Diagnosis Of Coronary Heart Disease Research Articles

РАДИОНУКЛИДНЫЕ ПЕРФУЗИОННЫЕ ИССЛЕДОВАНИЯ МИОКАРДА С ПОЗИТРОН-ИЗЛУЧАЮЩИМИ РАДИОНУКЛИДАМИ: ОБЗОР

Non-communicable diseases, coronary heart disease has ranked first among the causes of morbidity and mortality according to WHO over the past decade and a half in most developed countries. Molecular imaging techniques make it possible to detect this disease at an early stage, determine the prognosis, risks and the need for intervention. Radionuclide diagnostics can be widely used in patients with cardiac diseases to assess the viability of cardiomyocytes and myocardial perfusion and to detect the presence and extent of perfusion defects, stress-induced ischemia, and post-infarction changes using single photon emission computed tomography and positron emission tomography. Compared with foreign countries, radionuclide imaging methods are not currently widely used in cardiology practice in Russia. This review highlights the physical foundations of single-photon emission tomography and positron emission tomography, the physiological and pathophysiological basis of radiopharmaceutical uptake in myocardial tissue, the mechanisms and procedures for performing functional pharmacological and physical stress tests, and recent data in the field of radionuclide imaging of myocardial pathology. This review aims to acquaint the reader with the world practices of using positron-emitting radionuclides in diagnostic procedures, highlighting both their basic principles and the latest achievements in this area. The review focuses on the practice of using 82Rb in the assessment of myocardial perfusion, including in comparison with other positron-emitting radionuclides, as one of the promising areas of development in the diagnosis of coronary heart disease.

Deep learning for myocardial ischemia auxiliary diagnosis using CZT SPECT myocardial perfusion imaging.

The World Health Organization reported that cardiovascular disease is the most common cause of death worldwide. On average, one person dies of heart disease every 26 min worldwide. Deep learning approaches are characterized by the appropriate combination of abnormal features based on numerous annotated images. The constructed convolutional neural network (CNN) model can identify normal states of reversible and irreversible myocardial defects and alert physicians for further diagnosis. Cadmium zinc telluride single-photon emission computed tomography myocardial perfusion resting-state images were collected at Chang Gung Memorial Hospital, Kaohsiung Medical Center, Kaohsiung, Taiwan, and were analyzed with a deep learning convolutional neural network to classify myocardial perfusion images for coronary heart diseases. In these grey-scale images, the heart blood flow distribution was the most crucial feature. The deep learning technique of You Only Look Once was used to determine the myocardial defect area and crop the images. After surrounding noise had been eliminated, a three-dimensional CNN model was used to identify patients with coronary heart diseases. The prediction area under the curve, accuracy, sensitivity, and specificity was 90.97, 87.08, 86.49, and 87.41%, respectively. Our prototype system can considerably reduce the time required for image interpretation and improve the quality of medical care. It can assist clinical experts by offering accurate coronary heart disease diagnosis in practice.

Myeloperoxidase, troponin I and C-reactive protein in blood of patients before and after coronary artery bypass grafting

The study of dynamics of laboratory markers before and after heart surgery makes it possible to predict the risks of postoperative complications. Troponin I is ‘the gold standard’ for diagnosing acute myocardial infarction, but with an increase in the marker after heart surgery, the interpretation of the results can be difficult. Therefore, the search for new combinations of laboratory markers can help in assessing the degree of myocardial damage after surgery, as well as the risk of complications. Myeloperoxidase as a new laboratory indicator is of interest, since there are many studies on the prognostic value of an increase in this marker in patients with coronary heart disease in the development of cardiovascular complications. In the present study, the dynamics of myeloperoxidase, troponin I, and C-reactive protein in patients (n = 60) with a confirmed diagnosis of coronary heart disease before and after elective coronary artery bypass grafting under cardiopulmonary bypass was assessed. The following results were obtained: an increased level of myeloperoxidase in blood plasma in patients before surgery is an additional indicator in assessing the risk of postoperative complications, regardless of the concentration of C-reactive protein. A correlation was found between the concentration of troponin I and the level of myeloperoxidase in the blood, as well as between the duration of cardiopulmonary bypass and the level of MPO 24 hours after surgery.

