Cardiovascular risk assessment is a basic tenet of the prevention of cardiovascular disease. Conventional risk assessment models require measurements of blood pressure, blood lipids, and other health-related information prior to assessment of risk via regression models. Compared with traditional approaches, fundus photograph-based cardiovascular risk assessment using artificial intelligence (AI) technology is novel, and has the advantages of immediacy, non-invasiveness, easy performance, and low cost. The Health Risk Assessment and Control Committee of the Chinese Preventive Medicine Association, in collaboration with the Chinese Society of Cardiology and the Society of Health Examination, invited multi-disciplinary experts to form a panel to develop the present consensus, which includes relevant theories, progress in research, and requirements for AI model development, as well as applicable scenarios, applicable subjects, assessment processes, and other issues associated with applying AI technology to assess cardiovascular risk based on fundus photographs. A consensus was reached after multiple careful discussions on the relevant research, and the needs of the health management industry in China and abroad, in order to guide the development and promotion of this new technology.
Humans ; Cardiovascular Diseases/prevention & control* ; Artificial Intelligence ; Consensus ; Risk Factors ; Heart Disease Risk Factors

Humans ; Cardiovascular System ; Cardiovascular Diseases ; Heart

Humans ; Cardiovascular System ; Cardiovascular Diseases ; Heart

Humans ; Cardiovascular Diseases ; Risk Factors ; Myocardial Infarction/complications* ; Coronary Disease/etiology* ; Heart Disease Risk Factors

Humans ; Cardiovascular Diseases/chemically induced* ; East Asian People ; Risk Factors ; Heart Disease Risk Factors ; Lipids ; Anticholesteremic Agents/adverse effects* ; Hydroxymethylglutaryl-CoA Reductase Inhibitors ; Treatment Outcome

Arrhythmia is an external manifestation of cardiac electrophysiological disorder. It exists in healthy people and patients with various heart diseases, which is often associated with other cardiovascular diseases. The contraction and diastole of myocardium are inseparable from the movement of ions. There are many ion channels in the membrane and organelle membrane of myocardium. The dynamic balance of myocardial ions is vital in maintaining myocardial electrical homeostasis. Potassium ion channels that have a complex variety and a wide distribution are involved in the whole process of resting potential and action potential of cardiomyocytes. Potassium ion channels play a vital role in maintaining normal electrophysiological activity of myocardium and is one of the pathogenesis of arrhythmia. Traditional Chinese medicine(TCM)has unique advantages in treating arrhythmia for its complex active components and diverse targets. A large number of TCM preparations have definite effect on treating arrhythmia-related diseases, whose antiarrhythmic mechanism may be related to the effect on potassium channel. This article mainly reviewed the relevant studies on the active components in TCM acting on different potassium channels to provide references for clinical drug use and development.
Humans ; Potassium Channels ; Medicine, Chinese Traditional ; Anti-Arrhythmia Agents/therapeutic use* ; Arrhythmias, Cardiac/drug therapy* ; Heart Diseases/drug therapy* ; Ions

OBJECTIVE: To explore the genetic basis for a fetus with Cardiac-urogenital syndrome (CUGS). METHODS: A fetus with congenital heart disease identified at the Maternal Fetal Medical Center for Fetal Heart Disease, Beijing Anzhen Hospital Affiliated to Capital Medical University in January 2019 was selected as the study subject. Clinical data of the fetus was collected. Copy number variation sequencing (CNV-seq) and trio-whole exome sequencing (trio-WES) were carried out for the fetus and its parents. Candidate variants were verified by Sanger sequencing. RESULTS: Detailed fetal echocardiographic examination had revealed hypoplastic aortic arch. The results of trio-WES revealed that the fetus has harbored a de novo splice variant of the MYRF gene (c.1792-2A>C), for which both parents were of the wild-type. Sanger sequencing confirmed the variant to be de novo. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was rated as likely pathogenic. CNV-seq has identified no chromosomal anomalies. And the fetus was diagnosed with Cardiac-urogenital syndrome. CONCLUSION The de novo splice variant of the MYRF gene probably underlay the abnormal phenotype in the fetus. Above finding has enriched the spectrum of MYRF gene variants.
Female ; Humans ; DNA Copy Number Variations ; Fetal Diseases ; Fetus/abnormalities* ; Heart Defects, Congenital/genetics* ; Mutation ; Transcription Factors/genetics*

Heart failure (HF) has become a major challenge in the treatment of global cardiovascular diseases. Great progress has been made in the drug treatment of HF, however, rehospitalization rate and mortality of patients with HF are still high. Hence, there is an urgent need to explore new treatment strategy and new underlying pathogenic mechanisms. In recent years, some researchers have suggested that regulation of ketone body metabolism may become a potentially promising therapeutic approach for HF. Some studies showed that the oxidative utilization of fatty acids and glucose was decreased in the failing heart, accompanied by the increase of ketone body oxidative metabolism. The enhancement of ketone body metabolism in HF is a compensatory change during HF. The failing heart preferentially uses ketone body oxidation to provide energy, which helps to improve the body's cardiac function. This review will discuss the potential significance of ketone body metabolism in the treatment of HF from three aspects: normal myocardial ketone body metabolism, the change of ketone body metabolism in HF, the effect of ketogenic therapy on HF and its treatment.
Humans ; Heart Failure/metabolism* ; Myocardium/metabolism* ; Ketone Bodies/metabolism* ; Cardiovascular Diseases ; Fatty Acids/metabolism* ; Energy Metabolism

