Cardiovascular disease (CVD) represents one of the main causes of mortality worldwide and nearly a half of it is related to ischemic heart disease (IHD). The article represents a comprehensive study on the diagnostics of IHD through the targeted metabolomic profiling and machine learning techniques. A total of 112 subjects were enrolled in the study, consisting of 76 IHD patients and 36 non-CVD subjects. Metabolomic profiling was conducted, involving the quantitative analysis of 87 endogenous metabolites in plasma. A novel regression method of age-adjustment correction of metabolomics data was developed. We identified 36 significantly changed metabolites which included increased cystathionine and dimethylglycine and the decreased ADMA and arginine. Tryptophan catabolism pathways showed significant alterations with increased levels of serotonin, intermediates of the kynurenine pathway and decreased intermediates of indole pathway. Amino acid profiles indicated elevated branched-chain amino acids and increased amino acid ratios. Short-chain acylcarnitines were reduced, while long-chain acylcarnitines were elevated. Based on these metabolites data, machine learning algorithms: logistic regression, support vector machine, decision trees, random forest, and gradient boosting, were used for IHD diagnostic models. Random forest demonstrated the highest accuracy with an AUC of 0.98. The metabolites Norepinephrine; Xanthurenic acid; Anthranilic acid; Serotonin; C6-DC; C14-OH; C16; C16-OH; GSG; Phenylalanine and Methionine were found to be significant and may serve as a novel preliminary panel for IHD diagnostics. Further studies are needed to confirm these findings.

AbstractMyocardial infarction is a major cause of morbidity and mortality worldwide. Metabolomic investigations may be useful for understanding the pathogenesis of ST-segment elevation myocardial infarction (STEMI). STEMI patients were comprehensively examined via targeted metabolomic profiling, machine learning and weighted correlation network analysis. A total of 195 subjects, including 68 STEMI patients, 84 patients with stable angina pectoris (SAP) and 43 non-CVD patients, were enrolled in the study. Metabolomic profiling involving the quantitative analysis of 87 endogenous metabolites in plasma was conducted. This study is the first to perform targeted metabolomic profiling in patients with STEMI. We identified 36 significantly altered metabolites in STEMI patients. Increased levels of four amino acids, eight acylcarnitines, six metabolites of the NO–urea cycle and neurotransmitters, and three intermediates of tryptophan metabolism were detected. The following metabolites exhibited decreased levels: six amino acids, three acylcarnitines, three components of the NO–urea cycle and neurotransmitters, and three intermediates of tryptophan metabolism. We found that the significant changes in tryptophan metabolism observed in STEMI patients—the increase in anthranilic acid and tryptophol and decrease in xanthurenic acid and 3-OH-kynurenine—may play important roles in STEMI pathogenesis. On the basis of the differences in the constructed weighted correlation networks, new significant metabolite ratios were identified. Among the 22 significantly altered metabolite ratios identified, 13 were between STEMI patients and non-CVD patients, and 17 were between STEMI patients and SAP patients. Seven of these ratios were common to both comparisons (STEMI patients vs. non-CVD patients and STEMI patients vs. SAP patients). Additionally, two ratios were consistently observed among the STEMI, SAP and non-CVD groups (anthranilic acid: aspartic acid and GSG (glutamine: serine + glycine)). These findings provide new insight into the diagnosis and pathogenesis of STEMI.

Endovascular methods are leading in the treatment of patients with acute coronary syndrome (ACS). Transradial access (TRA) is traditionally used, but there are some disadvantages. Distal transradial access (dTRA) is an alternative to conventional TRA, but its outcomes in patients with ACS are controversial.Aim. To evaluate the safety and efficacy of vascular accesses, as well as in-hospital outcomes of treatment of patients with ACS using conventional TRA versus dTRA.Material and methods. This single-center, prospective, randomized study included 264 patients with ACS, which were divided into 2 groups: group 1 (n=132) — dTRA, group 2 (n=132) — TRA. The groups were comparable in the initial clinical, laboratory and angiographic characteristics.Results. During percutaneous coronary intervention, 240 drug-eluting stents were implanted in 184 patients. In 10 patients, access was converted: from dTRA to TRA in 2,3% (n=3), from dTRA to femoral — 3,0% (n=4), from dTRA to femoral in 2,3% (n=3). The mean puncture time was 125,1±11,9 s in group 1 and 58,8±8,2 s in group 2 (p<0,00005). There was no difference in the total intervention duration as follows: 30,5±7,1 min and 29,4±4,6 min (p=0,1428), respectively. The time to hemostasis was significantly higher in the TRA group: 354,2±28,1 vs 125,4±15,3 min in group 1 (p<0,00005). When using dTRA, a lower incidence of hematomas (0,8 (n=1) vs 7,0% (n=9) (p=0,019)), spasm (5,6 (n=7) vs 13,2% (n=17) (p=0,039)) and radial artery occlusion (0,8 (n=1) vs 6,2% (n=8) (p=0,036)). The number of major adverse cardiac events (MACE) in both groups was comparable: 10,4% (n=13) and 10,1% (n=13) in group 1 and 2, respectively (p=0,932).Conclusion. The use of dTRA does not increase the total procedure duration compared to conventional TRA. The complication rate was comparable in both study groups. When dTRA was used, the incidence of local complications was significantly lower compared to conventional TRA. Thus, dTRA can be an alternative to conventional TRA, but large randomized trials are required for final conclusions.