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Identification of biomarkers and mechanisms of diabetic cardiomyopathy using microarray data

期刊: CARDIOLOGY JOURNAL, 2020; 27 (6)

Background: The study aimed to uncover the regulation mechanisms of diabetic cardiomyopathy (DCM) and provide novel prognostic biomarkers. Methods: The dataset GSE62203 downloaded from the Gene Expression Omnibus database was utilized in the present study. After pretreatment using the Affy package, differentially expressed genes (DEGs) were identified by the limma package, followed by functional enrichment analysis and protein-protein interaction (PPI) network analysis. Furthermore, module analysis was conducted using MCODE plug-in of Cytoscape, and functional enrichment analysis was also performed for genes in the modules. Results: A set of 560 DEGs were screened, mainly enriched in the metabolic process and cell cycle related process. Hub nodes in the PPI network were LDHA (lactate dehydrogenase A), ALDOC (aldolase C, fructose-bisphosphate) and ABCE1 (ATP Binding Cassette Subfamily E Member 1), which were also highlighted in Module 1 or Module 2 and predominantly enriched in the processes of glycolysis and ribosome biogenesis. Additionally, LDHA were linked with ALDOC in the PPI network. Besides, activating transcription factor 4 (ATF4) was prominent in Module 3; while myosin heavy chain 6 (MYH6) was highlighted in Module 4 and was mainly involved in muscle cells related biological processes. Conclusions: Five potential biomarkers including LDHA, ALDOC, ABCE1, ATF4 and MYH6 were identified for DCM prognosis.

Quantitative flow ratio-guided surgical intervention in symptomatic myocardial bridging

期刊: CARDIOLOGY JOURNAL, 2020; 27 (6)

Background: Patients with myocardial bridging (MB) are associated with adverse cardiovascular events, but a decision to perform surgical intervention, especially for patients with systolic intermediate stenosis, is a difficult clinical issue. Fractional flow reserve (FFR) represents a novel method for the functional evaluation of coronary stenosis, but the relationship between FFR and MB remains controversial because of the cyclic dynamic stenosis of MB. Quantitative flow ratio (QFR) is a novel index allowing fast assessment of FFR from a diagnostic coronary angiography. This study aimed to investigate the relationship between QFR and MB patients and to further develop a prediction model of QFR-guided surgical intervention for these patients. Methods: Forty-five symptomatic lone MB patients who had undergone coronary angiography were consecutively enrolled in this study. MB was located in the middle of left anterior descending artery with intermediate stenosis during systole. The patients were retrospectively divided into a medical therapy group or a surgical therapy group. Systolic geometry based QFR (SG-QFR) and diastolic geometry based QFR (DG-QFR) were calculated based on three-dimensional quantitative coronary angiography and patient-specific flow velocity. Subsequently, time-averaged QFR (TA-QFR) is defined as the average of SG-QFR and DG-QFR. Results: Receiver operating characteristic curve analysis revealed that TA-QFR (AUC = 0.91; 95% CI: 0.79-0.98) was found to be the best pre-operative index for surgical intervention to MB, when compared with DG-QFR (AUC = 0.69; 95% CI: 0.53-0.82; difference: 0.22; 95% CI: 0.04-0.41; p = 0.02) and SG-QFR (AUC = 0.87; 95% CI: 0.74-0.95; difference: 0.04; 95% CI: 0.00-0.08; p = 0.03). Conclusions: TA-QFR improved the performance of functional evaluation in MB patients with intermediate stenosis during systole and is useful for guiding surgical intervention.

Inhibitors of the renin-angiotensin system: The potential role in the pathogenesis of COVID-19

期刊: CARDIOLOGY JOURNAL, 2020; 27 (2)

Coronavirus disease 2019 (COVID-19), which initially began in China, has spread to other countries of Asia, Europe, America, Africa and Oceania, with the number of confirmed cases and suspected cases increasing each day. According to recently published research, it was found that the majority of the severe cases were elderly, and many of them had at least one chronic disease, especially cardiovascular diseases. Angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEIs/ARBs) are the most widely used drugs for cardiovascular diseases. The clinical effect of ACEIs/ARBs on patients with COVID-19 is still uncertain. This paper describes their potential role in the pathogenesis of COVID-19, which may provide useful in the advice of cardiologists and physicians.