Objective: To recognize the potential factors that contribute to the eradication of migraine headache in patients with patent foramen ovale (PFO) at one year after percutaneous closure. Methods: A prospective cohort study was conducted, which enrolled patients diagnosed with migraines and PFO at the Department of Structural Heart Disease, First Affiliated Hospital of Xi'an Jiaotong University between May 2016 and May 2018. The patients were segregated into two groups based on their response to treatment, and one group showed elimination of migraines while another did not. Elimination of migraines was defined as a Migraine Disability Assessment Score (MIDAS) score of 0 at one year postoperatively. Least Absolute Shrinkage and Selection Operator (LASSO) regression model was utilized to identify the predictive variables for migraine elimination post-PFO closure. Multiple logistic regression analysis was employed to determine the independent predictive factors. Results: The study enrolled a total of 247 patients, with an average age of (37.5±13.6) years, comprising 81 male individuals (32.8%). One year after closure, 148 patients (59.9%) reported eradication of their migraines. Multivariate logistic regression analysis revealed that migraine with or without aura (OR=0.003 9, 95%CI 0.000 2-0.058 7, P=0.000 18), a history of antiplatelet medication use (OR=0.088 2, 95%CI 0.013 7-0.319 3, P=0.001 48) and resting right-to-left shunt (RLS) (OR=6.883 6, 95%CI 3.769 2-13.548 0, P<0.001) were identified as independent predictive factors for elimination of migraine. Conclusion: Migraine with or without aura, a history of antiplatelet medication use, and resting RLS are the independent prognostic factors associated with elimination of migraine. These results provide important clues for clinicians to choose the optimal treatment plan for PFO patients. However, further studies are needed to confirm these findings.
Humans ; Male ; Young Adult ; Adult ; Middle Aged ; Foramen Ovale, Patent/surgery* ; Prospective Studies ; Heart Diseases ; Hospitals ; Migraine Disorders/surgery*

Objective: To investigate the diagnostic efficiency and clinical application value of an artificial intelligence-assisted diagnosis model based on a three-dimensional convolutional neural network (3D CNN) on echocardiographic videos of patients with hypertensive heart disease, chronic renal failure (CRF) and hypothyroidism with cardiac involvement. Methods: This study is a retrospective study. The patients with hypertensive heart disease, CRF and hypothyroidism with cardiac involvement, who admitted in Henan Provincial People's Hospital from April 2019 to October 2021, were enrolled. Patients were divided into hypertension group, CRF group, and hypothyroidism group. Additionally, a simple random sampling method was used to select control healthy individuals, who underwent physical examination at the same period. The echocardiographic video data of enrolled participants were analyzed. The video data in each group was divided into a training set and an independent testing set in a ratio of 5 to 1. The temporal and spatial characteristics of videos were extracted using an inflated 3D convolutional network (I3D). The artificial intelligence assisted diagnosis model was trained and tested. There was no case overlapped between the training and validation sets. A model was established according to cases or videos based on video data from 3 different views (single apical four chamber (A4C) view, single parasternal left ventricular long-axis (PLAX) view and all views). The statistical analysis of diagnostic performance was completed to calculate sensitivity, specificity and area under the ROC curve (AUC). The time required for the artificial intelligence and ultrasound physicians to process cases was compared. Results: A total of 730 subjects aged (41.9±12.7) years were enrolled, including 362 males (49.6%), and 17 703 videos were collected. There were 212 cases in the hypertensive group, 210 cases in the CRF group, 105 cases in the hypothyroidism group, and 203 cases in the normal control group. The diagnostic performance of the model predicted by cases based on single PLAX view and all views data was excellent: (1) in the hypertensive group, the sensitivity, specificity and AUC of models based on all views data were 97%, 89% and 0.93, respectively, while those of models based on a single PLAX view were 94%, 95%, and 0.94, respectively; (2) in the CRF group, the sensitivity, specificity and AUC of models based on all views data were 97%, 95% and 0.96, respectively, while those of models based on a single PLAX view were 97%, 89%, and 0.93, respectively; (3) in the hypothyroidism group, the sensitivity, specificity and AUC of models based on all views data were 64%, 100% and 0.82, respectively, while those of models based on a single PLAX view were 82%, 89%, and 0.86, respectively. The time required for the 3D CNN model to measure and analyze the echocardiographic videos of each subject was significantly shorter than that for the ultrasound physicians ((23.96±6.65)s vs. (958.25±266.17)s, P<0.001). Conclusions: The artificial intelligence assisted diagnosis model based on 3D CNN can extract the dynamic temporal and spatial characteristics of echocardiographic videos jointly, and quickly and efficiently identify hypertensive heart disease and cardiac changes caused by CRF and hypothyroidism.
Male ; Humans ; Artificial Intelligence ; Retrospective Studies ; Echocardiography/methods* ; Heart Diseases ; Hypertension ; Hypothyroidism