Objective: To explore the associations of glycated hemoglobin (HbA1c) with FPG and oral glucose tolerance test 2-hour (OGTT-2 h) in areas at different altitude in China. Methods: Subjects who participated in 2018-2019 China Chronic Disease and Risk Factor Surveillance and had no prior type 2 diabetes diagnosis were included. Subsequently, they were categorized into three groups based on altitude of living area (<2 000, 2 000- and ≥3 000 m). With adjustment for intracluster correlation, multivariable linear regression analysis was performed to evaluate the associations of HbA1c with FPG and OGTT-2 h in the context of HbA1c was normal (<5.7%) or abnormal (≥5.7%). Furthermore, the shape of relationships between HbA1c and glucose indicators was examined using restricted cubic spline. Finally, receiver operating characteristic curve was used to evaluate the diagnostic performance of HbA1c for diabetes. Results: A total of 157 277 subjects were included in the analysis. While FPG and OGTT-2 h levels gradually decreased with increase of altitude, HbA1c level was similar among the three groups. When HbA1c was <5.7%, its association with FPG and OGTT-2 h was weak and no obvious difference was observed among the three groups. When HbA1c was ≥5.7%, the FPG and OGTT-2 h increased by 15.45% (95%CI:14.71%- 16.18%) and 24.54% (95%CI:23.18%-25.91%) respectively per one standard deviation increase in HbA1c in group in area at altitude <2 000 m. However, the FPG and OGTT-2 h increased by 13.08% (95%CI:10.46%-15.76%) and 21.72% (95%CI:16.39%-27.31%), respectively, in group in area at altitude 2 000- m, and increased by 11.41% (95%CI:9.32%-13.53%) and 20.03% (95%CI:15.38%- 24.86%), respectively, in group of altitude ≥3 000 m. The restricted cubic spline indicated that the curve showing the association of HbA1c with FPG and OGTT-2 h was flat when HbA1c was <5.7%, but showed a positive linear relationship when HbA1c was ≥5.7%. The area under curve for detecting diabetes was 0.808 (95%CI:0.803-0.812) in group of altitude <2 000 m and 0.728 (95%CI:0.660-0.796, P=0.022) in group of altitude ≥3 000 m. The relevant optimal cutoff value of HbA1c was 5.7%, with a sensitivity of 65.4% and a specificity of 83.0%, and 6.0%, with a sensitivity of 48.3% and a specificity of 93.7%, respectively. Conclusions: When HbA1c was ≥5.7%, the association between HbA1c and glucose indicators became weaker as the increase of altitude. In the area at altitude ≥3 000 m, it may not be appropriate to use HbA1c in the diagnosis of diabetes.
Adult ; Humans ; Glycated Hemoglobin ; Diabetes Mellitus, Type 2/diagnosis* ; Blood Glucose/analysis* ; Glucose ; Altitude ; Fasting ; China/epidemiology* ; Diabetes Mellitus/epidemiology*

Most information used to evaluate diabetic statuses is collected at a special time-point, such as taking fasting plasma glucose test and providing a limited view of individual's health and disease risk. As a new parameter for continuously evaluating personal clinical statuses, the newly developed technique "continuous glucose monitoring" (CGM) can characterize glucose dynamics. By calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropy analysis of the CGM data, the study showed for the first time that the complexity of glucose time series in subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then to type 2 diabetes (P for trend < 0.01). Furthermore, CGI was significantly associated with various parameters such as insulin sensitivity/secretion (all P < 0.01), and multiple linear stepwise regression showed that the disposition index, which reflects β-cell function after adjusting for insulin sensitivity, was the only independent factor correlated with CGI (P < 0.01). Our findings indicate that the CGI derived from the CGM data may serve as a novel marker to evaluate glucose homeostasis.
Humans ; Glucose ; Blood Glucose ; Insulin Resistance/physiology* ; Diabetes Mellitus, Type 2/diagnosis* ; Blood Glucose Self-Monitoring ; Time Factors ; Insulin