Calcium-channel blockers: Clinical outcome associations with reported pharmacogenetics variants in 32 000 patients.

Pharmacogenetic variants impact dihydropyridine calcium-channel blockers (dCCBs; e.g., amlodipine) treatment efficacy, yet evidence on clinical outcomes in routine primary care is limited. Reported associations in pharmacogenomics knowledge base PharmGKB have weak supporting evidence. We aimed to estimate associations between reported pharmacogenetic variants and incident adverse events in a community-based cohort prescribed dCCB. We analysed up to 32 360 UK Biobank participants prescribed dCCB in primary care (from UK general practices, 1990-2017). We investigated 23 genetic variants. Outcomes were incident diagnosis of coronary heart disease, heart failure (HF), chronic kidney disease, oedema and switching antihypertensive medication. Participants were aged 40-79 years at first dCCB prescription. Carriers of rs877087 T allele in RYR3 had increased risk of hazard ratio (HF 1.13: 95% confidence interval 1.02 to 1.25, P= .02). Although nonsignificant after multiple testing correction, the association is consistent with prior evidence. We estimated that if rs877087 T allele could experience the same treatment effect as noncarriers, the incidence of HF in patients prescribed dCCB would reduce by 9.2% (95% confidence interval 3.1 to 15.4). In patients with a history of heart disease prior to dCCB (n =2296), rs877087 homozygotes had increased risk of new coronary heart disease or HF compared to CC variant. rs10898815 in NUMA1 and rs776746 in CYP3A5 increased likelihood of switching to an alternative antihypertensive. The remaining variants were not strongly or consistently associated with studied outcomes. Patients with common genetic variants in NUMA1, CYP3A5 and RYR3 had increased adverse clinical outcomes. Work is needed to establish whether outcomes of dCCB prescribing could be improved by prior knowledge of pharmacogenetics variants supported by clinical evidence of association with adverse events.

A TWO-STAGE EXTRACTION NETWORK FOR THE OPTICAL COHERENCE TOMOGRAPHY CONTOUR

Optical coherence tomography (OCT) with high resolution was found lucrative for coronary heart disease diagnosis and treatment such as evaluating the degree of vascular stenosis and guiding stent implantation. Lumen contour is an essential information for assessing the shape and stenosis of blood vessels. The automatic and accurate extraction of lumen contour can significantly reduce the burden of doctors and improve the efficiency of diagnosis and treatment of coronary heart disease. The existing contour segmentation methods have poor performance in extracting the contour of the image with a missing blood vessel wall. Therefore, this paper proposes a two-stage contour extraction method based on deep learning. First, the method uses the basic contour extraction network to complete the feature image extraction and coarse contour segmentation, then inputs the feature image into the attentional class feature (ACF) module, and uses the coarse segmentation results to guide the generation of the new feature map for the refined contour segmentation. Finally, the fully connected conditional random field (CRF) module is used for post-processing yielding a more refined and smooth segmentation boundary. The experiments show that compared with the other methods, the lumen contour segmentation method proposed in this paper can adequately resolve the problem of partial vessel wall absence in OCT images and improve the accuracy of lumen contour extraction.

PREFACE: A SPECIAL SELECTION ON EMERGING TECHNIQUES FOR BIOMECHANICS–PART II

PREFACE: A SPECIAL SELECTION ON EMERGING TECHNIQUES FOR BIOMECHANICS–PART II

Computed Tomography and Other Imaging Modalities in Pediatric Congenital Heart Disease

Congenital heart defects (CHD) are the most common congenital disabilities. Early and accurate diagnosis of coronary heart disease is very important for patients to get timely and effective treatment. In recent years, the accuracy of coronary heart disease diagnosis has been greatly improved with the development of medical imaging equipment and technology. At present, the clinical application of echocardiogram (echo), cardiovascular magnetic resonance (CMR) and computed tomography angiography (CTA) in coronary heart disease anatomy and function has increased significantly, which plays an important role in preoperative diagnosis, intraoperative monitoring, and postoperative recovery evaluation. However, each imaging technique has its indications. Providing the best examination plan for patients requires clinicians and radiologists’ close cooperation. Therefore, this study reviewed the imaging techniques for diagnosing coronary heart disease.

