INTRODUCTION: Degenerative mitral stenosis (DMS) is frequently cited as increasing in prevalence in the developed world, although comparatively little is known about DMS in comparison to rheumatic mitral stenosis (RMS). METHOD: A retrospective observational study was conducted on 745 cases of native-valve mitral stenosis (MS) with median follow-up time of 7.25 years. Clinical and echocardiographic parameters were compared. Univariate and multivariate Cox regression analyses were performed for a composite of all-cause mortality and heart failure hospitalisation. RESULTS: Patients with DMS compared to RMS were older (age, mean ± standard deviation: 69.6 ± 12.3 versus [vs] 51.6 ± 14.3 years, respectively; P<0.001) and a greater proportion had medical comorbidities such as diabetes mellitus (78 [41.9%] vs 112 [20.0%], P<0.001). The proportion of cases of degenerative aetiology increased from 1.1% in 1991-1995 to 41.0% in 2016-2017. In multivariate analysis for the composite outcome, age (hazard ratio [HR] 95% confidence interval [CI] of 1.032 [1.020-1.044]; P<0.001), diabetes mellitus (HR 1.443, 95% CI 1.068-1.948; P=0.017), chronic kidney disease (HR 2.043, 95% CI 1.470-2.841; P<0.001) and pulmonary artery systolic pressure (HR 1.019, 95% CI 1.010- 1.027; P<0.001) demonstrated significant indepen-dent associations. The aetiology of MS was not independently associated with the composite outcome. CONCLUSION DMS is becoming an increasingly common cause of native-valve MS. Despite numerous clinical differences between RMS and DMS, the aetiology of MS did not independently influence a composite of mortality or heart failure hospitalisation.
Humans ; Mitral Valve Stenosis/etiology* ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Rheumatic Heart Disease/mortality* ; Echocardiography ; Hospitalization/statistics & numerical data* ; Heart Failure/epidemiology* ; Singapore/epidemiology* ; Proportional Hazards Models ; Diabetes Mellitus/epidemiology*

BACKGROUND: The epidemiological pattern and disease burden of type 2 diabetes have been shifting in China over the past decades. This analysis described the epidemiological transition of type 2 diabetes in the past three decades and projected the trend in the future three decades in China. METHODS: Age-, sex-, and year-specific incidence, prevalence, death, and disability-adjusted life years (DALYs) for people with 15 years or older and diabetes or high fasting glucose in China and related countries from 1990 to 2021 were obtained from the Global Burden of Disease. We obtained the trends of age-, sex-, and year-specific rates and absolute numbers of incidence, prevalence, deaths, and DALYs attributable to type 2 diabetes in China from 1990 to 2021. Using the Lee-Carter model, we projected the incidence, prevalence, death, and DALYs attributable to type 2 diabetes to 2050 stratified by age and sex. RESULTS: The age-standardized incidence of type 2 diabetes was 341.5 per 100,000 persons (1.6 times in 1990) and the age-standardized prevalence was 9.96% (9960.0 per 100,000 persons, 2.5 times in 1990) in China 2021. In 2021, there were 0.9 million deaths and 26.8 million DALYs due to type 2 diabetes or hyperglycemia, as 2.9 and 2.7 times the data in 1990, respectively. The age-standardized rates of type 2 diabetes and hyperglycemia were projected to raise to 449.5 per 100,000 persons for incidence, 18.17% for prevalence, 244.6 per 100,000 persons for death, and 4720.2 per 100,000 persons for DALYs by 2050. The incidence of type 2 diabetes kept growing among individuals under the age of 20 years in the past three decades (128.7 per 100,000 persons in 1990 and 439.9 per 100,000 persons in 2021) and estimating 1870.8 per 100,000 in 2050. CONCLUSIONS The incidence, prevalence, and disease burden of type 2 diabetes grew rapidly in China in the past three decades. The prevention of type 2 diabetes in young people and the care for elder adults will be the greatest challenge for the country.
Humans ; Diabetes Mellitus, Type 2/mortality* ; China/epidemiology* ; Prevalence ; Female ; Male ; Incidence ; Middle Aged ; Adult ; Aged ; Adolescent ; Young Adult ; Disability-Adjusted Life Years ; Aged, 80 and over