Objective To investigate the cardiac structural and functional characteristics in the patients with heart failure with preserved ejection fraction (HFpEF) and type 2 diabetes mellitus (T2DM),and predict the factors influencing the characteristics. Methods A total of 783 HFpEF patients diagnosed in the Department of Geriatric Cardiology,the First Hospital of Lanzhou University from April 2009 to December 2020 were enrolled in this study.Echocardiography and tissue Doppler technique were employed to evaluate cardiac structure and function.According to the occurrence of T2DM,the patients were assigned into a HFpEF+T2DM group (n=332) and a HFpEF group (n=451).Propensity score matching (PSM)(in a 1∶1 ratio) was adopted to minimize confounding effect.According to urinary albumin excretion rate (UAER),the HFpEF+T2DM group was further divided into three subgroups with UAER<20 μg/min,of 20-200 μg/min,and>200 μg/min,respectively.The comorbidities,symptoms and signs,and cardiac structure and function were compared among the groups to clarify the features of diabetes related HFpEF.Multivariate linear regression was conducted to probe the relationship of systolic blood pressure,blood glucose,glycosylated hemoglobin,and UARE with cardiac structural and functional impairment. Results The HFpEF+T2DM group had higher prevalence of hypertension (P=0.001) and coronary heart disease (P=0.036),younger age (P=0.020),and larger body mass index (P=0.005) than the HFpEF group,with the median diabetic course of 10 (3,17) years.After PSM,the prevalence of hypertension and coronary heart disease,body mass index,and age had no significant differences between the two groups(all P>0.05).In addition,the HFpEF+T2DM group had higher interventricular septal thickness (P=0.015),left ventricular posterior wall thickness (P=0.040),and left ventricular mass (P=0.012) and lower early diastole velocity of mitral annular septum (P=0.030) and lateral wall (P=0.011) than the HFpEF group.Compared with the HFpEF group,the HFpEF+T2DM group showed increased ratio of early diastolic mitral filling velocity to early diastolic mitral annular velocity (E/e') (P=0.036).Glycosylated hemoglobin was correlated with left ventricular mass (P=0.011),and the natural logarithm of UAER with interventricular septal thickness (P=0.004),left ventricular posterior wall thickness (P=0.006),left ventricular mass (P<0.001),and E/e' ratio (P=0.049). Conclusion The patients with both T2DM and HFpEF have thicker left ventricular wall,larger left ventricular mass,more advanced left ventricular remodeling,severer impaired left ventricular diastolic function,and higher left ventricular filling pressure than the HFpEF patients without T2DM.Elevated blood glucose and diabetic microvascular diseases might play a role in the development of the detrimental structural and functional changes of the heart.
Humans ; Aged ; Heart Failure/diagnosis* ; Diabetes Mellitus, Type 2 ; Stroke Volume ; Glycated Hemoglobin ; Blood Glucose ; Propensity Score ; Ventricular Function, Left ; Hypertension

Blood glucose monitoring has become the weakest point in the overall management of diabetes in China. Long-term monitoring of blood glucose levels in diabetic patients has become an important means of controlling the development of diabetes and its complications, so that technological innovations in blood glucose testing methods have far-reaching implications for accurate blood glucose testing. This article discusses the basic principles of minimally invasive and non-invasive blood glucose testing assays, including urine glucose assays, tear assays, methods of extravasation of tissue fluid, and optical detection methods, etc., focuses on the advantages of minimally invasive and non-invasive blood glucose testing methods and the latest relevant results, and summarizes the current problems of various testing methods and prospects for future development trends.
Humans ; Blood Glucose ; Blood Glucose Self-Monitoring/methods* ; Diabetes Mellitus/diagnosis* ; Monitoring, Physiologic/methods* ; Tears