Causes of shortness of breath in patients with stable coronary heart disease

Shortness of breath is a common debilitating and limiting the quality of life symptom, which leads to frequent requests for medical help. The review summarizes data on the causes of shortness of breath in stable patients with suspected coronary heart disease (CHD), with an established diagnosis of CHD, as well as in patients with other cardiovascular diseases. PubMed, Science Direct, Google Scholar, and eLibrary search platforms were used for the selection of publications, the review includes publications from 2009 to 2021. Patients with suspected coronary artery disease complaining of shortness of breath, in addition to myocardial ischemia, not always associated with stenosing atherosclerosis of the coronary arteries. The following causes of shortness of breath are described: bronchial obstruction, psychogenic hyperventilation, and depression. When studying patients with other cardiovascular diseases, the causes of shortness of breath turned out to be even more diverse: transient myocardial ischemia (including in cases where the cause of shortness of breath initially appears to be non-ischemic), chronic heart failure, cardiac arrhythmias, pathology of the heart valves, thyroid dysfunction, lung diseases, obesity, anemia, etc. Thus, despite the limited evidence, it is obvious that in the presence of paroxysmal dyspnea in patients with stable coronary heart disease, its causes are more diverse than transient myocardial ischemia.

Composite carotid intima-media thickness as a risk predictor of coronary heart disease in a selected population in Sri Lanka.

Segment-specific variations of carotid intima-media thickness (CIMT) have not been assessed in South Asian populations. The purpose of this study was to determine if segment-specific CIMTs or a composite-CIMT score is a better risk predictor of coronary heart disease in South Asian populations. A comparative prospective study was conducted from November 2019 to October 2020 in a hospital in Colombo, Sri Lanka. Based on pre-defined inclusion and exclusion criteria, cases (having a diagnosis of Coronary Heart Disease (CHD), n = 338) and controls (non-CHD group, n = 356) were recruited. Ultrasound examination of the common carotid (CCA), the carotid bulb (CB) and the internal carotid segments (ICA) of the carotid vessels was conducted by a radiologist, and CIMTs were measured. A composite-CIMT score defined as the average value of all six segments of the left and right sides was derived. 694 participants were enrolled (male n = 399, 57.5%). The mean (±SD) age of the study sample was 60.2 (±9.86) years. There were variations in segment-specific values between the left and right vessels. The mean composite-CIMT value of the CHD group was significantly higher than that of the non-CHD group. A composite-CIMT score of 0.758 had a sensitivity of 98.4% and a specificity of 64.6% in distinguishing CHD from non-CHD groups (Area under the curve (AUC): 0.926). Carotid artery segment-specific CIMT variations were present in this population. The composite CIMT score is better than segment-specific CIMTs in predicting CHD and may be used to predict CHD in this population.

DeTransUnet: attenuation correction of gated cardiac images without structural information

Objective. Myocardial perfusion imaging (MPI) with positron emission tomography (PET) is a non-invasive imaging method, and it is of great significance to the diagnosis and prognosis of coronary heart disease. Attenuation correction (AC) for PET images is a necessary step for further quantitative analysis. In order not to use magnetic resonance (MR) or computed tomography (CT) images for AC, this work proposes DeTransUnet to obtain AC PET images directly from no-attenuation corrected (NAC) PET images. Approach. The proposed DeTransUnet is a 3D structure which combines the multi-scale deformable transformer layers and the 3D convolutional neural network (CNN). And it integrates the advantages of transformer with long-range dependence and CNN suitable for image calculation. The AC images using CT images for AC and scatter correction (SC) and are considered as training labels, while the NAC images are reconstructed without AC and SC. Standard uptake value (SUV) values are calculated for both NAC and AC images to exclude the influence of weight and injection dose. With NAC SUV images as the inputs of the DeTransUnet, the outputs of DeTransUnet are AC SUV images. Main results. The proposed DeTransUnet was performed on an MPI gated-PET dataset, and the results were compared with Unet2D and Unet2.5D. The metrics of the whole image and the left ventricular myocardium show that the proposed method has advantages over other deep learning methods. Significance. The proposed DeTransUnet is a novel AC framework that does not require CT or MR images. It can be used as an independent AC method on PET/MR instrument. In addition, when CT images contain defects or cannot be registered with PET images on PET/CT instrument, DeTransUnet is able to repair the defects and keep consistent with the NAC images.

