This paper tried to address how to apply the relative concepts and methods of evidence-based medicine in clinical practice of cardiology, especially in diagnosis and treatment, with an aim to promote the cardiovascular evidence-based medicine in China.
The randomized controlled trial is the best evidence in the evidence-based medicine. The cardiovascular disease internal department is the typical example of the evidence-based medicine. A serial large-scale randomized controlled trials provided the evidence and improved clinical treatment level. For normal development of a large-scale randomized controlled trials need to enhance the standard management.
With the discovery of cardiac stem cell, the conception of the heart considered to be a terminally differentiated organ was changed. Cardiac stem cells possess the common characteristics of self-renew, clone formation and differentiating into cardiomyocyte, smooth muscle cell, and endothelial cell. Because of the properties of tissue specificity and lineage commitment, cardiac stem cells are considered to have great advantages over other stem cells in the treatment of cardiovascular disease. However, the low rate of engraftment still remains a problem to be solved. In recent years, people attempted to combine stem cell therapy with other ways, such as tissue engineering, gene therapy, exosome therapy, to cure cardiovascular diseases, aiming at finding better ways to treat the cardiovascular disease. This article is mainly for the reviewing of the mechanisms underlying the stem cell therapy and the combinatory use of new technology emerged these years.
Circular RNA (circRNA) is a non-coding RNA which exists widely in eukaryotic cells with a structure of covalently closed continuous loop. Its generation, characteristics and functions have received extensive attention, making it one of the hot spots in the field of non-coding RNA research. Many studies have found that circRNA plays an important role in the development of various diseases including cardiovascular disease, nervous system disease and cancer. Cardiovascular disease is a worldwide common disease with high incidence and poor prognosis. Its exact pathogenesis has not been found, which blocks the development of cardiovascular disease treatment. In this review, we summarize the loop-forming mechanisms, the functions and the progress of current researches of circRNA in cardiovascular diseases.
Williams syndrome is a congenital multisystem disease. Cardiovascular abnormality caused by elastin deficiency is the main cause of morbidity and mortality in Williams syndrome patients. Recent studies have found that 80% of Williams syndrome patients have cardiovascular abnormalities, most of which are arterial stenosis, especially the aortic valve stenosis and pulmonary artery stenosis. Operation is the main method to treat the stenosis of the artery, and the results of the operation on the aortic valve stenosis in most centers are good, but the effect of transcatheter intervention is still not obvious, pulmonary artery reconstruction has a good effect on the treatment of peripheral pulmonary artery stenosis. Advances in genetic diagnosis, surgical techniques and treatment regimens are expected to significantly improve cardiovascular outcomes in these patients. This article reviews the latest research progress of Williams syndrome combined with cardiovascular disease.
There are various examination methods for cardiovascular diseases. Non-invasive diagnosis and prognostic information acquisition are the current research hotspots of related imaging examinations. Positron emission tomography (PET)/magnetic resonance imaging (MRI) is a new advanced fusion imaging technology that combines the molecular imaging of PET with the soft tissue contrast function of MRI to achieve their complementary advantages. This article briefly introduces several major aspects of cardiac PET/MRI in the diagnosis of cardiovascular disease, including atherosclerosis, ischemic cardiomyopathy, nodular heart disease, and myocardial amyloidosis, in order to promote cardiac PET/MRI to be more widely used in precision medicine in this field.
With the heavier burden of cardiovascular disease, an abundance of papers emerge every year in the research hotspots, which cover a wide range of types and content. In order to let readers interested in the cardiovascular field quickly understand the research hotspots and research frontier, it is necessary to sort out and summarize the research topic in time. According to the discipline classification, we screened papers in cardiovascular field from the Essential Science Indicators (ESI) hot papers published in 2019. Methods such as bibliometrics, statistical description, hierarchical induction, analysis and interpretation were used a step further to reveal the context and characteristics of research in the field of cardiovascular diseases, summarize the latest progress and development direction in this field, and provide information and hints for the expansion of future research directions. A total of 297 papers were finally included, which were mainly in the field of clinical medicine; The country with the most publications was the United States, while China ranked the fifth in terms of contribution; the research institution with the highest number of published papers was Harvard University; the New England Journal of Medicine (NEJM) has published the most papers, with contribution also from journals such as Circulation, Europe Heart Journal, JAMA, and Lancet. All the papers were categorized into disease burden, disease risk, drug treatment, device treatment and surgical treatment, clinical diagnosis, basic research and others, so as to review and summarize the research front in the field of cardiovascular diseases.
The peak period of cardiovascular disease (CVD) is around the time of awakening in the morning, which may be related to the surge of sympathetic activity at the end of nocturnal sleep. This paper chose 140 participants as study object, 70 of which had occurred CVD events while the rest hadn’t during a two-year follow-up period. A two-layer model was proposed to investigate whether hypnopompic heart rate variability (HRV) was informative to distinguish these two types of participants. In the proposed model, the extreme gradient boosting algorithm (XGBoost) was used to construct a classifier in the first layer. By evaluating the feature importance of the classifier, those features with larger importance were fed into the second layer to construct the final classifier. Three machine learning algorithms, i.e., XGBoost, random forest and support vector machine were employed and compared in the second layer to find out which one can achieve the highest performance. The results showed that, with the analysis of hypnopompic HRV, the XGBoost+XGBoost model achieved the best performance with an accuracy of 84.3%. Compared with conventional time-domain and frequency-domain features, those features derived from nonlinear dynamic analysis were more important to the model. Especially, modified permutation entropy at scale 1 and sample entropy at scale 3 were relatively important. This study might have significance for the prevention and diagnosis of CVD, as well as for the design of CVD-risk assessment system.
Cardiovascular diseases are the leading cause of death and their diagnosis and treatment rely heavily on the variety of clinical data. With the advent of the era of medical big data, artificial intelligence (AI) has been widely applied in many aspects such as imaging, diagnosis and prognosis prediction in cardiovascular medicine, providing a new method for accurate diagnosis and treatment. This paper reviews the application of AI in cardiovascular medicine.