Volume 10 · Issue 11 · 2018

Blood glucose monitoring is an important component in diabetes management, and continuous glucose monitoring (CGM) provides continuous, comprehensive blood glucose information throughout the day. In 2014, a new continuous glucose monitoring system-Flash glucose monitoring (FGM) was approved for marketing in the European Union, bringing major innovations to the field of blood glucose monitoring. This monitoring technique does not require finger blood calibration, only needs scanning to obtain instant glucose values and provide 14-day ambulatory glucose profile (AGP)^[1], attracting the attention of clinicians and diabetic patients.

diabetic neuropathy (DN) can involve the central and peripheral nerves^[1,2,3]Diabetic peripheral neuropathy (DPN) is more common. In recent years, the level of diagnosis and treatment of DN has been greatly improved. The basic research and clinical research of experts and scholars provide a scientific basis for the diagnosis and treatment of DN. Authoritative organizations have formulated guidelines for diagnosis and treatment, which effectively guide the standardization process of diagnosis and treatment in this field. But there are studies^[4,5]It was found that more than half of diabetic patients will have progressive worsening of neuropathy, with peripheral and autonomic dysfunction. Therefore, it is necessary to deeply study the pathogenesis of DN and further explore better diagnosis and treatment strategies for DN. In this paper, some achievements and problems to be solved in the diagnosis and treatment of DN are reviewed.

Diabetic peripheral neuropathy (DPN) refers to symptoms and/or signs associated with peripheral nerve dysfunction in diabetic patients, excluding other causes. DPN is one of the most common chronic complications of diabetes. DPN is highly occult, and more than 50% of DPN patients have no clinical symptoms. Its pathological degree is often inconsistent with the appearance and severity of symptoms. It is a high risk factor for foot ulcer, gangrene and amputation. Therefore, early diagnosis and treatment of DPN is of great significance for improving patients' quality of life and reducing death^[1]。 However, the clinical manifestations of DPN are diverse, the classification methods are different at home and abroad, the types of screening and examination methods are complex, and the diagnostic criteria are different. These different diagnostic criteria and classification methods easily lead to confusion in clinical diagnosis and treatment of DPN. This article reviews the classification methods, diagnostic criteria, screening and examination methods of DPN at home and abroad, hoping to help clinicians to correctly understand DPN.

In recent years, some scholars have found that there are a certain number of residual β cells in the pancreas of diabetic patients^[1,2,3,4]Some of them are resting, non-functional beta cells, which usually do not secrete insulin, but can synthesize and secrete insulin through certain mechanisms. These beta cells are usually understood as "dormant beta cells". In-depth research on the mechanism of dormancy of β cells is expected to reactivate dormant β cells and preserve the function of β cells, so as to find a new means of intervention in diabetes. In this paper, the types of "dormant beta cells" and related studies will be briefly described.

To detect small fiber neuropathy in patients with possible or established diabetic peripheral neuropathy (DPN) by skin punch biopsy and explore clinical characteristics and pathological features in different DPN patients.

A total of 37 patients were collected with possible or established DPN from December 2015 to February 2018. All patients underwent skin punch biopsy, intra epidermal nerve fiber density (IENFD) calculation, nerve conduction studies and clinical examination of neurological signs and symptoms. Fifteen healthy subjects were set as control. Chi-square test was used to analyze the impact of biopsy on DPN diagnosis rate. Student t test and Wilcoxon rank sum test were utilized to compare the difference of clinical characteristic and pathological feature between two subtypes of DPN patients.

The average IENFD in control was (13.4±0.8) fiber/mm in calf and (21.1±5.9) fiber/mm in thigh while the diagnostic cutoff point of DPN was 13.0 fiber/mm in calf and 11.4 fiber/mm in thigh, respectively. Among total 37 patients, 35 were diagnosed as small fiber neuropathy by using skin punch biopsy and the proportion of DPN raised from 73% (27/37) to 95% (35/37) (P<0.05), which included 8 patients with primarily small fiber neuropathy and 27 patients with mixed small and large fiber neuropathy. Patients with primarily small fiber neuropathy had lower level of glycated hemoglobin A_1c, lower proportion of diabetic retinopathy, nephropathy and cardiovascular autonomic neuropathy and higher IENFD in thigh [(8.8±2.6) vs (4.5±1.8) fiber/mm, t=5.424, P<0.01] than patients with mixed small and large fiber neuropathy. IENFD in calf was not significantly different between groups [(1.5±1.2) vs (2.5±1.3) fiber/mm, t=-1.965, P>0.05].

