Investigation on cardiovascular risk prediction using physiological parameters.
Cardiovascular disease (CVD) is the leading cause of death worldwide. Early prediction of CVD is urgently important for timely prevention and treatment. Incorporation or modification of new risk factors that have an additional independent prognostic value of existing prediction models is widely used for improving the performance of the prediction models. This paper is to investigate the physiological parameters that are used as risk factors for the prediction of cardiovascular events, as well as summarizing the current status on the medical devices for physiological tests and discuss the potential implications for promoting CVD prevention and treatment in the future. The results show that measures extracted from blood pressure, electrocardiogram, arterial stiffness, ankle-brachial blood pressure index (ABI), and blood glucose carry valuable information for the prediction of both long-term and near-term cardiovascular risk. However, the predictive values should be further validated by more comprehensive measures. Meanwhile, advancing unobtrusive technologies and wireless communication technologies allow on-site detection of the physiological information remotely in an out-of-hospital setting in real-time. In addition with computer modeling technologies and information fusion. It may allow for personalized, quantitative, and real-time assessment of sudden CVD events.
SIAT-Institute of Biomedical and Health Engineering, Chinese Academy of Sciences, Shenzhen 518055, China ; The CAS Laboratory for Health Informatics, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
Wan-Hua
WH
Lin
SIAT-Institute of Biomedical and Health Engineering, Chinese Academy of Sciences, Shenzhen 518055, China ; The CAS Laboratory for Health Informatics, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China.
Heye
H
Zhang
The CAS Laboratory for Health Informatics, Shenzhen Institutes of Advanced Technology, Shenzhen 518055, China ; Department of Electronic Engineering, Joint Research Centre for Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong.
Yuan-Ting
YT
Zhang
D055109:Ankle Brachial Index; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure / Q000502:physiology; D002318:Cardiovascular Diseases / Q000175:diagnosis*; D004562:Electrocardiography; D006801:Humans; D011237:Predictive Value of Tests; D016016:Proportional Hazards Models; D012307:Risk Factors
D001786:Blood Glucose