Abstract
Objective
Type 1 diabetes (T1DM) is associated with a higher risk of premature death, but there are factors in certain patients with T1DM that protect them from complications and premature death. These factors had not been identified in non-Caucasian populations, so we aimed to identify factors that protect against the development of diabetic nephropathy (DN) and diabetic retinopathy (DR) in long-standing T1DM in China.
Methods
Ninety-five T1DM patients with >30 years’ duration of diabetes were enrolled in this nationwide study. Differences between groups of patients with and without complications were compared, and multivariable regression analysis was used to evaluate the relationships between candidate protective factors and the development of DN or DR.
Results
Thirty of the participants did not have DN and the same amount did not have DR. 6/52 of participants without DN were from a rural area, whereas 11/28 of participants with DN had been born in a rural area (P = 0.005). Systolic blood pressure (SBP) was higher in participants with DN (135 ± 26 mmHg vs 121 ± 13 mmHg; P = 0.002). In participants without DR, 27/30 were married or cohabitating, and only 3/30 were single, never married, or widowed, but for those with proliferative DR (PDR), 13/26 had been married (P = 0.003). A rural or urban origin and SBP were associated with DN in the multivariable analysis.
Conclusion
we have shown that higher socioeconomic status, indicated by birth in an urban area, and being married or cohabitating, are accompanied by better blood pressure control and a lower risk of microvascular complications in Chinese patients with long-standing T1DM. These findings illustrate the importance of improving care for patients with T1DM in China.
Introduction
Chronic complications cause the largest proportion of deaths and increase in prevalence with the duration of the disease in long-standing type 1 diabetes (T1DM). (1) Indeed, the duration of diabetes and severity of hyperglycemia are the conventionally used predictors of diabetic retinopathy (DR) and diabetic nephropathy (DN). (2, 3) Previous studies have shown that almost all T1DM patients are likely to develop some degree of DN within 20 years of diagnosis. (4, 5) In addition, DN affects nearly 30% of T1DM patients and is associated with poor prognosis, being the most common reason for end-stage renal disease (ESRD) to develop in the US. (6) However, a study by Keenan et al. (7) of the Joslin Medalist group of T1DM patients identified individuals with diabetes for ≥50 years who appeared to be protected against DR and DN. Similar results have also been identified in other long-standing T1DM cohorts, such as the Golden Years study in UK and the Canadian study of the longevity of T1DM patients. (8, 9) These findings suggest that individuals with an extremely long duration of T1DM are either protected from or show slower progression of diabetic microvascular complications. This survival bias inherent in studying patients with a long duration of T1DM permits the evaluation of protective factors. However, all these studies of long-standing T1DM have been conducted in Caucasians; there have been no studies to date of the factors associated with DR and DN in equivalent non-Caucasian cohorts.
The prevalence of T1DM in China is extremely low compared with that in some European countries and North America, (10) and little is known about the features of long-term T1DM in patients in China. In the 3C Study of coverage, cost, and care for type 1 diabetes in China, there were only a few participants who had had diabetes for >30 years, (11) implying that few patients can live with the disease for more than 30 years, likely because of an overall deficit in care. Therefore, we aimed to characterize the prevalence of microvascular complications and risk factors associated with long-standing T1DM in China by studying a nationwide cohort of patients who had had diabetes for at least 30 years. (12)
Materials and methods
Study overview
To encourage people with T1DM to manage the disease more effectively, the Chinese Diabetes Society (CDS) pursued a ‘Care for Life, Hand in Hand’ program between December 2012 and December 2013, which aimed to identify people across China who had survived ≥ 30 years with T1DM. The diagnosis was confirmed by clinical endocrinologists, on the basis of hospital medical records. During the 1-year enrollment period, 105 individuals living across China were identified. As an incentive, they were provided with free insulin detemir, insulin aspart, and glucose monitoring strips for 3 years. The study was a cross-sectional, observational study of the participants that enrolled in the program. The Peking University People’s Hospital Institutional Review Board approved the study, and all the participants provided their written informed consent.
Participants
Between December 2015 and December 2016, all of the registered participants were contacted, and 95 of them had completed their study visit. The reasons for non-participation were death (n = 4), moving to the countryside (n = 3), and lack of interest (n = 3). The participants were from 21 provinces (Supplementary Fig. 1, see section on supplementary materials given at the end of this article), of which the most common were Beijing (17.5%), Jiangsu (16.5%), and Shanxi (10.3%).
