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Purpose. To explore and analyze the therapeutic effect of gamma globulins (GG) on Kawasaki disease (KD) in children and the influencing factors of short-term prognosis. Methods. First, 90 pediatric KD patients admitted between January 2019 and January 2021 were selected and divided into a control group (n = 40) and a research group (n = 50) according to the difference in treatment. In addition to routine treatment and nursing given to both groups, control group was given aspirin (ASA), based on which research group was supplemented with GG therapy. The treatment outcome and adverse events (AEs) of the two cohorts of patients were analyzed and compared, and the influencing factors of children's short-term prognosis were analyzed by logistics multivariate analysis. Results. Research group had a statistical higher overall response rate than control group, with significantly fewer cases suffering from AEs such as nausea and vomiting, diarrhea, rash, dizziness and headache, and coronary artery injury. On the other hand, logistics multivariate analysis identified that gender, body mass index (BMI), onset time, platelet (PLT), and treatment mode all independently influence the short-term prognosis of children with KD. Conclusions. GG therapy is effective in treating pediatric KD patients and can effectively prevent AEs. In addition, gender, BMI, onset-to-treatment time, PLT, C-reactive protein (CRP), and treatment methods are independent risk factors for short-term prognosis of children with KD. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases seriously endanger human physical and mental health and life safety, to investigate correlation between miR-let-7b and miR-29b and coronary artery calcification of various patients. At present, real-time fluorescence quantitative PCR (qRT-PCR) was used to detect the expression levels of plasma miR-let-7b and miR-29b in patients with coronary artery calcification and noncoronary artery calcification and to analyze whether the expression levels of miR-let-7b and miR-29b were different between the two groups. It was shown that there was no significant difference in the expression of miR-let-7d-3p between the two groups. But the expression of miR-29b in the observation group was significantly lower than that in the control group. Taken together, miR-29b might be a risk factor for coronary artery calcification and may be a marker for early diagnosis of coronary artery calcification. [ABSTRACT FROM AUTHOR]

Objective. Coronary heart disease (CHD) is considered an inflammatory relative disease. This study is aimed at analyzing the health information of serum interferon in CHD based on logistic regression and artificial neural network (ANN) model. Method. A total of 155 CHD patients diagnosed by coronary angiography in our department from January 2017 to March 2020 were included. All patients were randomly divided into a training set (n = 108) and a test set (n = 47). Logistic regression and ANN models were constructed using the training set data. The predictive factors of coronary artery stenosis were screened, and the predictive effect of the model was evaluated by using the test set data. All the health information of participants was collected. Expressions of serum IFN-γ, MIG, and IP-10 were detected by double antibody sandwich ELISA. Spearman linear correlation analysis determined the relationship between the interferon and degree of stenosis. The logistic regression model was used to evaluate independent risk factors of CHD. Result. The Spearman correlation analysis showed that the degree of stenosis was positively correlated with serum IFN-γ, MIG, and IP-10 levels. The logistic regression analysis and ANN model showed that the MIG and IP-10 were independent predictors of Gensini score: MIG (95% CI: 0.876~0.934, P < 0.001) and IP-10 (95% CI: 1.009~1.039, P < 0.001). There was no statistically significant difference between the logistic regression and the ANN model (P > 0.05). Conclusion. The logistic regression model and ANN model have similar predictive performance for coronary artery stenosis risk factors in patients with CHD. In patients with CHD, the expression levels of IFN-γ, IP-10, and MIG are positively correlated with the degree of stenosis. The IP-10 and MIG are independent risk factors for coronary artery stenosis. [ABSTRACT FROM AUTHOR]

Objective. This study was aimed at comparing the characteristics of coronary angiography based on intelligent algorithm in patients with acute non-ST-segment elevation myocardial infarction (NSTEMI) of different genders. Methods. Eighty patients were selected to segment the coronary angiogram using the convolutional neural network (CNN) algorithm, the input layer of the CNN was used to receive the image dataset, and three-dimensional data were input during semantic segmentation to achieve automatic segmentation of the target features. Segmentation results were quantitatively assessed by accuracy (Acc), sensitivity (Se), specificity (Sp), and Dice coefficient (Dice). The characteristics of coronary angiography were compared between the two groups. Results. The CNN algorithm had good segmentation effect, complete vessel extraction, and little noise, and Acc, Se, Sp, and Dice were 90.32%, 93.39%, 91.25%, and 89.75%, respectively. The proportion of diabetes mellitus was higher in female patients with NSTEMI (68.8%) than that in male patients (46.3%); the proportion of the left main coronary artery (LM) and left anterior descending artery (LAD) was lower in the female group (7.5%, 41.3%) than that in the male group (13.8%, 81.3%), and the difference between the two groups was statistically significant (P < 0.05). Conclusion. The CNN algorithm achieves accurate extraction of vessels from coronary angiographic images, and women with diabetes and hyperlipidemia are more likely to have NSTEMI than men, especially the elderly. [ABSTRACT FROM AUTHOR]