Skin punch biopsy can significantly improve DPN diagnosis rate and is an important tool for identifying diabetic small fiber neuropathy.

To investigate the sensitivity of peripheral nerve conduction study in early diagnosis of peripheral neuropathy in children with type 1 diabetes mellitus (T1DM).

Data were collected from a total of 217 children with T1DM [112 males, 105 females, with average age of (10.54±3.10) years] in the Department of Endocrinology at Children′s Hospital of Nanjing Medical University from the period of July 2007 to August 2017. They were further divided into three age groups, 4 to 6 years old, 7 to 14 years old, and above 14 years, respectively. Forty-six indicators of the nerve conduction study (NCS) were checked, and the final follow-up results were included in the statistical analysis. According to the disease duration, the patients were further divided into two groups duration of <5 years and ≥5 years. Incidence rate between the two groups were analyzed using Chi-square test. Variance analysis of the main factors related to T1DM, such as the presence of ketosis or ketoacidosis at onset, disease duration, and glycated hemoglobin A_1c (HbA_1c) level were also analyzed.

There was significant difference in the motor and sensory latency among three groups (P<0.000 1) as well as the amplitude of common peroneal nerve and the minimum F-wave latency of tibial nerve (P<0.001). Sensory nerve conduction velocity differences in median nerve, ulnar nerve and common peroneal nerve were statistically significant (P<0.05). From 217 cases, the total abnormal incidence rate of diabetic peripheral neuropathy (DPN) was 19.33%. Cases with the duration of <5 years has the incidence rate of 5.30% (377.14/7 121). While the other cases of the duration ≥5 years, the incidence rate was 14.03% (397.15/2 830). The four top single abnormality in descending order were as follows: the prolonged latency rate of median sensory nerve, the latency of ulnar sensory nerves, the minimum F-wave latency of tibial motor nerve and the amplitude of common peroneal nerve. Analysis of the main factors related to T1DM shows that the presence of ketosis or ketoacidosis during the disease progression had no significant correlation with DPN ( P>0.05). However, the disease duration and HbA_1c level were associated with DPN (P<0.05). There was a positive correlation between disease duration and minimum F-wave latency of tibial nerve, as well as the amplitude of ulnar nerve, common peroneal nerve, and tibial nerve (r=0.170-0.312, all P<0.05). On the other hand, a negative correlation was found between HbA_1c level and the motor nerve conduction velocity of ulnar nerve, median nerve and common peroneal nerve (r=-0.237--0.171, all P<0.05).

The impairment of sensory nerve conduction is more pronounced than motor nerve conduction in T1DM children with peripheral neuropathy. Selective peripheral nerve conduction test can help improve the sensitivity of NCS in T1DM children with DPN.

To investigate the relationship of type 2 diabetes mellitus with hepatocellular carcinoma (HCC) and alpha fetal protein (AFP).

A total of 508 patients [(59±12) years old, 406 males (79.92%)] with HCC from January 2010 to December 2016 were retrospectively evaluated. All patients were divided into type 2 diabetic group (n=233) and non-diabetic group (n=275). Fasting blood glucose, liver function and AFP level were compared and analyzed. Liver function was assessed according to the Child-Pugh classification criteria (Grade A, B and C). The pathological grade of hepatocellular carcinoma was divided according to Edmondson-Steiner pathology (Grade 1, 2, 3 and 4). The cancer stage of HCC was obtained at the time of diagnosis based on the Barcelona Clinic Liver Cancer classification (stage 0, 1, 2, 3 and 4). Patients were further divided into different groups based on age:<50 years, 50-59 years, 60-69 years and ≥70 years. The multivariate linear regression, multivariate logistic regression and covariance analysis were applied to investigate the relationship of type 2 diabetes with AFP in HCC.

Compared to non-diabetic group, the diabetic group had higher negative rate of AFP [54.51% (127/233) vs 37.82% (104/275), χ ²=14.17, P<0.001] and worse liver function (χ²=9.60, P=0.012). Serum AFP level in type 2 diabetics was remarkably lower than that in non-diabetics [11 (4-249) vs 89 (8-1 132) μg/L, Z=-4.32, P<0.001]. After adjustment for age, the AFP level in type 2 diabetics was still significantly lower than that in non-diabetics (H=10.15, P=0.002). Type 2 diabetes was significantly correlated with increased incidence risk of high-grade (grade 3 and 4) HCC (OR=1.80, 95%CI 1.08-3.00, P=0.025). In the HCC patients, the serum level of AFP was negatively correlated with age and T2DM (β=-0.151,P=0.001; β=-0.162, P=0.003).