Clinical and anthropometric assessments
Demographic and socioeconomic data, body mass, height, and blood pressure were assessed by study physicians and researchers. Blood and urine samples were also collected locally and shipped using a biosecure transportation system at −80°C to Peking University People’s Hospital within 24 h.
HbA1c was measured using an automated HPLC system (Primus Ultra 2, Trinity Biotech, Bray, Ireland). Serum lipids, including triglyceride (TG), total cholesterol (TC), high-density lipoprotein-cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) concentrations, were measured using an automated Hitachi-008 system (Hitachi). Urine albumin/creatinine ratio (UACR) was measured using a Roche-c311 system (Roche).
The patients’ renal status was assessed using the mean UACR obtained from two fasting and one post-meal urine samples. Participants without albuminuria (UACR < 30 mg/g) were compared with those with albuminuria (UACR ≥ 30 mg/g). DR was diagnosed by an ophthalmologist, using a slit lamp and an ophthalmoscope, and the severity of DR was classified as (1) no DR; (2) non-proliferative DR (NPDR); or (3) proliferative DR (PDR).
Statistical analysis
The data are expressed as means (s.d,s) for continuous variables, and percentages for categorical variables. Parameters were compared between groups using ANOVA for numeric data and the chi-square test for categorical data. P < 0.05 was considered to represent statistical significance. Multivariable logistic regression analysis was used to determine the odds ratios (ORs) for factors potentially associated with DN and the severity of DR. All parameters with P < 0.10 in the chi-square or ANOVA analyses were included in the multivariable regression model. Statistical analysis was performed using SPSS software (version 23.0, IBM).
Results
DN in patients with long-standing T1DM
Of the 95 participants enrolled in the study, 30 did not have albuminuria and the remainder did. 14 of the 30 with, and 28 of the 60 without DN were male. The age and the age at diagnosis were similar between participants with and without DN (56.0 ± 9.5 years vs 59.4 ± 12.6 years, and 16.3 ± 6.7 years vs 19.2 ± 11.6 years, respectively). The duration of diabetes was also similar between the two groups (39.7 ± 6.9 years vs 39.9 ± 6.1 years).
Of the participants who did not have DN, 6/52 had been born in a rural area, whereas 11/28 of participants with DN had been born in a rural area (P = 0.005). Systolic blood pressure (SBP) was higher in the DN group (135 ± 26 mmHg vs 121 ± 13 mmHg, P = 0.002) and HbA1c was slightly higher in individuals with DN (7.4 ± 1.3% vs 6.9 ± 1.2%), but this difference failed to reach statistical significance (P = 0.075). A comparison of the lipid profiles of the two groups showed no significant differences (P = 0.118, 0.822, 0.079, and 0.130 for TC, HDL-C, LDL-C, and TG, respectively). (Table 1)
Demographic, biochemical and clinical differences between participants with and without DN.
| Without albuminuria (n = 30)a | With albuminuria (n = 60)a | P valueb | |
|---|---|---|---|
| Male, n | 14/30 | 28/60 | 0.588 |
| Mean (s.d,) age, years | 56.0 (9.5) | 59.4 (12.6) | 0.234 |
| Mean (s.d,) age at diagnosis, years | 16.3 (6.7) | 19.2 (11.6) | 0.197 |
| Mean (s.d.) diabetes duration, years | 39.7 (6.9) | 39.9 (6.1) | 0.920 |
| Family resources, na | |||
| Rural area | 11/28 | 6/52 | 0.005 |
| Urban area | 17/28 | 46/52 | |
| Highest level of education, na | 0.359 | ||
| < University | 24/28 | 41/52 | |
| ≥ University | 4/28 | 11/52 | |
| Marital status, na | 0.389 | ||
| Married/cohabitating | 20/28 | 40/52 | |
| Single/never married/widowed | 8/28 | 12/52 | |
| Mean (s.d,) BMI (kg/m2) | 22.3 (2.9) | 22.6 (2.7) | 0.623 |
| Mean (s.d,) SBP, mmHg | 121 (13) | 135 (26) | 0.002 |
| Mean (s.d,) DBP, mmHg | 72 (8) | 74 (13) | 0.317 |
| Mean (s.d,) HbA1c, % | 6.9 (1.2) | 7.4 (1.3) | 0.075 |
| Mean (s.d,) total cholesterol, mmol/L | 4.9 (1.2) | 5.4 (1.3) | 0.118 |
| Mean (s.d,) HDL-C, mmol/L | 1.6 (0.3) | 1.6 (0.4) | 0.822 |
| Mean (s.d,) LDL-C, mmol/L | 2.6 (1.0) | 3.1 (1.1) | 0.079 |
| Mean (s.d,) triglyceride, mmol/L | 1.0 (0.5) | 1.2 (0.5) | 0.130 |
a4 were missing for diabetes nephropathy status; 10 were missing for family resources, highest level of education, and marital status; bP value < 0.05 from chi-squared test and ANOVA test comparing participants with and without DN.