This study was to analyze the diagnostic value of coronary computed tomography angiography (CCTA) and fractional flow reserve (FFR) based on computer-aided diagnosis (CAD) system for coronary lesions and the possible impact of calcification. 80 patients who underwent CCTA and FFR examination in hospital were selected as the subjects. The FFR value of 0.8 was used as the dividing line and divided into the ischemic group (FFR ≤ 0.8) and nonischemic group (FFR > 0.8). The basic data and imaging characteristics of patients were analyzed. The maximum diameter stenosis rate (MDS %), maximum area stenosis rate (MAS %), and napkin ring sign (NRS) in the ischemic group were significantly lower than those in the nonischemic group (P < 0.05). Remodeling index (RI) and eccentric index (EI) compared with the nonischemic group had no significant difference (P > 0.05). The total plaque volume (TPV), total plaque burden (TPB), calcified plaque volume (CPV), lipid plaque volume (LPV), and lipid plaque burden (LPB) in the ischemic group were significantly different from those in the non-ischemic group (P < 0.05). MAS % had the largest area under curve (AUC) for the diagnosis of coronary myocardial ischemia (0.74), followed by MDS % (0.69) and LPV (0.68). CT-FFR had high diagnostic sensitivity, specificity, accuracy, truncation value, and AUC area data for patients in the ischemic group and nonischemic group. The diagnostic sensitivity, specificity, accuracy, cutoff value, and AUC area data of CT-FFR were higher in the ischemic group (89.93%, 92.07%, 95.84%, 60.51%, 0.932) and nonischemic group (93.75%, 90.88%, 96.24%, 58.22%, 0.944), but there were no significant differences between the two groups (P > 0.05). In summary, CT-FFR based on CAD system has high accuracy in evaluating myocardial ischemia caused by coronary artery stenosis, and within a certain range of calcification scores, calcification does not affect the diagnostic accuracy of CT-FFR. [ABSTRACT FROM AUTHOR]

Background. Risk factors of coronary heart disease have been discussed in the literature; however, conventional statistical models are not appropriate when the outcome of interest is number of vessels with obstructive coronary artery disease. In this paper, a novel statistical model is discussed to investigate the risk factors of number of vessels with obstructive coronary artery disease. Methods. This cross-sectional study was conducted on 633 elderly cardiovascular patients at Ghaem Hospital, Mashhad, Iran from September 2011 to May 2013. Clinical outcome is number of vessels with obstructive coronary artery disease (=0, 1, 2, 3), and predictor variables are baseline demographics and clinical features. A right-truncated zero-inflated double Poisson regression model is performed which can accommodate both underdispersion and excess zeros in the outcome. The goodness-of-fit of the proposed model is compared with conventional regression models. Results. Out of 633 cardiovascular patients, 327 were male (51.7%). Mean age was ~ 65 ± 7 years (for individuals with zero, one ,and two coronary artery stenosis) and ~ 66 ± 7 years (for individuals with three coronary artery stenosis). BMI (0.04 ± 0.01 , p = 0.011) and female gender (0.19 ± 0.09 , p = 0.032) were significant associated with the count part of the model, and only BMI (− 0.47 ± 0.2 , p = 0.011) was significantly predictive of logit part of the model. The goodness-of-fit measurements indicate that the proposed model outperforms the conventional regression models. Conclusion. The proposal regression model shows a better fit compared to the standard regression analysis in modeling number of vessels with obstructive coronary artery disease. Hence, using truncated zero-inflated double Poisson regression model—as an alternative model—is advised to study the risk factors of number of involved vessels of coronary artery stenosis. [ABSTRACT FROM AUTHOR]

