Objective To evaluate the efficacy of n-3 PUFAs (fish oil) for prevention of cardiovascular events. Methods Randomized controlled trials (RCTs) were searched from the following electronic databases: PubMed, EMbase, The Cochrane Library (Issue 1, 2009), CBM, and CNKI. Quality assessment and data extraction were conducted by two reviewers independently. Disagreement was resolved through discussion. All data were analyzed by using Review Manager 4.2 software. Results Five studies involving 37 689 participants met the inclusion criteria. Meta-analysis results showed that: 1) Compared with placebo, the incidence rates of the cardiovascular death (RR=0.91, 95% CI 0.84 to 0.98), cardiovascular events (RR=0.95, 95%CI 0.91 to 0.98), angina (RR=0.79, 95%CI 0.64 to 0.96), and myocardial infarction (RR=0.79, 95%CI 0.65 to 0.96) could be reduced by n-3 PUFAs (fish oil). 2) There were no significant differences in death from any cause, the hospitalization rates of cardiovascular disease, sudden death, and heart failure (RR=0.95, 95%CI 0.90 to 1.00; RR=0.97, 95%CI 0.93 to 1.02; RR=0.90, 95%CI 0.79 to 1.01; RR=0.98, 95%CI 0.91 to 1.06). 3) Compared with placebo, the incidence rates of the arrhythmia and stroke could be increased, but there were no significant differences (RR=1.14, 95%CI: 0.80 to 1.62; RR=1.12, 95%CI 0.97 to 1.30). Conclusion Compared with placebo, n-3 PUFAs (fish oil) has good effects on reducing the incidence rates of total cardiovascular events, cardiovascular death, myocardial infarction, and angina pectoris, and it has the same efficacy in death from all cause, sudden death, heart failure, and the hospitalization rates of cardiovascular disease. There are no significant differences in the increased rates of arrhythmia and stroke.
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.
The main cause of death in patients with end-stage renal disease (ESRD) is cardiovascular disease, and trimethylamine-N-oxide (TMAO) has been found to be one of the specific risk factors in the pathogenic process in recent years. TMAO is derived from intestinal bacterial metabolism of dietary choline, carnitine and other substances and subsequently catalyzed by flavin monooxygenase enzymes in the liver. The changes of intestinal bacteria in ESRD patients have contributed to the accumulation of gut-derived uremic toxins such as TMAO, indoxyl sulfate and indole-3-acetic acid. While elevated TMAO concentration accelerates atherosclerosis through mechanisms such as inflammation, increased scavenger receptor expression, and inhibition of reverse cholesterol transport. In this review, this research introduces the biological function, metabolic processes of TMAO and mechanisms by which TMAO promotes the progression of cardiovascular disease in ESRD patients and summarizes current interventions that may be used to reverse gut microbiota disturbances, such as activated carbon, fecal microbial transplantation, dietary improvement, probiotic and probiotic introduction. It also focuses on exploring intervention targets to reduce the gut-derived uremic toxin TMAO in order to explore the possibility of more cardiovascular disease treatments for ESRD patients.
Cardiovascular disease (CVD) is one of the leading causes of death worldwide. Heart sound classification plays a key role in the early detection of CVD. The difference between normal and abnormal heart sounds is not obvious. In this paper, in order to improve the accuracy of the heart sound classification model, we propose a heart sound feature extraction method based on bispectral analysis and combine it with convolutional neural network (CNN) to classify heart sounds. The model can effectively suppress Gaussian noise by using bispectral analysis and can effectively extract the features of heart sound signals without relying on the accurate segmentation of heart sound signals. At the same time, the model combines with the strong classification performance of convolutional neural network and finally achieves the accurate classification of heart sound. According to the experimental results, the proposed algorithm achieves 0.910, 0.884 and 0.940 in terms of accuracy, sensitivity and specificity under the same data and experimental conditions, respectively. Compared with other heart sound classification algorithms, the proposed algorithm shows a significant improvement and strong robustness and generalization ability, so it is expected to be applied to the auxiliary detection of congenital heart disease.
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.