The Healthy China 2030 Plan set the goal of reducing premature deaths from diabetes by 30% by 2030. However, there has been a lack of assessment of premature mortality for diabetes since the action plan was issued. This study used data from the Global Burden of Disease Study 2021, calculated the premature deaths for diabetes by sex, provinces, and subtypes from 1990 to 2021. We explored the temporal trend of premature mortality using the average annual percent change (AAPC) for different sexes, provinces, and subtypes from 1990 to 2021. Furthermore, we predicted premature mortality for diabetes through 2030 for China and its provinces according to the average annual change rate from 2010 to 2021. There was a first slow upward trend in premature mortality for diabetes from 0.5% in 1990 to 0.6% in 2004, and then a decline until 2021 with premature mortality of 0.4%. By 2030, only Fujian (30.3%) will achieve the desired level of reduction, with only seven provinces meeting the target for females and none for males. There is a large range in the degree of decline between inland and coastal regions, showing obvious geographic differences, and there should be a focus on balancing medical resources.
Humans ; China/epidemiology* ; Female ; Male ; Mortality, Premature/trends* ; Diabetes Mellitus/mortality* ; Goals ; Middle Aged ; Adult

OBJECTIVE: To analyze the influence of type 2 diabetes mellitus (DM) on the prognosis of oral squamous cell carcinoma (OSCC) patients with surgical treatment. METHODS: The clinical data of 309 patients, who were diagnosed with OSCC and admitted to the same ward of Peking University Hospital of Stomatology from January 2014 to December 2017 were retrospectively reviewed, of whom, 104 were classified into DM group and 205 into non-DM group. The basic clinical data and follow-up results of the patients were analyzed and compared. Propensity score matching (PSM) was used to reduce confounding bias between the DM group and the non-DM group. Kaplan-Meier was used to calculate the survival rate of the two groups. Proportional hazards model was used to analyze the independent prognostic factors. The effect of glucose level on survival was analyzed. RESULTS: After PSM, 77 patients in each group were matched and the variables were balanced. There were statistically significant differences in postoperative oral dysplasia and local recurrence between the two groups (P < 0.05). There was no significant difference in survival analysis between the two groups, but the survival rate of the DM group had the tendency to be lower than that of the non-DM group after matching. Univariate analysis and multiva-riate analysis both revealed that the tumor stage was an independent factor influencing the overall survival rate and tumor-specific survival rate of the OSCC patients (P < 0.05), while diabetes had no significant influence on the survival of the OSCC patients (P>0.05). Multivariate analysis showed that tumor stage, triglyceride level, preoperative mean capillary fasting blood glucose, postoperative mean postprandial blood glucose were indepen-dent prognostic factors for overall survival in the DM group. Tumor stage and mean postoperative postprandial blood glucose were independent prognostic factors for tumor-specific survival in the DM group. The risk of postoperative complications and distant metastasis in the DM group with poor glycemic control was higher than that in the good glycemic controls. CONCLUSION There is no significant difference in overall survival and tumor-specific survival of the patients with or without DM. However, the possibility of mucosal dysplasia or local recurrence in the DM group is higher than that in the non-DM group. The tumor stage, triglyceride level and glycemic control of the patients with DM may affect their prognosis.
Humans ; Diabetes Mellitus, Type 2/complications* ; Mouth Neoplasms/mortality* ; Retrospective Studies ; Prognosis ; Carcinoma, Squamous Cell/mortality* ; Male ; Female ; Survival Rate ; Neoplasm Recurrence, Local ; Propensity Score ; Proportional Hazards Models ; Blood Glucose/analysis* ; Middle Aged ; Kaplan-Meier Estimate

