Volume 12 · Issue 05 · 2020

Only by refining the clinical application of basal insulin can more patients finally benefit, and the guidance and recommendations for the clinical application of basal insulin-thirty-three questions came into being. It aims to guide the clinical standardization of basal insulin, improve the overall blood glucose compliance rate of diabetes treatment in China, reduce the risk of hypoglycemia, and improve the prognosis of patients.

"Pre-diabetes" refers to people whose blood sugar levels are high but have not yet reached the diagnostic criteria for diabetes identified by epidemiological studies. The risk of developing diabetes or cardiovascular disease in this population is significantly increased compared with those with normal blood sugar. The prediabetic population includes people with impaired fasting blood glucose (IFG) and impaired glucose tolerance (IGT). In recent decades, although a large number of diabetes-related prevention studies have been carried out, and most diabetes prevention studies have confirmed that different interventions can reduce the risk of type 2 diabetes, this conclusion has only been widely verified in IGT populations and has not yet been verified in IFG alone. Sufficient evidence has been obtained in the population. However, whether the risk of microvascular and macrovascular complications can be reduced by certain intervention measures in prediabetic people is not yet conclusive, and it is even less known in people with simple fasting blood glucose impairment. Therefore, there is currently no sufficient clinical evidence to prove that intervention in people with simple fasting blood glucose impairment can bring improvement of metabolic indicators and long-term benefits in microvascular and macrovascular complications.

In view of the problems that Chinese clinicians may encounter in using basal insulin that is currently on the market in China, and the current situation that the compliance rate of diabetic patients treated with basal insulin in China needs to be improved, this edition of basal insulin clinical application guidance and suggestions-thirty-three questions are specially written, and the common problems in the clinical application of basal insulin are interpreted in the form of questions and answers, aiming at guiding the clinical standardization of basal insulin, improving the overall blood glucose compliance rate of diabetes treatment in China, reducing the risk of hypoglycemia, and improving the prognosis of patients.

To investigate the relationship of hemoglobin level with type 2 diabetes in middle-aged and elderly population in Shanghai Chongming District.

A populational-based array research with multiple stage stratified cluster and random sampling was performed to study 7 534 residents from a community in Shanghai Chongming District. The standardized questionnaires, physical examinations and related laboratory tests were undertaken. The hemoglobin concentration was determined by cyanmethemoglobin spectrophotometry. The participants were divided into non-diabetic group, newly diagnosed diabetic group and previously diagnosed diabetic group according to the 1999 WHO diagnostic criteria and medical history; the participants were also divided into non-anemia group and anemia group according to the 1999 WHO anemia diagnostic criteria. Binary logistic regression models were used to estimate the odds ratios (ORs) and confidence intervals (CIs) for diabetes mellitus for every quartile of hemoglobin compared to the lowest quartile. Spearman correlation analysis was used to estimate the association of all related metabolic parameters with hemoglobin.

The prevalence of anemia in the non-diabetic group [275 (4.9%)] was higher than that in the newly diagnosed diabetic group and the previously diagnosed diabetic group [23 (1.9%) and 22 (2.9%)] (P<0.01). The prevalence of anemia in the previously diagnosed diabetic group was higher than that in the newly diagnosed diabetic group (P<0.01). Hemoglobin levels were positively correlated with waist（r=0.257）, hip（r=0.155）, BMI（r=0.141）, FPG（r=0.232）, 2 h PG（r=0.140）, HbA_1C（r=0.028）, insulin（r=0.036）, HOMA-IR（r=0.102）, LDL-C（r=0.056）, TC（r=0.054） and TG（r=0.202）(P<0.05). Non-diabetic people at baseline were quartile according to hemoglobin level. At follow-up, the incidence of diabetes, fasting blood glucose and 2 h plasma glucose after glucose loading were higher in the highest hemoglobin quartile population than the lowest quartile population. After adjusting for other influencing factors, binary logistic regression analysis showed that the highest quartile hemoglobin was associated with increased risk of T2DM, with a fully adjusted odds ratio (OR) of 1.415 (95% confidence interval (CI), 1.087 to 1.841, P<0.01).