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

OBJECTIVES: The incidence of type 2 diabetes mellitus has increased significantly in recent years. With the development of artificial intelligence applications in healthcare, they are used for diagnosis, therapeutic decision making, and outcome prediction, especially in type 2 diabetes mellitus. This study aimed to identify the artificial intelligence (AI) applications for type 2 diabetes mellitus care. METHODS: This is a review conducted in 2018. We searched the PubMed, Web of Science, and Embase scientific databases, based on a combination of related mesh terms. The article selection process was based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Finally, 31 articles were selected after inclusion and exclusion criteria were applied. Data gathering was done by using a data extraction form. Data were summarized and reported based on the study objectives. RESULTS: The main applications of AI for type 2 diabetes mellitus care were screening and diagnosis in different stages. Among all of the reviewed AI methods, machine learning methods with 71% (n = 22) were the most commonly applied techniques. Many applications were in multi method forms (23%). Among the machine learning algorithms applications, support vector machine (21%) and naive Bayesian (19%) were the most commonly used methods. The most important variables that were used in the selected studies were body mass index, fasting blood sugar, blood pressure, HbA1c, triglycerides, low-density lipoprotein, high-density lipoprotein, and demographic variables. CONCLUSIONS: It is recommended to select optimal algorithms by testing various techniques. Support vector machine and naive Bayesian might achieve better performance than other applications due to the type of variables and targets in diabetes-related outcomes classification.
Artificial Intelligence ; Blood Glucose ; Blood Pressure ; Body Mass Index ; Classification ; Decision Making ; Delivery of Health Care ; Diabetes Mellitus ; Diabetes Mellitus, Type 2 ; Diagnosis ; Fasting ; Incidence ; Lipoproteins ; Machine Learning ; Mass Screening ; Methods ; Support Vector Machine ; Triglycerides

BACKGROUND: Glycosylated hemoglobin (HbA1c) has been recommended as a diagnostic test for prediabetes and diabetes. Here, we evaluated the level of agreement between diagnoses based on fasting plasma glucose (FPG) versus HbA1c levels and determined optimal HbA1c cutoff values for these diseases in youth and young adults. METHODS: The study included 7,332 subjects (n=4,129, aged 10 to 19 years in youth group; and n=3,203 aged 20 to 29 years in young adult group) from the 2011 to 2016 Korea National Health and Nutrition Examination Survey. Prediabetes and diabetes were defined as 100 to 125 mg/dL (impaired fasting glucose [IFG]) and ≥126 mg/dL for FPG (diabetes mellitus [DM] by FPG [DMFPG]), and 5.7% to 6.4% and ≥6.5% for HbA1c, respectively. RESULTS: In the youth group, 32.5% with IFG had an HbA1c level of 5.7% to 6.4%, and 72.2% with DMFPG had an HbA1c ≥6.5%. In the young adult group, 27.5% with IFG had an HbA1c level of 5.7% to 6.4%, and 66.6% with DMFPG had an HbA1c ≥6.5%. Kappa coefficients for agreement between the FPG and HbA1c results were 0.12 for the youth group and 0.19 for the young adult group. In receiver operating characteristic curve analysis, the optimal HbA1c cutoff for IFG and DMFPG were 5.6% and 5.9% in youths and 5.5% and 5.8% in young adults, respectively. CONCLUSION: Usefulness of HbA1c for diagnosis of IFG and DMFPG in Koreans aged <30 years remains to be determined due to discrepancies between the results of glucose- and HbA1c-based tests. Additional testing might be warranted at lower HbA1c levels to detect IFG and DMFPG in this age group.
Adolescent ; Blood Glucose ; Diabetes Mellitus ; Diagnosis ; Diagnostic Tests, Routine ; Fasting ; Glucose ; Hemoglobin A, Glycosylated ; Humans ; Korea ; Nutrition Surveys ; Plasma ; Prediabetic State ; ROC Curve ; Young Adult

In recent years, reports of diabetes mellitus (DM) cases that do not fit the traditional classification system have increased in prevalence. While insulin deficiency appears as type 1 DM (T1DM), the new type also has the clinical features of type 2 DM (T2DM); as such, this new type of DM is called ketosis-prone diabetes (KPD) and is correlated with findings of severe hyperglycemia and ketoacidosis. To provide a clear, clinical classification of DM, new classification systems are being studied. Among these, the Aβ system demonstrates the highest sensitivity and specificity in predicting clinical features and prognosis. We report 2 cases of KPD in Korean pediatric patients. The first patient was referred while in a state of diabetic ketoacidosis (DKA) and was considered to have T1DM. However, their blood glucose was well-controlled even with small doses of insulin, and the treatment was able to be changed to metformin therapy. The second patient seemed to be a typical case of T2DM because of his obesity and strong family history. However, blood glucose was not well-controlled with a regular diet, and ketosis occurred. After performing a glucagon stimulation test, both patients showed different clinical features that were finally diagnosed as type A-β+ KPD. The rapid and accurate diagnosis of KPD can reduce the duration of inappropriate insulin use and improve patients' quality of life. Further, the treatment of KPD children should be individualized according to each patient's lifestyle to preventing recurrent DKA.
Adolescent ; Blood Glucose ; Child ; Classification ; Diabetes Mellitus ; Diabetes Mellitus, Type 1 ; Diabetic Ketoacidosis ; Diagnosis ; Diet ; Glucagon ; Humans ; Hyperglycemia ; Insulin ; Ketosis ; Life Style ; Metformin ; Obesity ; Prevalence ; Prognosis ; Quality of Life ; Sensitivity and Specificity

