OBJECTIVE:To observe clinical efficacy and safety of Tianqi jiangtang capsules combined with metformin in the treatment of elderly patients with type 2 diabetes mellitus complicated with cerebral microvascular lesions. METHODS:A total of 96 elderly patients with type 2 diabetes mellitus complicated with cerebral microvascular lesions were randomly divided into control group(48 cases)and observation group(48 cases). Control group was given Metformin hydrochloride tablets 0.5 g orally,3 times a day. Observation group was additionally given Tianqi jiangtang capsules 1.6 g orally,3 times a day,on the basis of control group. Both groups received treatment for 4 weeks. Clinical efficacies of 2 groups were observed as well as total score of TCM symptoms,the levels of blood glucose(FPG,2 hPG,HbA1c),blood lipid(TC,TG,HDL-C,LDL-C),hs-CRP,ET-1,blood rheology and oxidative stress indexes(MDA,SOD),the occurrence of ADR. RESULTS:The total response rate of observation group was significantly higher than that of control group(89.58% vs. 70.83%),with statistical significance(P<0.05). After treat-ment,total score of TCM symptoms,the levels of blood glucose,hs-CRP,ET-1,TC,TG,LDL-C,blood rheology indexes and MDA in 2 groups were significantly lower than before;total score of TCM symptoms,the levels of FPG,2 hPG,hs-CRP,ET-1, TC,TG,LDL-C,blood rheology indexes and MDA in observation group were significantly lower than control group;the level of SOD in 2 groups were significantly higher than before,and the observation group was significantly higher than control group,and the level of HDL-C in observation group was significantly higher than before treatment and control group,with statistical signifi-cance(P<0.05). No obvious ADR was found in 2 groups during treatment. CONCLUSIONS:Tianqi jiangtang capsules combined with metformin show significant therapeutic efficacy in the treatment of elderly patients with type 2 diabetes mellitus,and can re-duce the levels of blood glucose and lipid,improve blood rheology and oxidative stress reaction,with goud safety.

Objective:To investigate the association between metabolically healthy obesity(MHO) and atherosclerosis risk among Chinese community population aged 40 or older.Methods:A total of 9 525 participants without cardiovascular diseases (3 621 men and 5 904 women) from Jiading community in Shanghai were enrolled to complete questionnaires, undergo extensive physical examination including brachial-ankle pulse wave velocity (baPWV) and blood pressure (BP) assessment, and laboratory screening. According to body mass index (BMI) and metabolic status, these participants were categorized into 4 groups including metabolically healthy non-obese (MHNO), metabolically unhealthy non-obese (MUNO), MHO, and metabolically unhealthy obese (MUO). High baPWV was defined as baPWV>1 400 mm/s, and high pulse pressure (PP) was defined as PP above fourth quartile of the population. Multivariate logistic regression model was conducted to explore the relationship between MHO and high baPWV as well as high PP after adjusting for confounders. Results:After multivariable adjustment, such as sex, age, current smoking, current drinking, and education, logistic regression analysis showed that MHO was significantly correlated with high baPWV ( OR=1.18, 95% CI 1.02-1.37) and high PP ( OR=1.72, 95% CI 1.43-2.08) in comparison with MHNO. Otherwise, both MUNO and MUO subjects were at higher risk for suffering from high baPWV (MUNO: OR=3.02, 95% CI 2.60-3.50; MUO: OR=3.26, 95% CI 2.87-3.70) and high PP (MUNO: OR=2.56, 95% CI 2.17-3.02; MUO: OR=3.49, 95% CI 3.01-4.06). Conclusion:On the basis of Chinese community population, there was a pronounced correlation between the MHO phenotype and the increased risk of developing atherosclerosis.