Objective: To forecast mortality, age-standardized mortality, and probability of premature mortality from diabetes, and to simulate the impact of controlling risk factors by 2030 in China. Methods: We simulated the burden of disease from diabetes in six scenarios according to the development goals of risk factors control by the WHO and Chinese government. Based on the theory of comparative risk assessment and the estimates of the burden of disease for China from the Global Burden of Disease Study 2015, we used the proportional change model to project the number of deaths, age-standardized mortality, and probability of premature mortality from diabetes under different scenarios of risk factors control in 2030. Results: If the trends in exposures to risk factors from 1990 to 2015 continued. Mortality, age-standardized mortality, and probability of premature mortality from diabetes would increase to 32.57/100 000, 17.32/100 000, and 0.84% by 2030, respectively. During that time, mortality, age-standardized mortality and probability of premature mortality for males would all be higher than for females. If the goals of controlling risk factors were all achieved, the number of deaths from diabetes in 2030 would decrease by 62.10% compared to the predicted numbers based on the historical trends in exposure to risk factors, and the probability of premature mortality would drop to 0.29%. If only the exposure to a single risk factor were achieved by 2030, high fasting plasma glucose control would have the greatest impact on diabetes, resulting in a 56.00% reduction in deaths compared to the predicted numbers based on the historical trends, followed by high BMI (4.92%), smoking (0.65%), and low physical activity (0.53%). Conclusions: Risk factors control plays an important role in reducing the number of deaths, age-standardized mortality rate, and probability of premature mortality from diabetes. We suggest taking comprehensive measures to control relevant risk factors for certain populations and regions, to achieve the goal of reducing the burden of disease from diabetes as expected.
Male ; Female ; Humans ; Risk Factors ; Diabetes Mellitus/epidemiology* ; Mortality, Premature ; Smoking ; Cost of Illness ; China/epidemiology* ; Global Burden of Disease

Introduction: Hypoglycemia is an important and harmful complication that often occurs in inpatient and outpatient settings. This study aims to assess the incidence of inpatient hypoglycemia and its related factors. We also assessed mortality and length of hospital stay. Methodology: We performed a retrospective cohort study among patients with type 2 diabetes mellitus admitted to a tertiary hospital in Indonesia. Using multivariate regression, we analyzed age, sex, body mass index, comorbidities, history of hypoglycemia, hyperglycemia treatment administered, nutritional intake, and medical instruction as the related risk factors for inpatient hypoglycemia. Results: From 475 subjects, 80 (16.8%) had inpatient hypoglycemia, of which, 7.4% experienced severe hypoglycemia. We found that patients with a history of hypoglycemia (RR: 4.6; 95% CI: 2.8-7.6), insulin and/or sulfonylurea treatment (RR 6.4; 95% CI: 1.6-26.5), and inadequate nutritional intake (RR 2.6; 95% CI: 1.5-4.3) were more likely to have hypoglycemic events compared to those who did not. The length of hospital stay for patients in the hypoglycemic group is significantly longer than those in the non-hypoglycemic group (13 vs 7 days, p<0.001), but their mortality rates did not differ (16% vs 10.9%, p=0.18). Conclusion Inpatient hypoglycemia may be affected by a history of hypoglycemia and inadequate nutritional intake. Patients who had inpatient hypoglycemia tend to have a longer median length of hospital stay.
Hypoglycemia ; Diabetes Mellitus ; Insulin ; Mortality ; Length of Stay