OBJECTIVES: This study analyzed Korea National Health and Nutrition Examination Survey data from 2007 to 2017 to assess trends in the prevalence, treatment, and control of diabetes in Korean adults ≥30 years of age.METHODS: Prevalent diabetes was defined as a fasting plasma glucose level ≥126 mg/dL, self-reported use of anti-diabetic treatment (insulin or oral anti-diabetic drugs), or diabetes diagnosis by a physician. Target levels were defined as glycosylated hemoglobin <6.5% or <7.0%, blood pressure <130/80 mmHg, and total cholesterol <200 mg/dL. All survey waves were age-standardized to the 2005 Korean census population.RESULTS: Diabetes prevalence increased from 9.6% in 2007–2009 to 10.8% in 2016-2017 (p<0.001). Impaired fasting glucose prevalence significantly increased in both genders and almost every age group. Diabetes awareness and glycemic control did not show an increasing trend; however, the treatment rate and proportion of people diagnosed with diabetes achieving target blood pressure and total cholesterol levels improved from 57.2% to 63.5% (p=0.008), from 41.1% to 53.2% (p<0.001), and from 65.0% to 78.0% (p<0.001), respectively.CONCLUSIONS: From 2007 to 2017, the prevalence of diabetes increased moderately in Korea, whereas the diabetes treatment rate and the proportion of people diagnosed with diabetes achieving target blood pressure and total cholesterol levels improved. However, awareness of diabetes and glycemic control require significant improvements. A national-level action plan is required to raise awareness about diabetes and prediabetes, with the goal of improving glycemic control and minimizing the occurrence of adverse health outcomes.
Adult ; Blood Glucose ; Blood Pressure ; Censuses ; Cholesterol ; Diabetes Mellitus ; Diagnosis ; Fasting ; Glucose ; Hemoglobin A, Glycosylated ; Humans ; Korea ; Nutrition Surveys ; Prediabetic State ; Prevalence

BACKGROUND: Previous studies have reported that fasting insulin and blood glucose levels are higher in postmenopausal than in premenopausal women and that insulin resistance was more serious in postmenopausal women. The effects of menopause on glucose metabolism have been well studied, but it is unclear whether age at menopause onset is associated with fasting blood sugar and HbA1c levels. The purpose of this study is to determine the effect of menopause age on diabetes and prediabetes.METHODS: We retrospectively analyzed data from the Sixth Korea National Health and Nutrition Examination Survey (2013–2015). The participants were 2,156 naturally menopausal women, except diabetes, stroke, coronary artery disease and cancer patients. The study population was divided into four groups according to the age of natural menopause onset ( < 40, 40–44, 45–55, and ≥56 years). Diagnosis of diabetes and prediabetes was based on the American Diabetes Association guideline. The association between menopause age and diabetes or prediabetes was analyzed by multiple logistic regression.RESULTS: Women reaching menopause at 40–44 years were 4.901 times more likely to have diabetes (odds ratio [OR], 4.901; 95% confidence interval [95% CI], 1.353–17.756, P=0.016) than those who reached menopause at an age of ≥56 years. Women with menopause at age < 40 years were 2.839 times more likely to have diabetes or prediabetes (OR, 2.839; 95% CI, 1.012–7.968, P=0.047).CONCLUSION: Women with premature menopause (< 40 years) have high risk of developing diabetes or prediabetes, and women with a menopause age of 40–44 years have high risk of developing diabetes.
Blood Glucose ; Coronary Artery Disease ; Diabetes Mellitus ; Diagnosis ; Fasting ; Female ; Glucose ; Humans ; Insulin ; Insulin Resistance ; Korea ; Logistic Models ; Menopause ; Menopause, Premature ; Metabolism ; Nutrition Surveys ; Prediabetic State ; Retrospective Studies ; Stroke