes and risks of cardiovascular diseases in patients with hypertension: results of ESSE-RF in the Primorsky Krai

Machine learning for predicting the outcomes and risks of cardiovascular diseases in patients with hypertension: results of ESSE-RF in the Primorsky Krai

Contents of matrix metalloproteinase type 2 (MMP-2) and complexes MMP-9/TIMP-1, MMP-2/TIMP-2, and total cholesterol in practically healthy people and patients with hypertension

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