Volume 12 · Issue 07 · 2020

Gestational diabetes mellitus (GDM) is the most common type of hyperglycemia during pregnancy and has a significant clinical "transgenerational effect". The author focuses on the history and research status of GDM, and looks forward to the future, from the aspects of diagnostic criteria, the far-reaching impact of GDM on mother and child, treatment during pregnancy, earlier identification of high-risk groups and exploration of pathogenesis, etc., hoping to deepen the understanding of GDM, and achieve the goal of reducing the prevalence of GDM, reducing perinatal adverse outcomes, reducing the outcome rate of postpartum T2DM, and cutting off the "cross-generational effect" in the future.

Under normal pregnancy, in order to ensure the energy in the main form of glucose needed for fetal growth and development, physiological insulin resistance will occur in the mother, and at the same time, islet β cells compensatingly increase insulin secretion to maintain normal blood sugar. When insulin resistance is excessive and (or) β cell compensation is insufficient, gestational diabetes mellitus (GDM) occurs. Obesity is the strongest predictor of insulin resistance and GDM during pregnancy. Factors such as polycystic ovary syndrome, intestinal flora imbalance, heredity and aging also increase its risk. We should also pay attention to the impact of early life experience on one's metabolic state and this pregnancy. Identifying the heterogeneity of GDM pathogenesis is helpful for understanding GDM, guiding treatment and even judging prognosis.

The epidemic of type 2 diabetes and its complications has caused a great burden on the disease management system in our country. The lag defect inherent in the traditional upgrade treatment management model affects patients to obtain the maximum benefit from treatment. Recent advances in this field have prompted us to reconsider strategies for the prevention and treatment of type 2 diabetes. The prevention and treatment of type 2 diabetes should be guided by reducing cardiovascular complications and attaching importance to the reversibility of early disease; In terms of strategy, we should pay attention to the combined compliance of early comprehensive risk factors to effectively reduce the residual cardiovascular risk. At the same time, we must grasp the time window of early intensive treatment to achieve disease reversal, and fundamentally delay the progression of disease and complications; In terms of specific means, we should combine the latest clinical results and the actual situation to select therapeutic drugs with macrovascular and microvascular benefits, so as to achieve the comprehensive diabetes prevention and treatment goals in the Healthy China 2030 Plan Outline with a more active and positive attitude.

Nonalcoholic fatty liver disease (NAFLD) refers to the excessive deposition of intrahepatic fat caused by excessive drinking and other clear liver damage factors. Patients with this disease are often complicated with obesity, metabolic syndrome, type 2 diabetes, cardiovascular and cerebrovascular diseases and other systemic metabolic abnormalities. At present, NAFLD has become the leading cause of chronic liver disease globally, significantly increasing the disease and medical burden of the population. Although there have been more than 300 clinical research projects for NAFLD so far, no drug has been officially approved for the clinical treatment of NAFLD. The high heterogeneity of the etiology of NAFLD determines that there are huge differences in the response of patients with fatty liver caused by different pathogenic factors to drug treatment. If the pathogenic factors of NAFLD are not accurately distinguished, NAFLD intervention drugs can only reach 20% ~30% at most. Therefore, the current diagnostic and classification criteria of NAFLD have been unable to effectively guide the clinical treatment of fatty liver. In this context, internationally renowned liver disease expert groups jointly initiated to modify the naming and diagnostic criteria of NAFLD diseases that have been used since 1980, and replace them with metabolic-related fatty liver disease (MAFLD). The new MAFLD designation highlights the central role of metabolic factors in causing liver fat deposition in this type of liver disease, and for the first time raises the clinical importance of metabolic factors causing liver lesions to the same level as other chronic liver diseases such as viral hepatitis and alcoholic liver disease. This naming change will help promote the etiology-based classification system of fatty liver, and ultimately play an active role in guiding individual precision treatment of fatty liver. The author will discuss in detail the reasons and clinical significance of the change of NAFLD to MAFLD naming, and look forward to the changes in the individualized diagnosis and treatment of fatty liver that may be brought by the new MAFLD naming.

Diabetic foot ulcer has an important impact on the health status and quality of life of patients. Understanding the relationship between diabetic foot ulcer and psychosociology plays an important role in promoting the healing of diabetic foot ulcer, avoiding recurrence and improving the quality of life of patients.

