1 Introduction
Coronary artery disease, a severe macrovascular complication among patients with type 2 diabetes (T2D), is often asymptomatic in patients with diabetes until the onset of myocardial infarction or sudden cardiac death.[1] [2]
Silent myocardial ischemia in asymptomatic patients with type 2 diabetes can be detected by stress myocardial perfusion imaging (MPI) using single-photo emission computes tomography (SPECT ). It is still under debate which patients with T2D should be tested for SMI. The American Diabetes Association (ADA) suggested that T2D patients with two or more risk factors including hyperlipidemia, hypertension, active smoking, and albuminuria were recommended to screen for SMI.[3]
This investigation is the first to explore the risk factors of SMI detected by using SPECT in Chinese asymptomatic T2D patients.
2 Methods
2.1 Subjects
The patients were recruited from the Department of Diabetology of Tongren hospital (Beijing, China) between June 2014 and July 2016. Eligibility criteria including type 2 diabetes who were screened with stress myocardial perfusion imaging using SPECT . Exclusion criteria were as follows:
1. history of known coronary artery disease, congenital heart disease or known cardiomyopathy, or any clinical indication for stress testing;
2. limited life expectancy or end-stage renal or liver disease.
All of the participants’ medical histories were obtained and the patients received a physical examination, including age, sex, duration, smoking habit, blood pressure, body mass index (BMI), ECG. Meanwhile, they underwent blood and urine laboratory testing.
2.2 Screening for SMI and stress myocardial perfusion imaging
All of the patients were systematically screened with stress myocardial perfusion imaging using SPECT to evaluate the myocardial ischemia. For stress SPECT , adenosine (Adenoscan, Astellas Pharma US, Inc., Deerfield, IL) was infused over 6 minutes at 140 μg/kg/min and Tc-99m sestamibi was injected at 3.05 ± 0.4 minutes of adenosine infusion, and stress images were acquired within 15 to 60 minutes. SMI was defined as detection of perfusion abnormalities by stress MPI using SPECT .[4] SPECT in type 2 diabetic subject were observed in Figure 1 .
Figure 1: Images corresponding to myocardial perfusion SPECT obtained in SMI and non-SMI subjects. (A) Normal SPECT in a representative patient with type 2 diabetes. (B) Reversible defect in the left ventricular apical third of the anterior, septal and lateral region in a representative patient with type 2 diabetes with SMI. SMI = silent myocardial ischemia, SPECT = single photon emission computed tomography.
2.3 Assessment of DR grading
The presence of DR was diagnosed using digital retinal photographs (2 eyes × 2 fields), taken by using a TRC-NW7SF (Topcon Co. Tokyo, Japan) non mydriatic camera at 45°. These photographs were subsequently examined independently by 2 qualified retinal photography graders in accordance with quality assurance protocols. The severity of DR was graded based on the international clinical diabetic retinopathy and diabetic macular edema disease severity scale.[5]
1. no retinopathic changes;
2. mild non-proliferative retinopathy (NPDR);
3. moderate NPDR;
4. severe NPDR; and
5. proliferative retinopathy (PDR).
The degree of diabetic retinopathy was determined according to the grading in the worse eye.
2.4 Ethical statement
The study was conducted with the approval from the Ethics Committee of Beijing Tongren Hospital, Capital Medical University, and adhered to the Declaration of Helsinki . Written informed consent was obtained from each participant.
2.5 Statistical analysis
Continuous variables with normal distribution were presented as mean ± standard derivation (SD). If continuous variables had a skewed distribution, the median and interquartile range of the variable was used. Normally distributed data were analyzed by t test, while nonnormally distributed data were compared using the rank-sum test. Categorical data were compared by the χ2 test. Multivariate analysis was performed using the logistic regression method. Statistical analysis was performed using SPSS 17.0 (SPSS Inc, Chicago, IL). All of the statistical tests were 2-sided and considered statistically significant if P < .05.
3 Results
3.1 Patient characteristics and laboratory analysis
In this hospital-based cross-sectional study, of the 821 eligible participates, 207 participants were excluded because of meeting exclusion criteria. A final total of 614 participants were included in this research (Fig. 2 ).
Figure 2: Selection of patients for study. A total of 821 patients with type 2 diabetes were investigated by using SPECT , and 614 participants were included in the analysis. SPECT = single photon emission computed tomography.
In all of the patients, the average age was 57.0 ± 10.8 years and the duration of diabetes was 10.9 ± 7.6 years. The value of the hemoglobin A1c (HbA1c) was 8.9 ± 2.0%. Besides, the prevalence of DR and albuminuria was 34% (209/614) and 27.5% (165/614).
Then diabetic patients were divided into 2 groups with and without SMI. A total of 131 (21.3%) patients with type 2 diabetes suffered from SMI detected by using SPECT . No significant differences were found in duration of known diabetes, age, blood pressure, smoke history, BMI, total cholesterol (TC), triglyceride (TG), LDL, and HDL cholesterol, except for gender, albuminuria, and stage of DR (Table 1 ). The trend to severe retinopathy and nephropathy in the SMI group was significantly higher than that in the non-SMI group (P < .05).
Table 1: Baseline demographics in the study.