There is a significant positive correlation between hemoglobin and the incidence of diabetes. Increased level of hemoglobin level is an independent risk factor and potential predictor for incidence of type 2 diabetes in middle-aged elderly population in this study.

To explore the feasibility of simplifying the calculation of renal threshold for glucose excretion (RT_G) by calculating the mean blood glucose (MBG) with venous glycated hemoglobin A_1c(HbA_1c) and fingertip blood glucose spectrum.

A total of 168 hospitalized patients with type 2 diabetes mellitus (T2DM) who were admitted to Tianjin Medical University Chu Hsien-I Memorial Hospital from January 2018 to January 2019 were selected by stratified random sampling method. We estimated the glomerular filtration rate (eGFR) and detected the 24-hour urine sugar, the continuous glucose monitoring (CGM), finger glucose performed 8 times a day and HbA_1c to reflect the MBG level, which were used to calculate RT_G. Pearson correlation analysis was used to analyze the correlation of three RT_G, and multiple linear regression equation was used to establish the mathematical model of RT_G calculated by HbA_1c and fingertip blood glucose. A total of 450 patients with T2DM were reenrolled as the verification population of the new mathematical model. Homser and Lemeshow tests were used to verify the consistency of three RT_Gcalculated by fingertip blood glucose, HbA_1cand dynamic glucose monitoring.

There was strong correlation between RT_Gusing three different methods to calculate RT_Gwith the mean blood glucose (P<0.01); for fingertip blood glucose profile, the multiple linear regression equation was RT_G=-24.572+18.385×fingertip MBG (mg/dl)+0.211×eGFR ［ml·min^-1·(1.73 m²)^-1］-0.914×24 h GLU (g/24 h), and for HbA_1c, the equation was: RT_G=-52.334+28.359×HbA_1c(%)+0.189×eGFR ［ml·min^-1·(1.73 m²)^-1］-0.616×24 h GLU(g/24 h). Homser and Lemeshow test showed a high degree of fitting between the predicted value of those mathematical models with the observed value, and the data distribution was consistent (χ²₂=9.809, P₂=0.679; χ²₃=6.832, P₃=0.555). According to receiver operating characteristic (ROC) curve, the area under curve (AUC) of RT_G calculated by HbA_1c was 0.744 (P<0.01), and the AUC of RT_G calculated by fingertip blood glucose was 0.892 (P<0.01), the sensitivity of diagnosis was 65.53%, the specificity was 90.95%, and the Yoden index was 0.663. Multivariate logistic regression model showed that age, duration of diabetes, body mass index (BMI) and kidney volume were associated with RT_G independently (OR 1.038-2.849, all P<0.05), and further stratification showed that RT_G of T2DM patients increased with age, the course of disease, BMI, and kidney volume.

There are strong association between the three methods to calculate renal threshold for glucose excretion. Using fingertip blood glucose and HbA_1c to calculate RT_G are simple and clinically convenient. The risk factors of high RT_G are age, duration of diabetes, BMI and kidney volume.

To explore the risk of necrotizing fasciitis (NF) in patients with diabetic foot (DF) and decide whether to have a emergency surgery.

A retrospective analysis of 109 DF patients who were admitted to the First Affiliated Hospital of Chongqing Medical University from October 2013 to December 2015 was divided into DF group (93 cases) and DF with necrotizing fasciitis group (DNF, 16 cases). Clinical data of the two groups were compared, the significant difference variables such as white blood cell, glycosylated hemoglobin，albumin, and the related variables with NF, such as glycated hemoglobin A_1c, red cell distribution width, C-reactive protein reported in previous studies were converted into categorical variables. The multivariable logistic regression analysis and regression coefficients curves were used to constructed the risk assessment of DF with NF (RADNF) score. This model was validated in a cohort of 97 diabetic foot patients from January to December in 2016.