To explore the correlation between different gestational seasons and blood fasting blood glucose (FBG) levels in the three trimesters during pregnancy.

Five hundred and fourty two healthy women in early pregnancy were included from the First Affiliated Hospital of China Medical University and General Hospital of Northern Theater Command. Participants were divided into spring group (n=85), summer group (n=55), autumn group (n=203) and winter group (n=199) according to the last menstrual period. FBG level was prospectively monitored during the three trimesters of pregnancy. Statistical analysis was performed by chi-square test, Mann-Whitney U test, Kruskal-Wallis test, paired Friedman nonparametric test and binary logistic regression.

FBG levels in the whole three trimesters of pregnancy were highest in the summer group, followed by spring group, and FBG levels in the autumn and winter groups were significantly lower than the former two groups (P<0.05). Also, among the autumn and winter groups, the percentage of women with FBG≥5.1 mmol/L were significantly lower, and the percentage of women with FBG<4.4 mmol/L were also markedly higher than the former two groups(P<0.05). Binary logistic regression analysis showed that as compared with those who got pregnant in winter, pregnancy in summer was an independent risk factor for FBG levels≥5.1 mmol/L in the second and third trimesters; and that in both spring and summer were also independent risk factors for FBG level≥4.4 mmol/L (indicating high risk of developing GDM) while pregnancy in autumn wasn′t an independent risk factor for increasing FBG level in the second trimester.

Among the healthy women before pregnancy, those who get pregnant in the autumn and winter may have lower FBG levels during the three trimesters than in the spring and summer. The former women may have a decreased risk of developing GDM.

To explore the predictive values of early pregnancy fasting plasma glucose (FPG), lipid profiles and blood pressure, and establish prediction models for gestational diabetes mellitus (GDM) of different pre-pregnancy body mass index (p-BMI) ranges.

This is a prospective case-control study. From September 2017 to June 2018, 1 471 singleton pregnant women in our hospital were prospectively enrolled. We chose women with intact data of p-BMI, early pregnancy blood pressure, FPG and lipid profiles as objectives. According to the International Diabetes and Pregnancy Study Group (IADPSG) criteria, 222 women diagnosed with GDM, and 420 women diagnosed with normal glucose tolerance (NGT) were enrolled into case-control study. The relevant data were collected. Objectives were divided into normal weight group and overweight/obese group basing on p-BMI, then logistic regression was used to establish GDM prediction models, and ROC was used to analyze the predictive values.

(1) Compared with the NGT group, the GDM group were older at gestation, had higher proportions of diabetes mellitus (DM) family history, and GDM history. Pre-pregnancy weight, BMI, early pregnancy systolic and diastolic blood pressure (SBP and DBP), FPG, triglycerides (TG), total cholesterol (TCHO), and low-density lipoprotein cholesterol (LDL-C) of the GDM group were all significantly higher. Seventy five g OGTT FPG, 1 hour plasma glucose (1 hPG), 2 hour plasma glucose (2 hPG) during middle pregnancy were also significantly higher in the GDM group (P<0.05). (2) The age at gestation higher than 31.2 years, early pregnancy FPG higher than 5.42 mmol/L, TG higher than 1.00 mmol/L, LDL-C higher than 2.49 mmol/L, DBP higher than 72.5 mmHg (1 mmHg=0.133 kPa) and DM family history were independent predictors of GDM. (3) For pre-pregnancy normal weight women, GDM can be predicted using age at gestation, early pregnancy FPG and DBP. For pre-pregnancy overweight/obese women, besides early pregnancy FPG and DBP, TG, times of pregnancy and DM family history were all independent predictors. The predictive value of TG was higher than that of FPG or DBP (area under curve were 0.718,0.640 and 0.648). The prediction model combining above independent predictors had improved predictive value (area under curve was 0.793).

While GDM was diagnosed during middle or late pregnancy, higher levels of FPG, TG, LDL-C and DBP have emerged during early pregnancy. Women with different p-BMI have different predictive indicators in early pregnancy. Age at gestation, FPG and DBP were independent predictors for normal-weight women. For pre-pregnancy overweight/obese women, besides early pregnancy FPG and DBP, TG, times of pregnancy and DM family history were all independent predictors. The predictive value of TG was higher than that of FPG or DBP. The prediction model combining above independent predictors had improved predictive value.