Type 2 diabetes mellitas contributes to lower serum AFP level and worse liver function, which is more likely to delay and interfere with HCC diagnosis, leading to higher malignant degree of HCC.

To evaluate the clinical value of noninvasive skin-stretching device in the healing of diabetic foot after toe amputation or debridement.

A total of 51 diabetic patients with diabetic foot gangrene at Wagner stage 4 after toe amputation or debridement were recruited in the study from May 2017 to March 2018 by using a prospective cohort design. The patients were assigned into trial _{group (n=17) and control group (n=34) and matched by 1}∶₂ ratio [age:(54.9±10.8) yrs vs (59.2±11.3) yrs, duration of diabetic foot: 1.0(1.0, 4.1) months vs 1.5(1.0, 2.0) months]. All patients underwent basic treatment and vacuum sealing drainage therapy until exposing bones were covered by fresh granulation tissues and wound inflammation disappeared. The wounds of control group were received regular dressing change, and adhesive noninvasive skin-stretching devices were applied to the wounds of trial group. The wounds were observed from the 1st day to the day of wound healing or 3 months after surgery. Healing rates were compared, and Kaplan-Meier survival analysis was used for comparing cumulative wound healing rate over time between two groups.

The healing rate of trial group was significantly higher than that of control group (94.1% vs 58.8%, χ ²=5.206, P<0.05). The differences of Kaplan-Meier healing time curve between two groups were statistically significant (P<0.01). Median of healing time in trial group was significantly shorter than that in control group [42 (41, 59) d vs 78 (50, 90) d, Z=3.30, P<0.01]. Taking the end of the last vacuum sealing drainage therapy as the starting point of time, the differences of Kaplan-Meier healing time curve between two groups were statistically significant (P<0.01), and the median of healing time in trial group was significantly shorter than that in control group [13 (8, 14) d vs 42 (26, 42) d, Z=4.845, P<0.01].

The application of noninvasive skin-stretching device in diabetic foot gangrene in the repairation stage after surgery can reduce wound healing time and increase wound healing rate.

To evaluate current status and influencing factors of hypoglycemia fear in patients with type 2 diabetes mellitus(T2DM).

The multi-centers convenience sampling method was used to enroll 392 patients with T2DM [176 males (44.9%), 216 females (55.1%)] who had experienced hypoglycemia within 6 months from outpatient and inpatient in 7 hospitals to complete Hypoglycemia Fear-Behavior Scale from October 2016 to January 2017. The t test and one-way AVOVA and multiple linear regression analysis were used to analyze the data.

The scores of the Hypoglycemia Fear-Behavior Scale were between 20 and 91 points, with an average of (47.65±13.02) points. The three dimensions ranking from high to low based on average score were cautious, avoidance, and maintain high blood glucose. Single factor analysis showed that the scores of Hypoglycemia Fear-Behavior Scale was significantly associated with gender, duration, living style, place of residence, medical expenses, diabetes education, diet control, weekly exercise time, daily insulin injections, smoking, drinking, nocturnal hypoglycemia and asymptomatic hypoglycemia (t=-5.760-2.029, F=4.029-6.872, all P<0.05). Multiple linear regression analysis showed that diet control, diabetes education, asymptomatic hypoglycemia, medical expenses and gender were the influencing factors of hypoglycemia fear behavior (β=6.279, 6.343, 8.237, 2.775, 2.652, allP<0.05).

Diet control, diabetes education, asymptomatic hypoglycemia, medical expenses and gender are the influencing factors of hypoglycemia fear behavior. Health professionals should pay attention to the feelings and behaviors of diabetes patients with hypoglycemia, and implement individualized education.

To determine the effects of high-fat diet on metabolic health outcomes in their male offspring and methylated regulation of the metabolic master regulator, peroxisome proliferator-activated receptor gamma coactivator 1-alpha (Pgc-1α) in C57BL/6 mice.

8-week-old C57BL/6 male mice (n=20) were divided into two groups: the standard chow group (C, n=10) and the high fat diet group (HF, n=10) with random number table. After 12 weeks high fat diet (HFD) feed, each male mouse mated with a female sibling. Male pups were divided into two groups: male offspring from the control group (CM, n=8) and male offspring from HF group (HFM, n=9) were given HFD for 4 weeks until sacrifice at 8 weeks of age.The experimental data were analyzed by t test between two groups.

