Circulating microvesicles across a population with various degree of cardiovascular burden are associated with systolic blood pressure

Revealing the nature of cardiovascular disease using DERGA, a novel data ensemble refinement greedy algorithm

BACKGROUND

The study aimed to determine the most crucial parameters associated with CVD and employ a novel data ensemble refinement procedure to uncover the optimal pattern of these parameters that can result in a high prediction accuracy.

METHODS AND RESULTS

Data were collected from 369 patients in total, 281 patients with CVD or at risk of developing it, compared to 88 otherwise healthy individuals. Within the group of 281 CVD or at-risk patients, 53 were diagnosed with coronary artery disease (CAD), 16 with end-stage renal disease, 47 newly diagnosed with diabetes mellitus 2 and 92 with chronic inflammatory disorders (21 rheumatoid arthritis, 41 psoriasis, 30 angiitis). The data were analyzed using an artificial intelligence-based algorithm with the primary objective of identifying the optimal pattern of parameters that define CVD. The study highlights the effectiveness of a six-parameter combination in discerning the likelihood of cardiovascular disease using DERGA and Extra Trees algorithms. These parameters, ranked in order of importance, include Platelet-derived Microvesicles (PMV), hypertension, age, smoking, dyslipidemia, and Body Mass Index (BMI). Endothelial and erythrocyte MVs, along with diabetes were the least important predictors. In addition, the highest prediction accuracy achieved is 98.64%. Notably, using PMVs alone yields a 91.32% accuracy, while the optimal model employing all ten parameters, yields a prediction accuracy of 0.9783 (97.83%).

CONCLUSIONS

Our research showcases the efficacy of DERGA, an innovative data ensemble refinement greedy algorithm. DERGA accelerates the assessment of an individual's risk of developing CVD, allowing for early diagnosis, significantly reduces the number of required lab tests and optimizes resource utilization. Additionally, it assists in identifying the optimal parameters critical for assessing CVD susceptibility, thereby enhancing our understanding of the underlying mechanisms.

Acute Intake of Fructose Increases Arterial Pressure in Humans: A Meta-Analysis and Systematic Review

Hypertension is a major cardiac risk factor. Higher blood pressures are becoming more prevalent due to changing dietary habits. Here, we evaluated the impact on blood pressure in human subjects after acutely ingesting fructose using meta-analysis. A total of 89 studies were collected from four different electronic databases from 1 January 2008 to 1 August 2023. Of these studies, 10 were selected that fulfilled all the criteria for this meta-analysis. Heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial blood pressure (MAP), and blood glucose level were analyzed using the Cohen's d analysis or standardized mean difference at a confidence interval (CI) of 95%. The SBP, DBP, and MAP showed medium effect size; HR and glucose level displayed small effect size. The standardized mean difference of normal diet groups and fructose diet groups showed a significant increase in SBP (p = 0.04, REM = 2.30), and DBP (p = 0.03, REM = 1.48) with heterogeneity of 57% and 62%, respectively. Acute fructose ingestion contributes to an increase in arterial pressure in humans. The different parameters of arterial pressure in humans correlated with each other. These findings support further rigorous investigation, retrospective of necessity, into the effect of chronic dietary of fructose in humans in order to better understand the impact on long term arterial pressure.