To explore the relationship between serum serine protease inhibitor B1 (SerpinB1) and the risk of gestational diabetes mellitus (GDM).

A total of 328 pregnant women who were checked up in the clinic of Shengjing Hospital of China Medical University from 2016 to 2018 were divided into two groups according to GDM diagnostic criteria: normal (NC) group (n=155) and GDM group (n=173). The correlations between serum SerpinB1 level and glucose and lipid metabolism indexes were analyzed in 5-12 weeks, 13-23 weeks, 24-28 weeks and 29-37 weeks of pregnancy. The pregnant women who did not have GDM at 5-12 weeks of gestation but diagnosed GDM after 24 weeks of pregnancy were selected as GDM-A group (n=18). The pregnant women who did not have GDM at 13-23 weeks of gestation but diagnosed GDM after 24 weeks of pregnancy were selected as GDM-B group (n=26). Logistic regression was used to analyze the risk factors of GDM during pregnancy. Receiver operating characteristic (ROC) curve predicted the cut-off value of serum SerpinB1 levels affecting the occurrence of GDM after 24 weeks of pregnancy.

In the GDM group, the serum SerpinB1 level at 5-12 weeks gestation, 13-23 weeks gestation, 24-28 weeks gestation of pregnancy was significantly higher than that in the NC group (P<0.05). At 24-28 weeks of gestation, the level of serum SerpinB1 was positively correlated with LDL-C（r=0.786, P<0.05） and negatively correlated with fasting insulin and HOMA-IR(r=-0.724 and -0.680 respectively, P<0.05). After correcting the confounding factors such as gestational age, pre-pregnant BMI, acanthosis nigricans and triglycerides, etc, serum SerpinB1 level at 13-23 weeks gestation was still an independent risk factor for GDM after 24 weeks of pregnancy (OR=1.573, 95%CI was 1.035 to 2.228,P<0.05). The area under the ROC curve of GDM was 0.631 (P<0.05).

Elevated serum SerpinB1 levels at 13-23 weeks of pregnancy is related to the risk of GDM occurrence after 24 weeks of pregnancy, which may be a serological marker before the occurrence of GDM.

To explore effects of gestational weight gain (GWG) and gestational diabetes mellitus (GDM) on the accuracy of sonographically estimated neonatal weight near delivery.

A total of 1 404 cases of pregnant women in Beijing Hospital from September 2016 to November 2017 were include in retrospective analysis. Trimester-specific gestational weight gain, oral glucose tolerance test, birth weight and estimated neonatal weight at 1-week before delivery were collected. The patients were classified into inadequate GWG (279 cases), normal GWG (570 cases) and excessive GWG (555 cases). ANOVA and logistic regression analysis were used to compare the weight estimation errors of fetal body weight and the prediction of macrosomia by B-ultrasound between different groups, and to analyze the effect of total GWG and GDM on the accuracy of sonographically estimated neonatal weight.

The total GWG effected actual error of birth weight and estimated neonatal weight, the actual error of B-ultrasound prediction of birth weight in the inadequate GWG group was lower than that in the normal group ［(-19.3±238.0) vs (52.5±255.5) g, P<0.05］, and the actual error in the excessive GWG group was higher than that in the normal group ［(84.1±269.2) vs (52.5±255.5) g,P<0.05］. But it had no significant effect on the accuracy of sonographic estimations of neonatal weight. GDM had little effect on the actual error and absolute error, but it increased the risk of inaccurate estimations of neonatal weight (odds ratio 1.483, 95% confidence interval 1.101-1.998). There was no significant difference in the sensitivity, specificity of the prediction of macrosomia among the total GWG and GDM groups.

The total GWG during pregnancy and GDM may effect the accuracy of sonographically estimated neonatal weight to a certain extent. Neither GWG nor GDM has effect on the sensitivity, specificity of the prediction of macrosomia.

To explore the normal reference interval of saliva 1, 5-anhydroglucitol (1, 5-AG) in Chinese population, and to give evidence for clinical application of the noninvasive examination method.

A total of 224 subjects with normal glucose tolerance (aged 20-69, 59 male and 165 female) were enrolled in Shanghai Jiao Tong University Affiliated Sixth People′s Hospital from September 2018 to June 2019 and chewed the cottons in the Salivette tubes 40-50 times for 1 minute to collect saliva. Saliva 1, 5-AG levels were measured using liquid chromatography-mass spectrometry (LC-MS) and serum 1, 5-AG levels were measured with enzymatic method. The independent sample t test, analysis of variance, Wilcoxon rank sum test and Kruskal-Wallis test were used for the inter-group comparison. Spearman correlation analysis and multiple linear regression were used to study the relationship between saliva 1, 5-AG and other indicators.

