Article 6 (source: IEEE journal of translational engineering in health and medicine. 2018；6:190050)Silent Myocardial Ischemia (SMI) is an issue of public health that leads to heartattack and significanty influences the mortality rate in patients with type 2 diabetes.SMI is myocardial ischemia without   chest discomfort and other angina symptoms. Theincidence rate of SMI in diabetic patients was 2.2 times higher than the incidence rateof SMI in nondiabetic patients. SMI had been investigated and confirmed with a 6%-23% prevalenco in diabetic patients using Myocardial Perfusion Imaging (MP) andinvasive coronary angiography. SMI can lead to acute myocardial infarction, adversecardiac events, and poor prognosis outcomes, that are severe in diabetic care. Therefore,it is quite important to have an early predictor of SMI that can feasibly screen diabeticpatients and give a risk stratification of heart ischemia and may prevent many diabeticpatients from sudden cardiac death or adverse cardiovascular events. Holter devices,the ambulatory clectrocardiography (ECG), has proven to be a useful tool to detectpatients at high risk of SMI. However, Holter devices need to monitor the patients overthe course of 24 hours or even up to 72 hours to detect abnormal clectrical signals fromthe electrocardiogram. This long-term measurement makes the Holter less effective forscreening the whole population of high cardiovascular risk group such as diabeticgroups. Besides the ambulatory ECG, low ankle-brachial index (ABI) andmicroalbuminuria, the albumin-tocreatinine ratio (ACR) between 30mg/g to 300mg/g,have also been investigated in the detecti tion of SMI. Another potential method ofdetecting SMI is using arterial pulse spectru um analysis. The spectrum of arterial pulsewave reflects the loading condition of the arterial system, which has been investigated,modeled, applied, and interpreted in many clinical studies. According to Lin's model,radial pulse spectrum analysis can reveal the arterial-ventricular function by itsharmonics change. Chen et al. validated this concept and proved that the specificcharacteristic of radial pulse spectrum changed from the resting state to the onset ofacute, uncomplicated myocardial infarction state, and gradually shifted to other restingcharacteristics a week after surgery. Furthermore, the cross-sectional study showed thatthe harmonics of the radial pulse spectrum were correlated with the ischemic heartdisease. To summarize results from those studies, the ventricular-arterial couplingsystem distributed the pressure pulse wave to different organs in proportions ofharmonics according to the system state. Therefore, the pattern of harmoniccomponents could reveal the blood flow condition of organs, and more specifically,reveal the condition of myocardial perfusion. However, there is still a lack of directstatistic evidence quantifying the correlation between harmonics of the radial pulsewave and myocardial perfusion, and validating whether the harmonics of the pulsespectrum contains the information in identifying SMI. Hence, the objective of this studywas to statistically validate the degree of confidence that the harmonics of radial pulsespectrum and myocardial perfusion were correlated, using receiver operatingcharacteristic curve (ROC) and multivariable linear regression. This report chose type2 diabetic patients because of their high-risk prevalence for SMI. We included thepatients without any angina pectoris history, at high risk of SMI, and suitable forperforming MPI. We further investigated the relationship between SMI and differentrisk factors. In the end, this report analyzed the different risk factor profiles to proposean effective and efficient method for early SMI diagnosis.
【題組】41. What is the clinical syndrome of SMI?
(A) pain
(B) chest discomfort
(C) no specificfeelings
(D) vomiting