A combination of various risk factors results in the development of coronary heart disease. The earlier that one identifies and deals with reversible risk factors for coronary heart disease, the greater the chance of recovery. The main goal of this research is to learn whether risk variables are associated with greater extent of coronary artery disease in people with coronary heart disease. This article selects 290 patients who had had coronary angiography in our hospital from September 2018 to March 2019 using a retrospective research and analytic methodology. Coronary angiography split the patients into two groups: those with coronary heart disease and those without. To determine the correlation between risk factors and a score related to heart disease, computer-aided statistical analysis of data about the differences in those risk factors was performed. The results were analyzed using the Spearman correlation and partial correlation, and the relationship between risk factors and Gensini score was analyzed by multiple linear regression. For the analysis, binary logistic regression was used to calculate the correlation between the risk factors of coronary heart disease and the probability of developing coronary heart disease. The findings concluded that increased age, smoking, elevated hs-CRP, HbA1c, hypertension, diabetes, and hyperuricemia are all contributors to coronary heart disease. Coronary heart disease is an independent risk factor for this condition. Many of the factors that play a role in the long-term development of the severity of coronary artery disease, such as hypertension, diabetes, smoking, elevated hs-CRP, decreased HDL-C, raised LDL-C, and TG, are commonly found in men. hs-CRP is the primary risk factor for the degree of coronary artery stenosis and could contribute to the progression of the condition by playing a major role in creating more stenosis. [ABSTRACT FROM AUTHOR]

Coronary CT angiography (CTA) with the characteristics of noninvasive and simple operation is widely used in the diagnosis of coronary artery stenosis. The choice of contrast agent exerts an important impact on the imaging quality of CTA. Conventional iodine contrast agents are easily excreted by the kidneys, from which the imaging window is short, and the imaging quality is poor. Metal nanomaterials have unique optical properties and have broad application prospects in imaging. Our aim is to explore the value of gold nanorod contrast agent in the diagnosis of coronary heart disease. A gold nanorod suspension was first prepared, and the prepared gold nanorod was uniform and had good dispersibility. It can be seen from the light absorption curve that there are two obvious peaks on the UV absorption peak of the gold nanorods. The gold nanorods were cultured in different solutions, and it was found that the particle size of the gold nanorods did not change significantly within 72 hours, indicating that the prepared gold nanorods had good stability. When observing the damage degree of mouse kidney tissue, it was shown that the damage degree of gold nanorod contrast agent to mouse kidney tissue was less than that of iodine contrast agent. The above results indicate that the gold nanorod contrast agent has good stability and safety. Therefore, our study demonstrated that the gold nanorod contrast agent has high value in the diagnosis of coronary arteries and the analysis of plaque properties. [ABSTRACT FROM AUTHOR]

The motive of this article is to present the case study of patients to investigate the association between the ultrasonographic findings of lower extremity vascular disease (LEAD) and plaque formation. Secondly, to examine the association between the formation of coronary artery and carotid artery atherosclerosis in patients with type 2 diabetes mellitus. 124 patients with type 2 diabetes (64 males and 60 females with the age group 25-78 years) are considered for the research studies who have registered themselves in the Department of Endocrinology and Metabolism from April 2017 to February 2019. All participants have reported their clinical information regarding diabetes, alcohol consumption, smoking status, and medication. The blood samples from subjects are collected for measurement of HbA1c, total cholesterol, triglycerides, HDL-c, and LDL-c levels. Two-dimensional ultrasound has been used to measure the inner diameter, peak flow velocity, blood flow, and spectral width of the femoral artery, pop artery, anterior iliac artery, posterior tibial artery, and dorsal artery and to calculate the artery stenosis degree. Independent factors of atherosclerosis are determined by multivariate logistic regression analysis. The results are evaluated within the control group and it is found that there is no significant impact of gender, age, and body mass index (P > 0.05) on the lower extremity vascular diseases. Those with smoking, alcohol consumption, hypertension, and dyslipidemia have higher positive rate (P < 0.05). The type 2 diabetes mellitus group has higher diastolic blood pressure and lower triglyceride (P < 0.05). Diastolic blood pressure, HbA1C, total cholesterol, HDL-c, and LDL-C are not remarkably dissimilar between the type 2 diabetes mellitus group and the control group (P > 0.05). Compared with the control group, the type 2 diabetes mellitus group has higher frequency of lower extremity vascular diseases in the dorsal artery than in the pop artery (P < 0.05). The blood flow of type 2 diabetes mellitus group is found to be lower than that of the control group, especially in the dorsal artery (P < 0.05). The blood flow velocity of the dorsal artery is accelerated (P < 0.01). Among 117 patients of type 2 diabetes mellitus (94.35%) with a certain degree of injury, there are 72 cases of type I carotid stenosis (58.06%), 30 cases of type II carotid stenosis (24.19%), and 15 cases of type III carotid stenosis (12.10%). Out of 108 subjects in the control group, there are 84 cases of type 0 carotid stenosis (77.78%), 19 cases of type I carotid stenosis (17.59%), 5 cases of type II carotid stenosis (4.63%), and 0 case of type III carotid stenosis (0.00%). Compared with the control group, carotid stenosis is more common in patients with type 2 diabetes mellitus (P < 0.05). Age, smoking, duration of diseases, systolic blood pressure, and degree of carotid stenosis are found to be associated with atherosclerosis. The findings suggest that the color Doppler ultrasonography can give early warning when applied in patients with carotid and lower extremity vascular diseases to delay the incidence of diabetic macroangiopathy and to control the development of cerebral infarction, thus providing an important basis for clinical diagnosis and treatment. [ABSTRACT FROM AUTHOR]