BMI, body mass index; DBP, diastolic blood pressure; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure.
DR in participants with long-standing T1DM
Thirty participants did not have DR, and the number of participants with NPDR and PDR were both 26. Of the participants without DR, or with NPDR or PDR, 15/30, 11/26, and 10/26, respectively, were male (P = 0.673). Participants with NPDR were the oldest (59.7 ± 10.8 years), those with PDR the youngest (52.1 ± 8.5 years), and those without DR intermediate in age (58.2 ± 10.9 years) (P = 0.035).
We also analyzed marital status, and found that in participants without DR, 27/30 were married or cohabitating, and only 3/30 were single, never married, or widowed. However, among those with PDR, only 13/26 were married or cohabiting (P = 0.003).
Lipid profile analysis showed that the TC concentrations was highest in participants with PDR, lowest in those without DR, and intermediate for those with NPDR (5.7 ± 1.3 mmol/L, 4.8 ± 1.1 mmol/L, and 5.7 ± 1.2 mmol/L, respectively; P = 0.018). There were similar trends for HDL-C and LDL-C concentrations, but these did not reach statistical significance (P = 0.052 and P = 0.067, respectively). (Table 2)
Demographic, biochemical and clinical differences among participants without DR, NPDR and PDR.
| Without DR (n = 30)a | NPDR (n = 26)a | PDR (n = 26)a | P valueb | |
|---|---|---|---|---|
| Male, n | 15/30 | 11/26 | 10/26 | 0.673 |
| Mean (s.d.) age, years | 58.2 (10.9) | 59.7 (10.8) | 52.1 (8.5) | 0.035 |
| Mean (s.d.) age at diagnosis, years | 18.7 (8.5) | 19.6 (8.9) | 12.7 (6.5) | 0.011 |
| Mean (s.d,) diabetes duration, years | 39.6 (7.2) | 39.9 (6.9) | 39.4 (5.7) | 0.967 |
| Family resources, na | 0.510 | |||
| Rural area | 5/30 | 4/26 | 7/26 | |
| Urban area | 25/30 | 22/26 | 19/26 | |
| Highest level of education, na | 0.342 | |||
| < University | 24/30 | 21/26 | 21/26 | |
| ≥ University | 6/30 | 5/26 | 5/26 | |
| Marital status, na | 0.003 | |||
| Married/cohabitating | 27/30 | 20/26 | 13/26 | |
| Single/never married/widowed | 3/30 | 6/26 | 13/26 | |
| Mean (s.d.) BMI (kg/m2) | 21.9 (2.4) | 23.2 (3.7) | 22.0 (1.7) | 0.235 |
| Mean (s.d,) SBP, mmHg | 124 (14) | 126 (21) | 128 (23) | 0.778 |
| Mean s.d,) DBP, mmHg | 72 (8) | 72 (14) | 74 (9) | 0.657 |
| Mean (s.d,) HbA1c, % | 6.8 (1.3) | 7.3 (1.4) | 6.8 (0.9) | 0.233 |
| Mean (s.d,) total cholesterol, mmol/L | 4.8 (1.1) | 4.9 (1.3) | 5.7 (1.2) | 0.018 |
| Mean (s.d,) HDL-C, mmol/L | 1.5 (0.3) | 1.5 (0.3) | 1.7 (0.4) | 0.052 |
| Mean (s.d,) LDL-C, mmol/L | 2.5 (0.7) | 2.8 (1.1) | 3.2 (1.1) | 0.067 |
| Mean (s.d,) triglyceride, mmol/L | 1.1 (0.6) | 1.1 (0.4) | 1.0 (0.5) | 0.972 |
a12 were missing for diabetes nephropathy status; 8 were missing for family resources, highest level of education, and marital status; bP value < 0.05 from chi-squared test and ANOVA test comparing participants without DR, with NPDR and with PDR.