3.2 Risk factors for SMI
Logistic regression analysis was applied, where the variables were selected because they were associated with the presence of SMI with a P value < .10 (male gender, smoke, DR, albuminuria, TC, LDL-c, SBP). It indicated that diabetic retinopathy (OR = 1.474, 95%CI: 1.113–1.951, P = .007), male gender (OR = 1.805, 95%CI: 1.183–2.747, P = .006), and low-density lipoprotein (LDL) cholesterol (OR = 1.298, 95%CI: 1.042–1.615, P = .02) were independent risk factors associated with SMI. The results were shown in Table 2 .
Table 2: Logistic regression analysis of silent myocardial ischemia (SMI) associated factors.
3.3 Prevalence of SMI according to the stage of DR, male
As shown in Fig. 3 , the prevalence of SMI increased in associated with the progression of retinopathy (P = .041). The percentage of SMI diagnosed in patients with no diabetic retinopathy (NDR), non-proliferative diabetic retinopathy (NPDR), and proliferative diabetic retinopathy (PDR) were 18.5% (75/405), 25.2% (37/147), and 30.6% (19/62), respectively. Besides, the percentage of SMI in male (24.5%, 85/347) was higher than that in female (17.2%, 46/267), P = .029.
Figure 3: The prevalence of SMI in the different groups. (A) The prevalence of SMI increased in associated with the progression of retinopathy. The prevalence of SMI diagnosed in NDR, NPDR, and PDR patients were 18.5% (75/405), 25.2% (37/147), and 30.6% (19/62), respectively. (B) The prevalence of SMI diagnosed in male and female patients group were 24.5% (85/347) and 17.2% (46/267). ∗P < .05. NDR = no detectible diabetic retinopathy, NPDR = non-proliferative diabetic retinopathy, PDR = proliferative diabetic retinopathy, SMI = silent myocardial ischemia.
4 Discussions
In this study, we have evaluated the prevalence and risk factors of silent myocardial ischemia detected by using SPECT in Chinese asymptomatic patients with type 2 diabetes. And concluded that Chinese male patients with type 2 diabetes with retinopathy and high levels of LDL-cholesterol are at increased risk of silent myocardial ischemia. Patients of T2DM with SPECT -detected SMI had significantly higher risks of cardiac death, all-cause mortality, nonfatal cardiac events and total cardiac events compared to patients without SMI.[2] [6–8] [9]
Screening for SMI in patients is intuitively attractive as this might potentially lead to benefits. But the utility of screening patients with type 2 diabetes for SMI is controversial. Recently, in the DIAD study[9] [10]
Actually, the risk factors for SMI remained controversial in former studies. The Framingham Heart Study[11,12] [9] [13] SPECT in Chinese asymptomatic type 2 diabetes. In this study, we evaluated the risk factors of SMI in a Chinese T2D population. It indicated that diabetic retinopathy (OR = 1.474, 95%CI: 1.113–1.951, P = .007), male gender (OR = 1.805, 95%CI: 1.183–2.747, P = .006), and low-density lipoprotein (LDL) cholesterol (OR = 1.298, 95%CI: 1.042–1.615, P = .02) were independent risk factors associated with SMI. Meanwhile, maleness and LDL-c were already acknowledged traditional risk factors of SMI. Thus, taking into account retinopathy status might further improve the selection of patients for SMI screening.
Our study suggested that T2D patient with diabetic retinopathy, a typical microvascular complication of diabetes, more likely to suffer from SMI. Diabetic retinopathy has previously been found to be associated with CHD.[7,13–15] [16] [15,17–20] [21]
5 Limitations
To our knowledge there have been no relevant studies evaluating risk factors of SMI diagnosed with SPECT in Chinese T2D patients. However, stratified analysis was not made according to the degree of myocardial ischemia. Besides, this study cannot explain why patients with type 2 diabetes with DR had a high risk of SMI. A large clinical trial with a long follow-up period may provide evidence to support screening of SMI in these patients. Finally, this was a single center study, with the possibility of selection bias. Therefore, further multicenter, prospective studies are warranted to confirm our findings.
6 Conclusion
Within the Chinese population, male patients with type 2 diabetes with DR and high levels of LDL cholesterol are at an increased risk of SMI. A routine screening for SMI may thus be considered advisable in these patients.
Author contributions
JKY and XRZ contributed to the design of the study, analysis, and interpretation of data, and prepared all of the figures and tables. JKY, XRZ, and HRZ, drafted a portion of the manuscript. JBZ, ML, ZZ, WL, and GRY took part in analyzing data and drafting a portion of the manuscript. All of the authors reviewed the manuscript.
Data curation: Zhu Xiao-Rong, Zhang Hui-Rong, Zhou Zhen, Liu Wei, Lu Jing, Yang Guang-Ran.
Formal analysis: Zhu Xiao-Rong, Zhou Zhen.
Funding acquisition: Yang Guang-Ran, Zhou Jian-Bo.
Methodology: Zhu Xiao-Rong, Li Mei, Zhou Jian-Bo.
Project administration: Yang Jin-Kui.
Validation: Zhou Jian-Bo.
Visualization: Zhu Xiao-Rong.
Writing – original draft: Zhu Xiao-Rong.
Writing – review & editing: Zhu Xiao-Rong, Yang Jin-Kui.
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