The hypersensitive C-reactive protein>20 mg/L, glycosylated hemoglobin A_1c≥11% and temperature≥38.0 ℃ were independent risk factors for NF (OR=18.450, 20.103, 5.539, P<0.01 or P<0.05). The AUC of the RADNF score was 0.864 (95%CI 0.785-0.943) in the developmental cohort, and the best cut off value for RADNF to identify NF was 4 points in diabetic foot population with sensitivity of 87.5% and specificity of 76.3%. Model performance was very good with sensitivity of 86.70% and specificity of 80.50% in validation cohort (Hosmer-Lemeshow goodness-of-fit test, P=0.939).

The RADNF score can be used to assess the risk of the necrotizing fasciitis in diabetic foot patients effectively. An emergency surgery should be considered once the RADNF score above 4 points.

To investigate the relationship between serum thyrotropin （TSH) and glycated hemoglobin A_1c (HbA_1c) in non-diabetic patients.

From May to October 2011, 10 140 permanent residents aged over 40 years old were sampled by cluster sampling method in yunyan district of guiyang city, and 5 819 residents were eventually included. All the subjects were investigated by detailed epidemiological questionnaire, and the basic data were collected to measure body mass index (BMI), waist circumference, blood pressure, blood glucose, blood lipid, insulin, glycosylated hemoglobin and thyrotropin. Non parameter test t test, and logistic regression analysis were used.

According to TSH level, the population was divided into the normal TSH group and the elevated TSH group. Compared with the normal TSH group, the HbA_1c value of the elevated TSH group was lower (P<0.05)，while the BMI, fasting insulin (FINS), homesostasis model assessment of insulin resistance (HOMA-IR), triglyceride (TG), low-density lipoprotein-cholesterol （LDL-C） and total cholesterol were higher , with statistically significant differences (P<0.05).After adjusting for age, systolic pressure, diastolic pressure, BMI, waist circumference, FPG, OGTT 2 h blood glucose, FINS, HOMA-IR, TG, HbA_1c,LDL-C , logistic regression analysis results showed that compared with the normal TSH group, the elevated TSH group was the factor affecting HbA_1c. TSH was negatively correlated with HbA_1c (OR=0.845, P=0.024, 95%CI=0.730 to 0.978).After further gender stratification, the negative correlation between TSH and HbA_1c was found only in males (OR=0.672, P=0.034, 95%CI=0.466 to 0.970), but not in females.

In non-diabetic population, increased TSH may reduce the level of HbA_1c. Serum TSH in male non-diabetic population is negatively correlated with HbA_1c, while serum TSH in female non-diabetic population is not significantly correlated with HbA_1c.

To retrospectively analyze the clinical data of one child with hepatocyte nuclear factor 4 alpha hyperinsulinism (HNF4α-HI), and further deepen the understanding of HNF4α-HI.

This patient with HNF4α-HI confirmed by genetic analysis was selected from February 2008 to December 2018 in Beijing Children's Hospital of Capital Medical University. The clinical data, treatment and the follow-up data of the patient was retrospectively analyzed.

The patient with HNF4α-HI was born with giant children, and his onset age was 1 day after birth. He was responsive to diazoxide treatment, carrying HNF4α gene c.157T>C (p.C53R) mutation, which was a novo mutation and pathogenic after comprehensive analysis of American College of Medical Genetics and Genomics standards. He can achieved spontaneous remission at 2 years old and the development of mental strength is the same as that of the same age now.

Children with HNF4α-HI are mostly born as giant children and have early onset age. Most of the children are responsive to diazoxide and some patients can achieve spontaneous remission with age. Because this type of children have the possibility of developing diabetes in adolescence or early adulthood, diabetes screening should be performed annually after the age of 10.