BMI, body mass index; DBP, diastolic blood pressure; DR, diabetes retinopathy; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NPDR, non-proliferative diabetes retinopathy; PDR, proliferative diabetes retinopathy; SBP, systolic blood pressure.
Factors associated with DN
In the multivariable regression analysis, which was adjusted for HbA1c and LDL-C, urban/rural background, and SBP maintained their associations with DN. The OR (95% CI) for birth in a rural location was 4.76 (1.82, 8.81), compared with an urban location, and the equivalent statistics for SBP were 1.05 (1.01, 1.08). However, HbA1c and LDL-C were not associated with DN (the ORs (95% CIs) were 1.12 (0.61, 2.08) for HbA1c and 1.59 (0.83, 3.02) for LDL-C). (Table 3)
Factors associated with albuminuria according to multivariable logistic regression.
| OR | 95% CI | |
|---|---|---|
| Family resources | ||
| Rural area | 4.76 | 1.82, 8.81 |
| SBP, mmHg | 1.05 | 1.01, 1.08 |
| HbA1c, % | 1.12 | 0.61, 2.08 |
| LDL-C, mmol/L | 1.59 | 0.83, 3.02 |
Multivariable logistic regression including all variables with P < 0.10 in bivariate analysis.
DN, diabetes nephropathy; LDL-C, low-density lipoprotein cholesterol; SBP, systolic blood pressure.
Factors associated with DR
The association of marital status with DR remained after adjustment for age, age at diagnosis, TC, HDL-C, and LDL-C. The OR (95% CI) was 3.63 (1.49, 6.61) for non-proliferative DR versus no DR in patients who were married or cohabitating, and the OR (95% CI) was 8.09 (2.21, 14.11) for patients with PDR compared with noDR (Table 4).
Factors associated with NPDR and PDR according to multivariable logistic regression.
| OR | 95% CI | OR | 95% CI | |
|---|---|---|---|---|
| Marital status | ||||
| Married/cohabitating | Referent | Referent | ||
| Single/never married/widowed | 3.63 | 1.49, 6.61 | 8.09 | 2.21, 14.11 |
| Age, years | 1.06 | 0.96, 1.17 | 0.94 | 0.82, 1.07 |
| Age at diagnosis, years | 0.99 | 0.87, 1.11 | 0.98 | 0.85, 1.14 |
| Total cholesterol, mmol/L | 0.83 | 0.61, 2.12 | 2.54 | 1.35, 8.47 |
| HDL-C, mmol/L | 1.25 | 0.15, 8.24 | 1.72 | 0.23, 8.54 |
| LDL-C, mmol/L | 1.85 | 0.51, 5.59 | 1.90 | 0.81, 7.37 |
Multivariable logistic regression including all variables with P < 0.10 in bivariate analysis.
HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; NPDR, non-proliferative diabetes retinopathy; PDR, proliferative diabetes retinopathy.
Discussion
People who have lived with T1DM for a long time are likely to have characteristics that protect them against morbidity and mortality due to complications. This survival bias in the population enabled us to evaluate which factors might be protective in the present study. Our findings suggest that patients with T1DM who do not develop microvascular complications are more likely to have higher socio-economic status, illustrated by a higher likelihood of having been born in urban area, to be married or cohabitating, and in the case of DN, to have lower blood pressure.
The presence of renal disease is the major predictor of mortality for patients with T1DM, and those without renal disease have been shown to show mortality comparable to the general population. (13) In the present study, only 28/60 of the participants were normoalbuminuric, which is a lower percentage than that previously published for Caucasians. In the Joslin 50-Year Medalist Study of patients who had had diabetes for more than 50 years, 70.3% were normoalbuminuric, (7) and in the UK Golden Years Cohort, a group of 400 patients with T1DM of >50 years’ duration, 64% were normoalbuminuric. (14, 15) Efficient long-term self-management aimed at improving blood glucose, blood pressure, and cholesterol control, are crucial for the prevention of microvascular complications in diabetes. Given fact that China was underdeveloped and had limited health care resources 30 years ago, it is reasonable to infer that the higher prevalence of DN in the present study was largely due to poor diabetes care in the past.