Relation of Exercise Capacity to Incident Heart Failure Among Men and Women With Coronary Heart Disease (from the Henry Ford Exercise Testing [FIT] Project)

Exercise capacity (EC) is inversely related to the risk of cardiovascular disease and incident heart failure (HF) in healthy subjects. However, there are no present studies that exclusively evaluate EC and the risk of incident HF in patients with known coronary heart disease (CHD). We aimed to determine the relation between EC and incident HF in patients with an established clinical diagnosis of CHD. We retrospectively identified 8,387 patients (age 61 ± 12 years; 30% women; 33% non-White) with a history of myocardial infarction (MI) or coronary revascularization procedure and no history of HF at the time of a clinically indicated exercise stress test completed between 1991 and 2009. EC was quantified in metabolic equivalents of task (METs) estimated from treadmill testing. Incident HF was identified through June 2010 from administrative databases based on ≥3 encounters with International Classification of Diseases, Ninth Revision 428.x. Cox regression analysis was used to evaluate the risk of incident HF associated with METs. Covariates included age; gender; race; hypertension, diabetes, hyperlipidemia, smoking, and MI; medications for CHD and lung diseases; and clinical indication for treadmill testing. During a median follow-up of 8.2 years (interquartile range 4.7 to 12.4 years) after the exercise test, 23% of the cohort experienced a new HF diagnosis. Lower EC categories were associated with higher HF incidence compared with METs ≥12, with nearly fourfold greater adjusted risk among patients with METs <6. Per unit increase in METs of EC was associated with a 12% lower adjusted risk for HF. There was no significant interaction based on race (p=0.06), gender (p=0.88), age ≤61 years (p=0.60), history of MI (p=0.31), or diabetes (p=0.38). This study reveals that among men and women with CHD and no history of HF, EC is independently and inversely related to the risk of future HF.

Effect Analysis and Evaluation of Serum Bilirubin and Uric Acid Test in Clinical Diagnosis of Coronary Heart Disease

Effect Analysis and Evaluation of Serum Bilirubin and Uric Acid Test in Clinical Diagnosis of Coronary Heart Disease

Early Diagnosis and Treatment of Coronary Heart Disease with Image Features of Optical Coherence Tomography under Adaptive Segmentation Algorithm.

This research was aimed at exploring the application value of optical coherence tomography (OCT) images under adaptive segmentation algorithm in the early diagnosis of coronary heart disease (CHD). Eighty-two patients with CHD were included, who were to undergo coronary angiography (CAG) to confirm their condition. According to the diagnostic criteria of CHD in the American Coronary Artery Surgery Study (CASS), the patients were divided into the stable plaque group (41 cases) and unstable plaque group (41 cases). Besides, 20 healthy volunteers were selected as the control group, and all of them underwent OCT scans. On the basis of a fourth-order partial differential equation (PDE) and active contour (AC) model, a novel adaptive image segmentation algorithm PDE-AC was constructed and used for OCT image processing. No significant difference was found in general clinical data and serological indicators in the control group compared to the other two groups (P > 0.05). The lipid plaque length, degree of stenosis, and lipid pool angle, macrophages and intimal erosion, and plaque fissure in the unstable plaque group were highly greater than those in the stable plaque group. The fibrous cap thickness (FCT) was significantly thinner than that in the stable plaque group (P < 0.05). The diagnostic sensitivity, specificity, and accuracy of OCT under PDE-AC algorithm for CHD (91.53%, 84.08%, and 95.38%) were markedly higher than those of single OCT (83.46%, 75.11%, and 88.02%) (P < 0.05). In summary, OCT images under PDE-AC algorithm did better than simple OCT images in the diagnosis of CHD. Lipid plaque length, degree of stenosis, and lipid pool angle, macrophage and intimal erosion, plaque fissure, and FCT were important indicators for judging plaque stability, having the better clinical application value.