Association between mild thyroid dysfunction and clinical outcome in acute coronary syndrome undergoing percutaneous coronary intervention

期刊: CARDIOLOGY JOURNAL, 2020; 27 (3)

Background:Thyroid hormones profoundly influence the cardiovascular system, but the effects of mild thyroid dysfunction on the clinical outcome of acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI) are not well defined. This study aimed to determine the effect of mild thyroid dysfunction on 12-month prognosis in ACS patients undergoing PCI. Methods: In this prospective cohort study with a 12-month follow-up, 1560 individuals were divided into four groups based on thyroid hormone levels upon admission: euthyroidism (used as a reference group), subclinical hypothyroidism, subclinical hyperthyroidism, and low triiodothyronine syndrome (low T3 syndrome). The outcomes measured were all-cause mortality, cardiac mortality, nonfatal reinfarction, and unplanned repeat revascularization. Results: In this study, the prevalence of mild thyroid dysfunction was 10.8%. Multivariate analysis showed that low T3 syndrome, but not subclinical hypothyroidism or subclinical hyperthyroidism, was associated with a higher rate of all-cause (HR 2.553, 95% CI 1.093-5.964, p = 0.030) and cardiac mortality (HR 2.594, 95% CI 1.026-6.559, p = 0.034), compared with the euthyroidism group. Conclusions: Mild thyroid dysfunction was frequent in patients with ACS undergoing PCI. Low T3 syndrome was the predominant feature and was associated with 12-month adverse outcomes in these patients.

Reproducibility of quantitative flow ratio: An inter-core laboratory variability study

期刊: CARDIOLOGY JOURNAL, 2020; 27 (3)

Background: Quantitative flow ratio (QFR) is a novel approach to derive fractional flow reserve (FFR) from coronary angiography. This study sought to evaluate the reproducibility of QFR when analyzed in independent core laboratories. Methods: All interrogated vessels in the FAVOR II China Study were separately analyzed using the AngioPlus system (Pulse medical imaging technology, Shanghai) by two independent core laboratories, following the same standard operation procedures. The analysts were blinded to the FFR values and online QFR values. For each interrogated vessel, two identical angiographic image runs were used by two core laboratories for QFR computation. In both core laboratories QFR was successfully obtained in 330 of 332 vessels, in which FFR was available in 328 vessels. Thus, 328 vessels ended in the present statistical analysis. Results: The mean difference in contrast-flow QFR between the two care laboratories was 0.004 +/- +/- 0.03 (p = 0.040), which was slightly smaller than that between the online analysis and the two core laboratories (0.01 +/- 0.05, p < 0.001 and 0.01 +/- 0.05, p = 0.038). The mean difference of QFR with respect to FFR were comparable between the two core laboratories (0.002 +/- 0.06, p = 0.609, and 0.002 +/- +/- 0.06, p = 0.531). Receiver operating characteristic curve analysis showed that diagnostic accuracies of QFR analyzed by the two core laboratories were both excellent (area under the curve: 0.970 vs. 0.963, p = 0.142), when using FFR as the reference standard. Conclusions: The present study showed good inter-core laboratory reproducibility of QFR in assessing functionally-significant stenosis. It suggests that QFR analyses can be carried out in different core laboratories if, and only if, highly standardized conditions are maintained.

