Cardiovascular diseases is the leading cause of threat to human life and health worldwide. Early risk assessment, timely diagnosis, and prognosis evaluation are critical to the treatment of cardiovascular diseases. Currently, the evaluation of diagnosis and prognosis of cardiovascular diseases mainly relies on imaging examinations such as coronary CT and coronary angiography, which are expensive, time-consuming, partly invasive, and require high professional competence of the operator, making it difficult to promote in the community or in areas where medical resources are scarce. The fundus microcirculation is a part of the human microcirculation and has similar embryological origins and physiopathological features to cardiovascular circulation. Several studies have revealed fundus imaging biomarkers associated with cardiovascular diseases, and developed and validated intelligent diagnosis and treatment models for cardiovascular diseases based on fundus imaging data. Fundus imaging is expected to be an important adjunct to cardiovascular disease diagnosis and treatment given its noninvasive and convenient nature. The purpose of this review is to summarize the current research status, challenges, and future prospects of the application of artificial intelligence based on multimodal fundus imaging data in cardiovascular disease diagnosis and treatment.
ObjectivesTo systematically review the efficacy of Nordic walking on prognosis of cardiovascular diseases. MethodsPubMed, Web of Science, EMbase, The Cochrane Library, CBM, CNKI and VIP databases were electronically searched to collect intervention studies on the efficacy of Nordic walking on prognosis of cardiovascular diseases from inception to June, 2018. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, then, meta-analysis was performed by RevMan 5.3 software. ResultsA total of 9 studies involving 328 patients were included. The results of meta-analysis showed that: compared with control group, there were an obvious decrease in the values of LDL (MD=–11.38, 95%CI –17.51 to –5.25, P=0.000 3), TG (MD=–21.14, 95%CI –32.33 to–9.96, P=0.000 2), SBP (MD=–7.96, 95%CI ?11.45 to –4.46, P<0.000 01) and TC, DBP, BMI (P<0.05). However, there were no obvious differences between two groups in HDL. ConclusionsNordic walking can improve the prognosis of patients with cardiovascular diseases, yet the long-term effect is unclear. Due to limited quality and quantity of the included studies, more higher quality studies are required to verify above conclusions.
Abstract: The amniotic fluidderived stem cells (AFSC) possess considerable advantageous characteristics including high proliferation potential, easy availability, low immunogenicity and oncogenicity，and accordance with medical ethnics. Moreover, they do not require the sacrifice of human embryos for their isolation and the cells can differentiate into all three kinds of germs. Accordingly，they initiate a new and very promising field in stem cell research and they will be a potential source of stem cells for therapies related to regeneration medicine of cardiovascular diseases. The research about the AFSC utilization in cardiovascular diseases is just started. Though there were some exciting breakthroughs, there still remain many challenges. In the article，we will discuss AFSC characteristics, influence of amniotic fluid harvesting time on stem cells, isolation and purification, emphasizing mainly on the potential of AFSC differentiation into cardiovascular cells, current situation and problems in this field.
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.
ObjectiveTo systematically evaluate the efficacy and safety of Polypill on cardiovascular risk factors. MethodSuch databases as Embase, Cochrane Library, PubMed, Web of Science, China National Knowledge Infrastracture, WanFang, and China Biology Medicine Disc were searched from their establishment to May 2015 for randomized controlled trials on the efficacy and safety of Polypillon on cardiovascular risk factors. Meta-analyses were performed by using the RevMan 5.2 software. ResultsSix studies were included which all came from overseas including 1 155 patients treated with Polypill and 1 149 treated with placebo or single or combined medicaiton. The meta-analysis showed that:when compared with the controls, Polypills could significantly reduce systolic blood pressure[WMD=-9.39 mm Hg (1 mm Hg=0.133 kPa), 95%CI (-14.44, -4.33) mm Hg, P=0.0003], diastolic blood pressure[WMD=-5.32 mm Hg, 95%CI (-8.10, -2.55) mm Hg, P=0.0002], total cholesterol[WMD=-1.11 mmol/L, 95%CI (-1.48, -0.74) mmol/L, P<0.00001], and low density lipoprotein[WMD=-0.91 mmol/L, 95%CI (-1.25, -0.57) mmol/L, P<0.00001]. However, those who took Polypill were easier to discontinue medication [OR=1.49, 95%CI (1.19, 1.87), P=0.0005]. In the respect of adverse effects, there was no significant difference between the two groups[OR=1.47, 95%CI (0.67, 3.25), P=0.34]. ConclusionsThe efficacy of Polypill on cardiovascular risk factors is obvious. Polypills can significantly reduce blood pressure and lipids. Tolerability is lower in those taking Polypills, but the difference is minor. There is no significant difference in the respect of adverse effects.
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.
With the development of science and technology, artificial intelligence is gradually integrated into every aspect of daily life and the medical field is no exception. Cardiovascular diseases, as the first killer to global health, is the focus of new technologies and methods. In this study, the application of computer vision, natural language processing, robotics and machine learning in cardiovascular disease studies were reviewed and prospected, in order to promote the development for new technologies and applications in the future.
Cardiovascular disease has caused a huge burden of disease worldwide, and the rapid advancement of smart wearable devices has provided new means for early diagnosis, real-time monitoring, and event prevention of cardiovascular disease. Smart wearable devices can be classified into various categories based on detection signals and physical carrier types. Based on an overview of the composition of such devices, this article further introduces the current cutting-edge research and related market products related to smart blood pressure monitoring, electrocardiogram monitoring, and ultrasound monitoring. It also discusses the future development and challenges of such devices, aiming to provide evidence support for the research and development of smart wearable devices in the diagnosis and treatment of cardiovascular diseases in the future.