Coronary angiography is the "gold standard" for the diagnosis of coronary heart disease, of which vessel segmentation and identification technologies are paid much attention to. However, because of the characteristics of coronary angiograms, such as the complex and variable morphology of coronary artery structure and the noise caused by various factors, there are many difficulties in these studies. To conquer these problems, we design a preprocessing scheme including block-matching and 3D filtering, unsharp masking, contrast-limited adaptive histogram equalization, and multiscale image enhancement to improve the quality of the image and enhance the vascular structure. To achieve vessel segmentation, we use the C-V model to extract the vascular contour. Finally, we propose an improved adaptive tracking algorithm to realize automatic identification of the vascular skeleton. According to our experiments, the vascular structures can be successfully highlighted and the background is restrained by the preprocessing scheme, the continuous contour of the vessel is extracted accurately by the C-V model, and it is verified that the proposed tracking method has higher accuracy and stronger robustness compared with the existing adaptive tracking method. [ABSTRACT FROM AUTHOR]

In this paper, we propose a rapid rigid registration method for the fusion visualization of intraoperative 2D X-ray angiogram (XA) and preoperative 3D computed tomography angiography (CTA) images. First, we perform the cardiac cycle alignment of a patient's 2D XA and 3D CTA images obtained from a different apparatus. Subsequently, we perform the initial registration through alignment of the registration space and optimal boundary box. Finally, the two images are registered where the distance between two vascular structures is minimized by using the local distance map, selective distance measure, and optimization of transformation function. To improve the accuracy and robustness of the registration process, the normalized importance value based on the anatomical information of the coronary arteries is utilized. The experimental results showed fast, robust, and accurate registration using 10 cases, each of the left coronary artery (LCA) and right coronary artery (RCA). Our method can be used as a computer-aided technology for percutaneous coronary intervention (PCI). Our method can be applied to the study of other types of vessels. [ABSTRACT FROM AUTHOR]

Seed point is prerequired condition for tracking based method for extracting centerline or vascular structures from the angiogram. In this paper, a novel seed point detection method for coronary artery segmentation is proposed. Vessels on the image are first enhanced according to the distribution of Hessian eigenvalue in multiscale space; consequently, centerlines of tubular vessels are also enhanced. Ridge point is extracted as candidate seed point, which is then refined according to its mathematical definition. The theoretical feasibility of this method is also proven. Finally, all the detected ridge points are checked using a self-adaptive threshold to improve the robustness of results. Clinical angiograms are used to evaluate the performance of the proposed algorithm, and the results show that the proposed algorithm can detect a large set of true seed points located on most branches of vessels. Compared with traditional seed point detection algorithms, the proposed method can detect a larger number of seed points with higher precision. Considering that the proposed method can achieve accurate seed detection without any human interaction, it can be utilized for several clinical applications, such as vessel segmentation, centerline extraction, and topological identification. [ABSTRACT FROM AUTHOR]

Of interest is the accurate and robust delineation of vessel center-lines for complete arterial tree structure in coronary angiograms which is an imperative step towards 3D reconstruction of coronary tree and feature-based registration of multiple view angiograms. Most existing center-line tracking methods encounter limitations in coping with abrupt variations in local artery direction and sudden changes of lumen diameter that occur in the vicinity of arterial lesions. This paper presents an improved center-line tracing algorithm for automatic extraction of coronary arterial tree based on robust local features. The algorithm employs an improved scanning schema based on eigenvalues of Hessian matrix for reliable identification of true vessel points as well as an adaptive look-ahead distance schema for calculating the magnitude of scanning profile. In addition to a huge variety of clinical examples, a well-established vessel simulation tool was used to create several synthetic angiograms for objective comparison and performance evaluation. The experimental results on the accuracy and robustness of the proposed algorithm and its counterparts under difficult situations such as poor image quality and complicated vessel geometry are presented. [ABSTRACT FROM AUTHOR]