Tumor immunotherapy is developing rapidly, and programmed cell death protein 1 (PD-1) antibody is being used more and more widely as a new immunotherapy drug, and its immune-related adverse reactions, including endocrine-related adverse reactions, are gradually appearing. The authors report a 52-year-old female patient with lung adenocarcinoma after treatment with PD-1 antibody for 8 courses (16 weeks) developed fasting blood glucose impairment and diabetic ketoacidosis rapidly in a short time. The glycosylated hemoglobin was 8.1%, and the C peptide was both fasting and post-load<3.33 pmol/L, DM-related islet autoantibodies were all negative, and HLA gene detection indicated DRB1^*03:03 is the susceptible genotype. The patient was discharged after receiving routine intravenous fluid rehydration and subsequent intensive insulin therapy. After 16 months of follow-up, the patient's pancreatic islet β cell function was still in a state of exhaustion, and the blood glucose fluctuated greatly. This case suggests that PD-1 antibody treatment may induce the development of fulminant type 1 diabetes, especially in patients with susceptible HLA genotypes. It is hoped that this article will arouse widespread attention of endocrinologists and oncologists, and pay attention to blood sugar monitoring when applying these drugs, so as to discover and avoid serious complications such as diabetic ketoacidosis in time.

Subcutaneous insulin resistance (SIR) is a rare but neglected clinical syndrome in which patients have severe resistance to subcutaneous insulin and normal sensitivity to intravenous insulin. The mechanism of SIR is not fully understood, and accelerated subcutaneous degradation of insulin or localized insulin-derived amyloidosis may be one of the potential mechanisms. The therapeutic methods reported in the literature include the use of protease inhibitors, continuous intravenous or intraperitoneal insulin infusion, and inhaled insulin, but the efficacy is different, suggesting that the pathophysiological mechanism of SIR is complex.

Gastric emptying and intestinal hormones have important regulatory effects on postprandial blood glucose balance. Excessive gastric emptying rate can easily lead to postprandial blood glucose fluctuations, and may cause impaired glucose tolerance and even diabetes. Inhibiting gastric emptying can delay the absorption of glucose in food and reduce the peak postprandial blood glucose, thus contributing to postprandial blood glucose management in diabetic patients. The author will review the recent progress of gastric emptying research, emphasizing on the prediction of abnormal blood glucose metabolism by gastric emptying rate variation and its significance in reducing postprandial blood glucose.

Islet beta cells play an important role in blood glucose sensing and regulation of homeostasis. Studies have shown that there are heterogeneity in pancreatic development, islet structure, cell morphology and function, and molecular markers among different beta cells of the same species and different individuals, among different islets of the same individual, and even within the same islet. Beta cell heterogeneity may be one of the potential mechanisms by which it can effectively respond to various physiological and pathological changes. Fully understanding beta cell heterogeneity will help to understand the pathogenesis of diabetes and provide new ideas for diabetes treatment.

Intestinal flora is closely related to the energy metabolism process of the host, and its composition and metabolic disorders can lead to insulin resistance, obesity and type 2 diabetes. Hypoglycemic drugs can regulate the composition and metabolism of intestinal flora, improve the intestinal environment, thereby reducing insulin resistance and improving host metabolism, and finally exert a hypoglycemic effect.

With the accumulation of massive multi-dimensional biomedical data, including genome, metabolome, lipidome, microbiome, electronic medical records, medical imaging and wearable device data, and multi-modal artificial intelligence (AI) model algorithms including deep learning, breakthroughs have made it possible to explore accurate classification and treatment of diabetes. By reviewing the progress made by applying traditional AI algorithms in the classification of type 2 diabetes, and drawing on the successful experience of multimodal AI models in other fields of precision medicine, this paper looks forward to the prospect of applying multimodal AI models to integrate multi-dimensional data in the accurate classification of type 2 diabetes.