Objective:To screen the incidence of proteinuria in rural areas of Shanxi province and construct a risk prediction model of proteinuria based on machine learning algorithm.Methods:It was a cross-sectional investigation study. The residents ≥30 years old in rural areas of Shanxi province from April to November 2019 were screened by multi-stage stratified sampling method, and data from questionnaire surveys, physical examinations, and laboratory examinations were collected. Urine albumin/creatinine ratio ≥30 mg/g was defined as proteinuria, and the incidence of proteinuria was calculated. Subjects were divided into proteinuria group and non-proteinuria group. The machine learning binary classification model of proteinuria and non-proteinuria was constructed based on the stackable integrated logistic regression algorithm (SE-LR), logistic regression, support vector machine, decision tree, random forest and extreme gradient lift algorithms, respectively. The area under the receiver operating characteristic curve, accuracy, recall, and F1 weights were used to evaluate the predictive efficiency of the comparison models. Finally, the importance of the predictive features of the model with the best overall performance was ranked.Results:There were 8 869 rural residents included in the study, aged (58.59±9.49) years old, with 3 872 males (43.66%) and 4 997 females (56.34%). The prevalence of proteinuria in rural areas of Shanxi province was 13.49% (1 196/8 869). Blood pressure, pulse, body mass index, waist circumference, proportion of obesity or overweight, proportion of hypertension, proportion of moderate to severe salt intake, glycosylated hemoglobin, uric pH value, urinary specific gravity, proportion of positive urinary occult blood, proportion of positive urinary glucose, proportion of positive urinary ketone body, proportion of urinary red blood cell count ≥5/μl, proportion of urinary white blood cell count ≥10/μl and urinary α1 microglobulin in the proteinuria group were all higher than those in the non-proteinuria group (all P<0.05). The proportions of lack of exercise and drinking history in the proteinuria group were lower than those in non-proteinuria group (both P<0.05). The overall performance of SE-LR model was the best, with the area under the curve (0.736, 95% CI 0.719-0.746) slightly lower than that of the logistic regression model (0.745, 95% CI 0.680-0.762), and the highest accuracy (0.844), recall rate (0.621) and F1 weighting value (0.801). In the SE-LR model, the orders of importance of the top 10 features were urinary α1- microglobulin, urinary occult blood, urinary sugar, uric acid basicity, smoking history,overweight or obesity, body mass index, total cholesterol, glycosylated hemoglobin and hypertension. Conclusions:The prevalence of proteinuria is high in rural areas of Shanxi province. The risk prediction model of proteinuria established by machine learning algorithm can predict the risk of proteinuria and identify its risk factors, which can provide a scientific basis for disease prevention, intervention, and treatment in the community and clinic to a certain extent.

Background/Aims: Low educational attainment is a well-established risk factor for nonalcoholic fatty liver disease (NAFLD) in developed areas. However, the association between educational attainment and the risk of NAFLD is less clear in China. Methods: A cross-sectional study including over 200,000 Chinese adults across mainland China was conducted. Information on education level and lifestyle factors were obtained through standard questionnaires, while NAFLD and advanced fibrosis were diagnosed using validated formulas. Outcomes included the risk of NAFLD in the general population and high probability of fibrosis among patients with NAFLD. Logistic regression analysis was employed to estimate the risk of NAFLD and fibrosis across education levels. A causal mediation model was used to explore the potential mediators. Results: Comparing with those receiving primary school education, the multi-adjusted odds ratios (95% confidence intervals) for NAFLD were 1.28 (1.16 to 1.41) for men and 0.94 (0.89 to 0.99) for women with college education after accounting for body mass index. When considering waist circumference, the odds ratios (95% CIs) were 0.94 (0.86 to 1.04) for men and 0.88 (0.80 to 0.97) for women, respectively. The proportions mediated by general and central obesity were 51.00% and 68.04% for men, while for women the proportions were 48.58% and 32.58%, respectively. Furthermore, NAFLD patients with lower educational attainment showed an incremental increased risk of advanced fibrosis in both genders. Conclusions In China, a low education level was associated with a higher risk of prevalent NAFLD in women, as well as high probability of fibrosis in both genders.

A new definition of metabolic dysfunction-associated fatty liver disease (MAFLD) has recently been proposed. We aim to examine the associations of MAFLD, particularly its discordance from non-alcoholic fatty liver disease (NAFLD), with the progression of elevated brachial-ankle pulse wave velocity (baPWV) and albuminuria in a community-based study sample in Shanghai, China. After 4.3 years of follow-up, 778 participants developed elevated baPWV and 499 developed albuminuria. In comparison with the non-MAFLD group, the multivariable adjusted odds ratio (OR) of MAFLD group for new-onset elevated baPWV was 1.25 (95% confidence interval (CI) 1.01-1.55) and 1.35 (95% CI 1.07-1.70) for albuminuria. Participants without NAFLD but diagnosed according to MAFLD definition were associated with higher risk of incident albuminuria (OR 1.77; 95% CI 1.07-2.94). Patients with MAFLD with high value of hepamet fibrosis score or poor-controlled diabetes had higher risk of elevated baPWV or albuminuria. In conclusion, MAFLD was associated with new-onset elevated baPWV and albuminuria independently of body mass index, waist circumference, and hip circumference. Individuals without NAFLD but diagnosed as MAFLD had high risk of albuminuria, supporting that MAFLD criteria would be practical for the evaluation of long-term risk of subclinical atherosclerosis among fatty liver patients.
Humans ; Pulse Wave Analysis ; Albuminuria ; Ankle Brachial Index ; Non-alcoholic Fatty Liver Disease/diagnosis* ; Vascular Stiffness ; Prospective Studies ; Risk Factors ; China/epidemiology*