Objective: To understand the characteristics and trend of the premature death rate of 4 major chronic diseases in Ji'nan from 2015 to 2020. Methods: The death cause surveillance data and population data during 2015-2020 in Ji'nan were collected, and abbreviated life table, Joinpoint regression analysis and other methods were used to analyze the characteristics and change trends of the premature death rates of 4 major chronic diseases. Results: The crude mortality rate and age standardized mortality rate changes for the 4 major chronic diseases from 2015 to 2020 range from 568.65/100 000 to 604.06/100 000 and 366.77/100 000 to 432.48/100 000, respectively. The annual premature death rate of 4 major chronic diseases declined by 3.33% averagely from 2015 to 2020 (95%CI: -6.25%--0.32%), which might be explained by the declines of the premature death rates of cardiovascular and cerebrovascular diseases [average annual percentage change (AAPC)=-3.23%, 95%CI: -6.32%--0.05%] and cancer (AAPC=-3.58%,95%CI:-6.83%--0.21%). The average decline rate in women (AAPC=-4.19%,95%CI:-7.56%- -0.70%) was higher than that in men (AAPC=-2.92%,95%CI: -5.65%--0.11%). Conclusions: The premature death rate of 4 major chronic diseases showed a downward trend in Ji'nan from 2015 to 2020. Men should be considered as a key population in the prevention and control of 4 major chronic diseases, and attention should also be paid to the non-significant declines in the premature death rates of chronic respiratory diseases and diabetes.
Cerebrovascular Disorders ; Chronic Disease ; Diabetes Mellitus ; Female ; Humans ; Male ; Mortality, Premature ; Regression Analysis

Introduction: Metformin has known mechanistic benefits on COVID-19 infection due to its anti-inflammatory effects and its action on the ACE2 receptor. However, some physicians are reluctant to use it in hypoxemic patients due to potential lactic acidosis. The primary purpose of the study was to determine whether metformin use is associated with survival. We also wanted to determine whether there is a difference in outcomes in subcategories of metformin use, whether at home, in-hospital, or mixed home/in-hospital use. Objectives: This study aimed to determine an association between metformin use and mortality among patients with type 2 diabetes mellitus hospitalized for COVID-19 infection. Methodology: This was a cross-sectional analysis of data acquired from the COVID-19 database of two tertiary hospitals in Cebu from March 1, 2020, to September 30, 2020. Hospitalized adult Filipino patients with type 2 diabetes mellitus who tested positive for COVID-19 via RT-PCR were included and categorized as either metformin users or metformin non-users. Results: We included 355 patients with type 2 diabetes mellitus in the study, 186 (52.4%) were metformin users. They were further categorized into home metformin users (n=109, 30.7%), in-hospital metformin users (n=40, 11.3%), and mixed home/in-hospital metformin users (n=37, 10.4%). Metformin use was associated with a lower risk for mortality compared to non-users (p=0.001; OR=0.424). In-hospital and mixed home/in-hospital metformin users were associated with lower mortality odds than non-users (p=0.002; OR=0.103 and p=0.005; OR 0.173, respectively). The lower risk for mortality was noted in metformin, regardless of dosage, from 500 mg to 2 g daily (p=0.002). Daily dose between ≥1000 mg to <2000 mg was associated with the greatest benefit on mortality (p≤0.001; OR=0.252). The survival distributions between metformin users and non-users were statistically different, showing inequality in survival (χ2=5.67, p=0.017). Conclusion Metformin was associated with a lower risk for mortality in persons with type 2 diabetes mellitus hospitalized for COVID-19 disease compared to non-users. Use of metformin in-hospital, and mixed home/in-hospital metformin use, was also associated with decreased risk for mortality. The greatest benefit seen was in those taking a daily dose of ≥1000 mg to <2000 mg.
Metformin ; Diabetes Mellitus ; COVID-19 ; Mortality