(1) The average level of saliva 1, 5-AG in 224 normal subjects was 0.53 (0.35-0.77) mg/L, and there was no gender difference in saliva 1, 5-AG levels (P=0.118). (2) According to age the subjects were divided into three subgroups: 20-29 years, 30-49 years and 50-69 years. There were no significant differences in saliva 1, 5-AG levels among three age subgroups in both male and female (all P>0.05). (3) According to body mass index (BMI) the subjects were divided into three subgroups: 18.5-20.9 kg/m², 21.0-22.9 kg/m² and 23.0-24.9 kg/m². There were no significant differences in saliva 1, 5-AG levels among three BMI subgroups in both male and female (all P>0.05). (4) The normal reference interval of saliva 1, 5-AG (the 2.5-97.5 percentiles) was 0.09-1.63 mg/L, serum 1, 5-AG was the only independent factor associated with saliva 1, 5-AG (standardized β=0.279,t=3.636, P<0.01).

Based on LC-MS determination method the normal reference interval of saliva 1, 5-AG was 0.09-1.63 mg/L. Saliva 1, 5-AG is not affected by gender, age and BMI and is noninvasive, convenient and robust for clinical application and may become another complementary tool for blood glucose monitoring in diabetes.

To explore the effects of individualized nutrition training on weight loss and weight maintenance in patients with simple obesity.

Of 100 simple obese patients from the obesity clinic of Endocrinology and Metabolism Department between Jan. 2015 and Dec. 2016, 12 patients dropped out halfway and 88 patients were recruited and randomly divided into 2 groups: the individualized nutrition training (INT) group (n=48) and the conventional nutrition intervention (CNI) group (n=40). The therapeutic process included intervention, transition and maintenance period. Under the guidance of a specialist physician, a registered nutritionist and a nurse, each patient received treatment including 3 month intervention period (a low-calorie, low-carbohydrate diet: daily calories<1 200 kcal, carbohydrate 20% to 30%, protein 30% to 35%, fat 35% to 40%), followed by 1 month transition period and 12 month maintenance period (a balanced diet: daily calories ≤25 kcal/kg, carbohydrates 55% to 60%, protein 15% to 20%, fat≤30%). In CNI group nutrition prescriptions were provided by the nutritionist, nutrition education and monthly follow-up were completed by the nurse, and the safety was monitored by the physician. In INT group during intervention period, the nutritionist gave individualized nutrition training covering 3 meals daily by Wechat. Additionally, the advices for exercise intensity, dietary requirements and follow-up frequency were consistent in these two groups. The scores of dietary behavior and the weight rates of reaching the standard at different time points were compared between these two groups. Fisher exact probability method,t test and Spearman method were used for statistical analysis.

No differences was found in the initial dietary behavior scores between these two groups (3.92±1.13 and 3.88±0.97, P>0.05). After intervention, the dietary behavior scores in INT group increased significantly than those in CNI group at the beginning of the maintenance period (7.81±0.67 and 7.13±1.22,P<0.01) and at the end of the maintenance period (7.00±1.11 and 4.68±1.10,P<0.01); The weight loss percentage of the patients in INT group increased significantly than those in the CNI group at the end of the intervention period (15.0% and 9.2%,P<0.01), at the beginning of the maintenance period (14.2% and 8.4%,P<0.01) and at the end of the maintenance period (11.3% and 2.6%,P<0.01).The weight loss percentage over 5% in INT group was more than those in CNI group at the end of the maintenance period (91.7%vs 20.0%, P<0.01).

Individualized nutrition training may help patients with simple obesity lose more weight and prevent weight rebound.

To investigate the characteristics and associated factors of islet beta cell function (evaluated by C-peptide) changing with the disease duration in patients with type 2 diabetes mellitus (T2DM).