We found that birth location was associated with the development of DN in the present study. This is an important sociodemographic characteristic in China, which is representative of the kind of social environment in which an individual is born and brought up. China was underdeveloped three decades ago, especially in rural areas. It is likely that individuals who did not have DN had better glucose control, particularly during the early phase of their diabetes, than those who had developed DN. In the T1D Exchange Clinic Registry cohort, indicators of higher socio-economic status, such as income, health insurance, educational level, and marital status were also associated with better glycemic control. (16) Socioeconomic status correlates with the level of self-management skills, such as the frequency of self-monitoring of blood glucose (SMBG) measurements, the timing of the meal bolus, and the frequency with which an insulin dose is missed, all of which are important for good glycemic control and better long-term outcomes. In the Finnish Diabetic Nephropathy (FinnDiane) study, which had a median 7-year follow-up period, chronic kidney disease was shown to predict all-cause mortality in T1DM patients. (17) Furthermore, an analysis of data from the Swedish National Diabetes Register of 24,947 T1DM patients showed that lower socioeconomic status increases the risk of mortality by a factor of two-to-three. (18) Deficiencies in diabetes care and resources, particularly soon after diagnosis, may account for the high prevalence of DN in the present cohort, and might also explain the overall higher mortality risk for people with T1DM living in China.
As shown in previous studies, SBP was also associated with the development of DN in the present cohort. In the UK Golden Years Cohort, hypertension was also significantly associated with DN. (8) In addition, similar results were obtained in the study of Swedish National Diabetes Register data, which suggested that better SBP control is protective against DN in patients who have had T1DM for >50 years. (19) Given the fact that careful blood pressure control is crucial for the prevention of DN in T1DM, our study highlights the importance of screening for and the treatment of hypertension in T1DM patients to prevent DN.
One interesting finding of the present study is that marital status was associated with DR in the multivariable analysis, an association that has not been identified in other studies of long-standing T1DM. However, individuals who are married or cohabitating are also more likely to have higher socioeconomic status, and the cross-sectional design of the present study means that a causal relationship between marital status and diabetic complications cannot be inferred. However, a previous study of T1DM patients showed that married or cohabiting individuals were more likely to show better glycemic control and self-care (20). These findings remind us of the importance of considering the well-being of patients with this chronic disease in clinical practice.
Although there was a trend for lower HbA1c to be associated with the absence of DN, HbA1c was not associated with DN or DR in the multivariable analyses. This might be because we provided free insulin and glucose strips for the participants, which better enabled them to achieve appropriate glycemic control. Indeed, the mean HbA1c of nearly 7.0% in the present cohort is indicative of good glucose control in many of the participants. Future studies follow the current and other cohorts longitudinally to more accurately determine the relationships between HbA1c and the development of microvascular complications.
Relative youth, a shorter duration of diabetes, and lower HbA1c, BMI, and triglyceride concentration have been shown to be protective against microvascular complications in other similar studies. (8, 15) Although we were able to see beneficial trends for lower HbA1c and better lipid control in the present study, multivariable analysis showed no significant associations between these factors and the development of microvascular complications. One possible reason for this may be the relatively small number of participants in the present study. However, given that this was a nationwide program initiated by the CDS, which provided diabetic care supplies as an incentive, the care of patients with T1DM in China is a cause for concern.
There were several limitations to the present study. First, it is important to emphasize that due to the cross-sectional design of the study, selection bias may represent a major confounder, because patients with advanced microvascular complications may not have survived long enough to be enrolled in the study. Second, we studied a relatively small cohort, which reduces the statistical power of the analyses and generates less precise estimates.
In conclusion, our study has shown that higher socioeconomic status, represented by birth in an urban area, being married or cohabitating, and better blood pressure control are associated with a lower risk of diabetic microvascular complications in patients with long-standing T1DM living in China. These findings emphasize the importance of improving medical care for this group, and future studies should be conducted regarding the most appropriate targets and most effective approaches to the prevention of such complications.
Supplementary materials
This is linked to the online version of the paper at https://doi.org/10.1530/EC-19-0521.
Declaration of interest
The authors declare that there is no conflict of interest that could be perceived as prejudicing the impartiality of the research reported.