Early menopause and a low body mass index are associated with an increased risk of coronary heart disease in Japanese women.

The primary objective was to investigate the association between early menopause and cardiovascular disease (CVD) prevalence in Japanese women. The secondary objective was to ascertain the association with CVD risk factors. In this cross-sectional study, 7,239 naturally menopausal women from the Yamagata Cohort Study who completed an annual health visit and questionnaire between 2009 and 2015 were divided into three groups according to their age at menopause (women experiencing menopause at <45, 45-49 y, and ≥ 50 y). The diagnosis of coronary heart disease (CHD) and stroke were made by self-report, while hypertension, hyperlipidemia, and diabetes mellitus, were diagnosed by vital signs and laboratory parameters. Logistic regression analysis was used to estimate the associations between age at menopause and CVD prevalence and CVD risk factors. A total of 354 (4.9%) and 156 (2.2%) women reported a history of CHD and stroke, respectively. Women experiencing menopause at <45 years had a higher prevalence of CHD than those experiencing menopause at ≥50 years (OR 1.77, 95% CI 1.07-2.90; P = 0.023). Stroke, hypertension, diabetes mellitus, and hyperlipidemia were equally prevalent among the three groups. Significant interactions were observed between age at menopause and body mass index (BMI) (P = 0.025) and parity (P = 0.025). Among those with a BMI < 18.5 or parity ≥2, women experiencing menopause at <45 years had a significantly higher prevalence of CHD than those experiencing menopause at ≥50 years. Early menopause and low BMI were associated with CHD in Japanese women.

THE EFFECT OF COVID-19 ON MYOCARDIAL DAMAGE: A CLINICAL CASE

Despite the fact that the general clinical manifestations of COVID-19 are well known, there remain problems associated with the impact of COVID-19 on human health, in addition to its effects on the respiratory system. Patients with COVID-19 and concomitant cardiovascular diseases are more likely to be hospitalized and to pass treatment in the intensive care units and to have worse prognoses. The article discusses the problems arising from the effect of type 2 coronavirus acute respiratory syndrome (SARS-CoV-2) on the cardiovascular system, starting with the mechanisms associated with angiotensin converting enzyme 2 (ACE2) receptors, as well as discusses cases of major pathological changes in the heart and blood vessels that are detected in these patients. In addition to the known risk factors for severe COVID-19: cardiovascular diseases, diabetes mellitus, chronic lung diseases and old age, even young patients without a history of risk factors may develop myocardial damage. We present a description of a clinical case of acute myocardial infarction against the background of a new coronavirus infection COVID-19 in a patient aged 28 years with a diagnosis of coronary heart disease.

PPBP gene as a biomarker for coronary heart disease risk in postmenopausal Thai women.