OBJECTIVE: The pathogenesis of myocardial injury upon corona virus disease 2019 (COVID-19) infection remain unknown,evidence of impact on outcome is insufficient, therefore, we aim to investigate the risk factors for death among COVID-19 patients combined with hypertension, coronary heart disease or diabetes in this study. METHODS: This was a single-centered, retrospective, observational study. Patients of Sino-French Eco-City section of Tongji Hospital, Wuhan, China attended by Peking University Supporting Medical Team and admitted from Jan. 29, 2020 to Mar. 20, 2020 were included. The positive nucleic acid of COVID-19 virus and combination with hypertension, coronary heart disease or diabetes were in the standard. We collected the clinical data and laboratory examination results of the eligible patients to evaluate the related factors of death. RESULTS: In the study, 94 COVID-19 patients enrolled were divided into the group of death (13 cases) and the group of survivors (81 cases), the average age was 66.7 years. Compared with the survival group, the death group had faster basal heart rate(103.2 beats/min vs. 88.4 beats /min, P=0.004), shortness of breath(29.0 beats /min vs. 20.0 beats /min, P<0.001), higher neutrophil count(9.2×10⁹/L vs. 3.8×10⁹/L, P<0.001), lower lymphocyte count(0.5×10⁹/L vs. 1.1×10⁹/L, P<0.001), creatine kinase MB(CK-MB, 3.2 μg/L vs. 0.8 μg/L, P<0.001), high sensitivity cardiac troponin Ⅰ(hs-cTnⅠ, 217.2 ng/L vs. 4.9 ng/L, P<0.001), N-terminal pro brain natriuretic peptide(NT-proBNP; 945.0 μg/L vs. 154.0 μg/L, P<0.001), inflammatory factor ferritin(770.2 μg/L vs. 622.8 μg/L , P=0.050), interleukin-2 recepter(IL-2R, 1 586.0 U/mL vs. 694.0 U/mL, P<0.001), interleukin-6(IL-6, 82.3 ng/L vs. 13.0 ng/L, P<0.001), interleukin-10(IL-10, 9.8 ng/L vs. 5.0 ng/L, P<0.001)were higher than those in the survival group. Univariate logistic regression analysis showed that the risk factors for death were old age, low non oxygen saturation, low lymphocyte count, myocardial injury, abnormal increase of IL 2R, IL-6, and IL-10. Multivariate regression showed that old age (OR=1.11, 95%CI=1.03-1.19, P=0.026), low non oxygen saturation(OR=0.85, 95%CI=0.72-0.99, P=0.041), and abnormal increase of IL-10(＞9.1 ng/L, OR=101.93, 95%CI=4.74-2190.71, P=0.003)were independent risk factors for COVID-19 patients combined with hypertension, coronary heart disease or diabetes. CONCLUSION In COVID-19 patients combined with hypertension, coronary heart disease or diabetes, the risk factors for death were old age, low non oxygen saturation, low lymphocyte count, myocardial injury, and abnormal increase of IL-2R, IL-6, and IL-10. Old age, low non oxygen saturation and abnormal increase of IL-10 were independent risk factors.
Aged ; Betacoronavirus ; COVID-19 ; China/epidemiology* ; Coronary Disease/complications* ; Coronavirus Infections/mortality* ; Diabetes Mellitus ; Humans ; Hypertension/complications* ; Pandemics ; Pneumonia, Viral/mortality* ; Retrospective Studies ; Risk Factors ; SARS-CoV-2

Diabetic kidney disease is a microvascular complication of diabetes mellitus and the leading cause of end-stage renal disease resulting in renal replacement therapy. Approximately 30% to 40% of diabetic patients have diabetic kidney disease, which contributes to a significant increase in morbidity and mortality. Microalbuminuria is considered the gold standard for diabetic kidney disease diagnosis; however, its predictive value is restricted. Although blood glucose control, blood pressure control, and angiotensin converting enzyme inhibitors have been the primary treatment strategies, there are no definitive treatment modalities capable of inhibiting the progression of kidney dysfunction in these patients. This study was undertaken to answer seven questions regarding the various aspects of diabetic kidney disease. Why does it develop? what kind of factors affect its development? How is it diagnosed? What are its possible biomarkers? When is a kidney biopsy necessary? What are the preventive and therapeutic options? And what are the novel treatments?
Angiotensin-Converting Enzyme Inhibitors ; Biomarkers ; Biopsy ; Blood Glucose ; Blood Pressure ; Diabetes Mellitus ; Diabetic Nephropathies ; Diagnosis ; Humans ; Kidney ; Kidney Failure, Chronic ; Mortality ; Renal Replacement Therapy