Funding
This work was supported by National Natural Science Foundation of China (grant number 81700722, 81970698) and the National Key Research and Development Program (grant number 2016YFC1304901).
Acknowledgements
The authors would like to thank all the participants and the physicians who helped with data and sample collection: Rongwen Bian, Jiangsu Provincial Hospital; Hanqing Cai, The Second Affiliated Hospital of Jilin University; Zhimei Deng, Heilongjiang Province Qiqihar Hospital; Hongjie Di, Jiangsu Integrated Traditional Chinese and Western Medicine Hospital; Yatao Ding, Yanghou Hongquan Hospital; Jingtao Dou, China PLA General Hospital; Bo Feng, Shanghai East Hospital; Xuhua Gao and Qidong Zheng, Zhejiang Province Yuhuan Hospital; Chunxiu Gong, Beijing Children’s Hospital; Xiaoju Guan, Shanxi Province Taiyuan Heping Hospital; Lixin Guo, Beijing Hospital; Ruiqing Guo, Hebei Province Cangzhou Second Hospital; Xiaohui Guo and Nan Gu, Peking University First Affiliated Hospital; Xu Hong, Beijing Friendship Hospital; Hui Hui, Hunan Province Binzhou Hospital; Qiuhe Ji, Xi’an Xijing Hospital; Jinhua Jiang, Yanbian Second Hospital; Hui Jin, Dongnan University Zhongda Hospital; Weihong Li, Shanxi Province Yangquan Hospital; Yuxia Li, Shanxi Province Yuncheng Tongde Hospital; Ziling Li, Neimenggu Baogang Hospital; Shaoda Lin and Kun Lin, Guangdong Province Shantou First Hospital; Chang Liu, Hunan Province Binzhou First Hospital; Hongfei Liu, Hunan Province Third Hospital; Changmei Liu, Binyi Hospital; Jie Liu, Shanxi Province People’s Hospital; Juming Lu, China PLA General Hospital; Weiping Lu, Jiangsu Province Huaian Hospital; Weiguang Luo, Shenyang Fourth Hospital; Li Mao, Jiangsu Province Huaian Hospital; Anhua Shao, Shanghai First Hospital; Yi Shen, Hebei Province Qinhuangdao First Hospital; Jianying Tang, Shanghai Third Hospital; Zhenghe Tang, Shandong Province Laigang Hospital; Chenggong Tian, Nanjing Gulou Hospital; Haoming Tian and Sheyu Li, Sichuan University Huaxi Hospital; Su Wang, Tianjing Fifth Hospital; Ying Wang, Jiangsu Province Yangzhou First Hospital; Feng Wei, Shandong Province Binzhou Hospital; Jianping Xiang, Hunan Province Huaihua First Hospital; Xinhua Xiao and Jianping Xu, Beijing Union Hospital; Zhangrong Xu, China PLA 306 Hospital; Bingquan Yang, Dongnan University Zhongda Hospital; Jianming Yang, Hubei Province Yichang First Hospital; Jie Yang, Shandong Province Taian Hospital; Sujie Yang, Shandong Luzhong Hospital; Tao Yang, Jiangsu Province People’s Hospital; Hong Yin, Gansu Province Lanzhou First Hospital; Xiaohua Yu, Liaoning Province Liaoyang Central Hospital; Jing Zhang, Shanxi Province Integrated Traditional Chinese and Western Medicine Hospital; Lei Zhang, Qingdao Diabetes Hospital; Qian Zhang, Guiyang Medical School Second Affiliated Hospital; Xiaokai Zhang, Fujian Province General Hospital; Ying Zhang, Guangzhou Medical School Third Affiliated Hospital; Qiu Zhang, Anhui Medical School First Affiliated Hospital; Meihua Zhao, Jiangsu Province Huaian First Hospital; Qian Zhao, Ningxia Province People’s Hospital; Hui Zheng, Tianjing Taida International Cardiovascular Hospital; Mao Zheng, Anhui Province General Hospital; Hong Zhong, Heilongjiang Province General Hospital; Jiaqiang Zhou, Sir Run Run Shaw Hospital; Qun Zhu, Nanjing Medical University Second Affiliated Hospital; and Benliang Zou, Xiyuan Hospital China Academy of Chinese Medical Sciences.
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