BackgroundEstrogen is an important ovarian hormone with anti-atherogenic and cardioprotective effects. Postmenopausal women have lower estrogen levels, associated with significantly higher risks of coronary heart disease (CHD) and CHD-related death. Effective biomarkers for the diagnosis, prediction, and treatment of CHD are needed to address this problem and thus reduce the mortality due to CHD in postmenopausal women. We recently reported that the PPBP and DEFA1/DEFA3 genes may be feasible synergistic biomarkers for CHD risk in Thai men with hyperlipidemia. The PPBP gene encodes pro-platelet basic protein (PPBP) from activated platelets, and DEFA1/DEFA3 encodes human neutrophil peptides (HNP) 1–3, mainly produced by activated neutrophils. Both platelets and neutrophils are involved in chronic inflammation during the development of atherogenesis and CHD. This study investigated the potential roles of PPBP and DEFA1/DEFA3 and their proteins as biomarkers for CHD risk in postmenopausal Thai women.MethodsThis cross-sectional study enrolled 90 postmenopausal Thai women, including 12 healthy controls (N), 18 patients with hyperlipidemia (H), and 21 patients diagnosed with CHD. The remaining 39 women were receiving cholesterol-lowering drugs for hyperlipidemia (HD) were excluded from the study. All CHD patients underwent coronary bypass grafting or coronary angioplasty. PPBP and DEFA1/DEFA3 mRNA expression levels in peripheral blood mononuclear cells isolated from heparinized blood were determined by quantitative reverse-transcription polymerase chain reaction. Levels of PPBP and HNP-1–3 proteins in corresponding plasma samples were assessed by enzyme-linked immunosorbent assay. Differences in parameters were compared among groups and correlations between parameters and clinical manifestations were analyzed.ResultsPPBP mRNA and protein levels were significantly increased in the CHD group compared with the N and H groups. In contrast, DEFA1/DEFA3 mRNA and HNP-1–3 protein levels did not differ significantly among the groups. None of the levels were associated with any of the clinical parameters analyzed in this study.ConclusionThe results indicate that gene and protein expression levels of PPBP, but not DEFA1/DEFA3, and HNP-1–3, may be feasible biomarkers for assessing CHD risk in postmenopausal Thai women with hyperlipidemia.

Artificial Intelligence in Coronary CT Angiography: Current Status and Future Prospects

Coronary heart disease (CHD) is the leading cause of mortality in the world. Early detection and treatment of CHD are crucial. Currently, coronary CT angiography (CCTA) has been the prior choice for CHD screening and diagnosis, but it cannot meet the clinical needs in terms of examination quality, the accuracy of reporting, and the accuracy of prognosis analysis. In recent years, artificial intelligence (AI) has developed rapidly in the field of medicine; it played a key role in auxiliary diagnosis, disease mechanism analysis, and prognosis assessment, including a series of studies related to CHD. In this article, the application and research status of AI in CCTA were summarized and the prospects of this field were also described.

Intake of whole grain foods and risk of coronary heart disease in US men and women

BackgroundEpidemiological studies have demonstrated a favorable association of whole grain intake with coronary heart disease (CHD) risk, although whether such an inverse association holds true for individual whole grain foods that have various nutritional profiles has not been examined.MethodsWe followed 74,244 women from Nurses’ Health Study since 1986, 91,430 women from Nurses’ Health Study II since 1991, and 39,455 men from the Health Professionals Follow-Up Study since 1984, who did not have a history of cardiovascular disease or cancer at baseline. Intake of seven individual whole grain foods was repeatedly assessed using a validated semi-quantitative food frequency questionnaire every 2–4 years since baseline. CHD diagnoses were ascertained through review of medical records or death certificates.ResultsWe documented 9461 CHD cases during an average of 25.8 years’ follow-up. In the multivariable-adjusted model, the pooled hazard ratio (HR) (95% CI) of CHD risk corresponding to each one serving/day consumption of total whole grains was 0.93 (0.90–0.95; p trend <0.0001). Higher consumption of most individual whole grain foods was associated with significantly lower risk of CHD. Comparing participants consuming ≥1 serving/day with those consuming < 1 serving/month, the multivariable-adjusted pooled HRs (95% CIs) of CHD were 0.83 (0.78–0.89) for whole grain cold breakfast cereal, 0.92 (0.86–0.99) for dark bread, and 1.08 (0.96–1.22) for popcorn. For other whole grain foods with lower overall intake levels, comparing intake level of ≥2 servings/week with < 1 serving/month, the pooled hazard ratios (95% CIs) were 0.79 (0.74–0.84) for oatmeal, 0.79 (0.71–0.87) for brown rice, 0.84 (0.78–0.90) for added bran, and 0.87 (0.77–0.99) for wheat germ. Cubic spline regression suggested non-linear associations for certain whole grain foods: the risk reduction plateaued approximately over 2 servings/day for total whole grains, 0.5 serving/day for both cold breakfast cereal and dark bread, 0.5 serving/week for oatmeal, 1 serving/week for brown rice, and 2 serving/week for added bran (p for non-linearity <0.01 for all associations).ConclusionsThese data suggest that higher consumption of total whole grains, as well as individual whole grain foods except popcorn, were significantly associated with lower CHD risk. The inverse associations may plateau at various intake levels for total whole grain and individual whole grain foods. This study provides further evidence in support of increasing whole grain intake for the prevention of CHD in US populations.