MiR-1/133 attenuates cardiomyocyte apoptosis and electrical remodeling in mice with viral myocarditis

期刊: CARDIOLOGY JOURNAL, 2020; 27 (3)

Background: The role of miR-1 and miR-133 in regulating the expression of potassium and calcium ion channels, and mediating cardiomyocyte apoptosis in mice with viral myocarditis (VMC) is investigated herein. Methods: Male Balblc mice were randomly divided into groups: control group, VMC group, VMC + + miR-1/133 mimics group, or VMC + miR-1/133 negative control (NC) group. VMC was induced with coxsackievirus B3 (CVB3). MiR-1/133 mimics ameliorated cardiac dysfunction in VMC mice and was compared to the VMC+NC group. Results: Hematoxylin and eosin staining showed a well-arranged myocardium without inflammatory cell infiltration in the myocardial matrix of the control group. However, in the VMC and VMC+NC groups, the myocardium was disorganized and swollen with necrosis, and the myocardial matrix was infiltrated with inflammatory cells. These changes were alleviated by miR- 1/133 mimics. TUNEL staining revealed decreased cardiomyocyte apoptosis in the VMC + miR-1/133 mimics group compared with the VMC group. In addition, miR-1/133 mimics up-regulated the expression of miR-1 and miR-133, the potassium channel genes Kcnd2 and Kcnj2, as well as Bcl-2, and down-regulated the expression of the potassium channel suppressor gene Irx5, L-type calcium channel subunit gene a1c (Cacna1c), Bax, and caspase-9 in the myocardium of VMC mice. MiR-1/133 also up-regulated the protein levels of Kv4.2 and Kir2.1, and down-regulated the expression of CaV1.2 in the myocardium of VMC mice. Conclusions: MiR-1 and miR-133 decreased cardiomyocyte apoptosis by mediating the expression of apoptosis-related genes in the hearts of VMC mice.

Artificial intelligence and automation in valvular heart diseases

期刊: CARDIOLOGY JOURNAL, 2020; 27 (4)

Artificial intelligence (AI) is gradually changing every aspect of social life, and healthcare is no exception. The clinical procedures that were supposed to, and could previously only be handled by human experts can now be carried out by machines in a more accurate and efficient way. The coming era of big data and the advent of supercomputers provides great opportunities to the development of AI technology for the enhancement of diagnosis and clinical decision-making. This review provides an introduction to AI and highlights its applications in the clinical flow of diagnosing and treating valvular heart diseases (VHDs). More specifically, this review first introduces some key concepts and subareas in AI. Secondly, it discusses the application of AI in heart sound auscultation and medical image analysis for assistance in diagnosing VHDs. Thirdly, it introduces using AI algorithms to identify risk factors and predict mortality of cardiac surgery. This review also describes the state-of-the-art autonomous surgical robots and their roles in cardiac surgery and intervention.

Diagnostic accuracy and reproducibility of optical flow ratio for functional evaluation of coronary stenosis in a prospective series

期刊: CARDIOLOGY JOURNAL, 2020; 27 (4)

Background: Evaluating prospectively the feasibility, accuracy and reproducibility of optical flow ratio (OFR), a novel method of computational physiology based on optical coherence tomography (OCT). Methods and results: Sixty consecutive patients (76 vessels) underwent prospectively OCT, angiography-based quantitative flow ratio (QFR) and fractional flow ratio (FFR). OFR was computed offline in a central core-lab by analysts blinded to FFR. OFR was feasible in 98.7% of the lesions and showed excellent agreement with FFR (ICCa = 0.83, r = 0.83, slope = 0.80, intercept = 0.17, kappa = 0.84). The area under curve to predict an FFR <= 0.80 was 0.95, higher than for QFR (0.91, p = 0.115) and for minimal lumen area (0.64, p < 0.001). Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio were 93%, 92%, 93%, 88%, 96%, 13.8, 0.1, respectively. Median time to obtain OFR was 1.07 (IQR: 0.98-1.16) min, with excellent intraobserver and interobserver reproducibility (0.97 and 0.95, respectively). Pullback speed had negligible impact on OFR, provided the same coronary segment were imaged (ICCa = 0.90, kappa = 0.697). Conclusions: The prospective computation of OFR is feasible and reproducible in a real-world series, resulting in excellent agreement with FFR, superior to other image-based methods.

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