目的探讨低压辅助悬吊式腹腔镜在合并心血管疾病患者行腹腔镜胆囊切除术(LC)中的应用价值和安全性。 方法回顾性分析2007年1月至2010年10月期间,通渭县中医院普外科以及甘肃省人民医院普外科收治的132例合并心血管疾病的急、慢性胆囊炎或胆囊结石患者的临床资料。 结果132例患者均进行了低压辅助悬吊式LC,手术均顺利完成,成功率为100%,无中转开腹,患者术中、术后生命体征正常。 结论低压辅助悬吊式腹腔镜技术在合并心血管疾病患者中是安全、可行的。
ObjectiveTo investigate the prevalence of hypertension and to find the cardiovascular risk factors in the urban residents of Chengdu city. MethodsBy cluster sampling, a population of 994 inhabitants were selected from 14 urban communities in Chengdu city between February and October 2010. They were 35-70 years old and had resided in the area for over 2 years. Hypertension questionnaire was used and physical examinations were taken to investigate. The definition of hypertension was determined by the Guidelines of Hypertension Prevention and Control made by National Revision Committee in 2010. Logistic regression model was used to define the risk factors for hypertension. ResultsThe prevalence rate of hypertension was 44.87%, and the standardized prevalence rate was 39.21% (male:41.07%, female:38.20%). The difference of prevalence rate between males and females was not significant (P>0.05). The prevalence rate of hypertension increased significantly with age. By multi-factor logistic regression analysis, age (OR=1.103, P<0.001), serum uric acid (OR=1.003, P=0.001), heart rate (OR=1.014, P=0.027), and waist circumference (OR=1.624, P<0.001) were the risk factors for hypertension. ConclusionThe prevalence rate of hypertension is high in urban communities of Chengdu city, and age, serum uric acid, heart rate, and waist circumference are the risk factors for hypertension.
ObjectivesTo systematically review the safety and efficacy of aspirin in primary prevention of cardiovascular diseases.MethodsPubMed, EMbase, Web of Science, The Cochrane Library, CBM, WanFang Data, CNKI and VIP databases were electronically searched to collect randomized controlled trials (RCTs) of aspirin for primary prevention of cardiovascular diseases from inception to November 2018. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, and then, meta-analysis was performed by RevMan 5.3 software.ResultsA total of 13 RCTs involving 164 225 participants were included. The results of meta-analysis showed that: aspirin reduced the risk of myocardial infarction (RR=0.85, 95%CI 0.75 to 0.97, P=0.01), ischemic stroke (RR=0.86, 95%CI 0.79 to 0.95, P=0.002) and risk of major adverse cardiovascular events (RR=0.90, 95%CI 0.86 to 0.94, P<0.000 1). However, all-cause mortality (RR=0.97, 95%CI 0.93 to 1.02, P=0.22) and cardiovascular mortality (RR=0.93, 95%CI 0.85 to 1.02, P=0.11) were not reduced. Additionally, it increased risk of hemorrhagic stroke (RR=1.29, 95%CI 1.02 to 1.64, P=0.03), major bleeding (RR=1.43, 95%CI 1.31 to 1.56, P<0.000 01) and gastrointestinal bleeding (RR=1.59, 95%CI 1.33 to 1.90, P<0.000 01).ConclusionCurrent evidence shows that aspirin can reduce the incidence of major adverse cardiovascular events and myocardial infarction during primary prevention of cardiovascular disease, while increase the risk of bleeding, especially gastrointestinal bleeding. Therefore, its potential benefits may be offset. Due to limited quality and quantity of the included studies, more high-quality studies are required to verify the above conclusion.
Objective To explore the relationship between uric acid (UA) level and cardiovascular disease in patients with OSAHS and its clinical significance. Methods The electronic medical record system of the First hospital of Lanzhou University was used to collect 475 subjects who completed polysomnography (PSG) during hospitalization from January 2019 to May 2020. According to the Guidelines for the Diagnosis and Treatment of Obstructive Sleep Apnea Hypopnea Syndrome (Basic Version), the patients were divided into four group: control group [apnea-hypopnea index (AHI) <5 times/h, n=96], mild group (5≤AHI≤15 times/h, n=130), moderate group (15<AHI≤30 times/h, n=112), and severe group (AHI>30 times/h, n=137). The age, gender, body mass index (BMI), smoking history, drinking history, hypertension, diabetes mellitus, cardiovascular disease and biochemical indexes [including triglyceride, total cholesterol, high density lipoprotein cholesterol, low density lipoprotein cholesterol, glucose, UA, blood urea nitrogen (BUN), serum creatinine, lactate dehydrogenase, homocysteine], PSG indexes were observed and compared among the four groups, and the differences were compared by appropriate statistical methods. Binary logistic regression model was used to evaluate the correlation between various risk factors and cardiovascular disease. Results There were statistically significant differences in age, gender, BMI, drinking history, hypertension and cardiovascular disease among the 4 groups (P<0.05). The levels of UA and BUN in mild, moderate and severe groups were higher than those in the control group, with statistical significance (P<0.05). With the increasing of OSAHS severity, the level of UA increased. There was statistical significance in the incidence of cardiovascular disease among the four groups (P<0.05), and the highest incidence of arrhythmia was found among the four groups. And the incidence of cardiovascular disease increases with the increasing of OSAHS severity. Binary Logistic regression analysis showed that the risk factors for cardiovascular disease in OSAHS patients were age, UA and BUN (P<0.05). Conclusions The occurrence of cardiovascular disease in OSAHS patients is positively correlated with the severity of OSAHS. The level of UA can be used as an independent risk factor for cardiovascular disease in OSAHS patients. Therefore, reducing the level of UA may have positive significance for the prevention and control of the prevalence and mortality of cardiovascular disease in OSAHS patients.