Classification of Myocardial Blood Flow based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging using Hierarchical Bayesian Models

AbstractDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising approach to assess microvascular blood flow (perfusion) within the myocardium, and the Fermi microvascular perfusion model is widely applied to extract estimates of the myocardial blood flow (MBF) from DCE-MRI data sets. The classification of myocardial tissues into normal (healthy) and hypoperfused (lesion) regions provides new opportunities for the diagnosis of coronary heart disease and for advancing our understanding of the aetiology of this highly prevalent disease. In the present paper, the Fermi model is combined with a hierarchical Bayesian model (HBM) and a Markov random fields prior to automate this classification. The proposed model exploits spatial context information to smooth the MBF estimates while sharpening the edges between lesions and healthy tissues. The model parameters are approximately sampled from the posterior distribution with Markov chain Monte Carlo (MCMC), and we demonstrate that this enables robust classification of myocardial tissue elements based on estimated MBF, along with sound uncertainty quantification. A well-established traditional method, based on a Gaussian mixture model (GMM) trained with the expectation–maximisation algorithm, is used as a benchmark for comparison.

Clinical value and expression of Homer 1, homocysteine, S-adenosyl-l-homocysteine, fibroblast growth factors 23 in coronary heart disease

BackgroundThis study aimed to explore clinical value and expression of Homer 1, S-adenosyl-l-homocysteine (SAH), homocysteine (Hcy), fibroblast growth factors (FGF) 23 in coronary heart disease (CHD).MethodsFrom March 2020 to April 2021, a total of 137 patients with CHD and 138 healthy subjects who came to our hospital for physical examination and had no cardiovascular disease were retrospectively enrolled, and they were assigned to the CHD group and the control group, respectively. Patients in the CHD group were divided into stable angina pectoris (SAP) group (n = 48), unstable angina pectoris (UAP) group (n = 46), and acute myocardial infarction (AMI) group (n = 43) according to clinical characteristics for subgroup analysis. The degree of coronary artery stenosis was assessed by Gensini score, which is a reliable assessment tool for the severity of coronary artery disease. The levels of Homer 1, SAH, Hcy, and FGF 23 were tested and compared. Spearman correlation analysis was used to analyze the correlation between serum Homer1, SAH, Hcy, FGF23 levels and Gensini score, and multivariate unconditional Logistic regression was used to analyze the risk factors of coronary heart disease.ResultsDemographic characteristics of each group were comparable (P > 0.05). The body mass index (BMI), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglyceride (TG), and glucose levels of the SAP group, UAP group and AMI group were significantly higher than those of the control group, and the number of patients with smoking, alcohol consumption, hypertension, and diabetes history was significantly more than that of the control group, respectively (P < 0.05). The level of high-density lipoprotein cholesterol (HDL-C) of each subgroup was significantly lower than the control group (P < 0.05). The above indicators showed no significant difference among three subgroups (P > 0.05). Serum SAH, Hcy, Homer1 and FGF23 levels in each subgroup were significantly higher than those in control group (P < 0.05). And above indicators in SAP group and UAP group were significantly lower than those in AMI group (P < 0.05), and the levels of above indicators in SAP group were significantly lower than those in UAP group (P < 0.05). The results of Spearman correlation analysis showed that serum Homer1, FGF23, SAH, Hcy levels were positively correlated with Gensini score (r = 0.376, 0.623, 0.291, 0.372, all P < 0.01). Multivariate logistic regression analysis showed that smoking, hypertension, diabetes, alcohol consumption, obesity, HDL-C, FGF23, SAH, Hcy, Homer 1 were independent risk factors for coronary heart disease.ConclusionThe levels of FGF23, SAH, Hcy, and Homer1 tend to increase in patients with CHD compared with normal population, and the more severe the disease, the higher the levels, which has certain reference value for the clinical diagnosis of CHD and the evaluation and monitoring of the disease.