Data were collected in 1 570 hospitalized T2DM patients ［970 males and 600 females, with a mean age of (58±12) years (12 to 88 years) and diabetes duration of (8.3±7.2)years (3 d to 34 years)］ from the Department of Endocrinology, the First Affiliated Hospital of Nanjing Medical University between November, 2014 and May, 2018. According to the diabetes duration, all patients were divided into 4 groups: diabetes duration ≤ 1 year group (n=340), 1 year<diabetes duration ≤ 5 years group (n=325), 5 years<diabetes duration ≤ 15 years group (n=650) and diabetes duration>15 years group (n=255). C-peptide release index (CRI) was compared and analyzed among different groups by ANOVA. On the basis of diabetes duration grouping, CRI levels were compared by independent sample t test between subgroups grouped using the median levels of glycosylated hemoglobin A_1c (HbA_1c) and 25-hydroxyvitamin D ［25(OH)D］. The major associated factors of CRI were analyzed by using Pearson correlation analysis and multiple linear regression analysis.

The major factors associated with CRI were diabetes duration, HbA_1c and 25(OH)D in T2DM, and the regression coefficients were -3.108, -17.247 and 0.326, respectively (all P<0.01). Islet function showed some regularities with the disease duration prolonged. Islet function decreased slowly in the early stage (disease duration ≤5 years), then decreased continuously in an annual rate of about 2%, and finally tended to weaken and decrease slowly again after 22 years of diabetes duration. According to the median of HbA_1c 8.7%, the patients were divided into HbA_1c<8.7% and HbA_1c≥8.7% subgroups. And the patients were assigned to 25(OH)D<45.7 nmol/L and 25(OH)D≥45.7 nmol/L subgroups on the basis of the median of 25(OH)D 45.7 nmol/L. The results showed that the CRIs in HbA_1c<8.7% subgroup were significantly higher than those in HbA_1c≥8.7% subgroup (all P<0.05), while there was no significant differences in CRIs after subgrouping by 25(OH)D (all P>0.05).

In T2DM patients, the islet function decreases slowly at first, then accelerates, and finally decreases slowly again with diabetes duration prolonged, and many factors are associated with CRI.

To study the clinical characteristics of diabetes mellitus with Coronavirus disease 2019 (COVID-19) and explore the possible mechanism of diabetes predisposition.

A single center, retrospective and observational study was used to collect 48 inpatients diagnosed with COVID-19 who were admitted to the first ward of the third department of infection, Raytheon hospital, Wuhan from February 23, 2020 to March 30, 2020. Demographic data, symptoms, laboratory tests, comorbidities, treatments and clinical outcomes have been collected. The patients were divided into non-diabetic group and diabetic group according to the combination of diabetes. The clinical data and laboratory test results of the two groups were observed, and the t test, non-parametric test and Chi square test were used for comparison.

All the 5 patients with COVID-19 diabetes mellitus had fever and respiratory symptoms, chest CT was consistent with typical COVID-19 imaging features, and novel coronavirus nucleic acid test results were positive. There were no statistically significant differences in age, gender composition, co-existing diseases, clinical symptoms, clinical typing, disease course and treatment plan between the diabetic group and the non-diabetic group (P>0.05).There was a statistically significant difference in fasting blood glucose between the non-diabetic group and the diabetic group (P<0.05).The difference of fasting blood glucose at discharge from the diabetes group compared with that at admission was also statistically significant (P<0.05).There was no statistically significant difference between the two groups in other laboratory examination indexes (P>0.05).

COVID-19 patients with diabetes are mainly manifested by fever and respiratory symptoms.Chest CT shows typical COVID-19 imaging features.

To investigate the blood glucose control of diabetic patients during the Coronavirus disease 2019 (COVID-19) epidemic, and to explore the factors affecting blood glucose.

Three hundred and fifty patients with diabetes mellitus hospitalized in the Endocrinology Department of the Second Affiliated Hospital of Air Force Military Medical University from 2017 to 2019 were selected, and we send questionnaires (a self-made questionnaire containing 39 questions, Zung anxiety self-assessment scale, Zung depression self-assessment scale) to the patients through WeChat group. After the effective questionnaires were collected, the patients were divided into good blood glucose control group (fasting blood glucose ≤7 mmol/L and 2 h postprandial blood glucose ≤10 mmol/L) and poor blood glucose control group (fasting blood glucose>7 mmol/L and/or 2 hours postprandial blood glucose>10 mmol/L). Chi squaretest or Fisher exact probability method and t test were used to compare the differences between the two groups. In Multi-factor logistic regression, the backward regression method was performed.