Compared with CM group, 4 weeks HFD resulted in a significantly increase in HFM in body weight 3.27% (t=-3.924, P<0.01), fat pad mass[(2.26±0.24)% vs (3.67±0.52)%, t=-3.906, P<0.01] and impaired glucose tolerance. Blood glucose in 15 min were (328±26) vs (410±53) mg/dl, 30 min were (318±43) vs (412±48) mg/dl, 60 min were (248±31) vs (328±32) mg/dl and area under the curve were (374±39) mg/dl×120 min vs (388±33) mg/dl×120 min (t=-2.291, -3.656, -4.759, -4.753, all P<0.01). Meanwhile, paternal HFD can increase the HFD-induced methylation of the Pgc-1α promoter were (36.8±4.7)% vs (44.3±3.6)% (t=-4.453, P<0.01) with a trend of decreased Pgc-1α mRNA expression in skeletal muscle.

The current study provides the evidence that paternal obesity can increase susceptibility to HFD-induced obesity and glucose tolerance dysfunction in male offspring with hypermethylation of the Pgc-1α promoter at CpG site-260.

The patient, a 26-year-old female, was admitted to the hospital on 8 July 2015 after "gaining weight for one year and finding an increase in blood sugar for 2 weeks". The patient has gradually gained about 10 kg in weight in the past year. Increased blood glucose was found 2 weeks ago, fasting blood glucose was 8.5 mmol/L, no symptoms of polyuria, dry mouth, polydipsia, no headache and visual field defect, and normal menstruation. The history of hypertension was 2 years, and the highest blood pressure reached 170/100 mmHg (1 mmHg =0.133 kPa). He usually took nifedipine controlled-release tablets to reduce blood pressure, but his blood pressure was not well controlled. He denied family history of diabetes and hypertension, and denied history of alcoholism and depression. Physical examination at admission: body temperature 36.5 ℃, pulse 90 beats/min, breathing 16 beats/min, blood pressure 160/100 mmHg, body weight 93 kg, height 169 cm, body mass index (BMI) 32.42 kg/m²The heart rate was 90 beats/min, the heart rhythm was uniform, the abdomen was soft, there was no tenderness and rebound pain in the whole abdomen, the liver and spleen were not touched, and there was no obvious edema in both lower limbs.

Diabetic ketoacidosis (DKA) is one of the main acute complications of diabetes. Its triggers include infection, improper diet or treatment, and various stress factors leading to insulin deficiency. It is mainly seen in patients with type 1 diabetes mellitus (T1DM). hypertriglyceridemia (HTG) is the most common lipid metabolism abnormality in the Chinese population. Any cause of elevated chylomicrons and/or very low density lipoprotein (VLDL) in plasma can lead to HTG. Insulin deficiency can lead to lipolysis to produce excessive fatty acids and increased triglyceride (TG) synthesis. TG levels exceeding 11.29 mmol/L are defined as severe HTG, and some patients are associated with gene variants such as lipoprotein lipase (LPL) and apolipoprotein (APO). The expression of a single gene mutation in individuals with meaningful pathophysiological changes is not uncommon in clinic, but the presence of LPL and APO A5 mutations at the same time has not been reported. We found simultaneous missense mutations in the LPL and APO A5 genes in a patient with recurrent DKA, which are reported below.

The latest epidemiological survey data show that the prevalence of diabetes in my country is as high as 10.9%, but only 49.2% of patients with blood sugar reach the standard^[1]。 The main cause of death of diabetic patients in China is cardiovascular complications^[2], and substandard blood glucose is one of the main causes of death from cardiovascular complications^[3]。 blood glucose monitoring is one of the important means of diabetes management. continuous glucose monitoring (CGM) is a monitoring technology that can monitor the glucose concentration in subcutaneous intercutaneous fluid through glucose sensors to reflect blood glucose levels. It can provide patients with comprehensive and reliable blood glucose data, and can find hyperglycemia and hypoglycemia that are not easily detected by traditional monitoring methods [such as self-monitoring of blood glucose (SMBG)], and its position in diabetes management is increasing day by day^[4,5]。 There is a close relationship between blood glucose control and blood glucose monitoring in diabetic patients, but there is a lack of standardized blood glucose report in the collection and analysis of blood glucose monitoring data^[4]At the same time, physicians do not make full use of monitoring data and the communication barriers between doctors and patients caused by complex data greatly hinder blood sugar control^[6,7]。

The number of patients with type 2 diabetes in China has exceeded 100 million, and the compliance rate of blood sugar control [glycosylated hemoglobin (HbA_1c)<7.0%] is only about 30%^[1]。 For most patients with type 2 diabetes mellitus (HbA_1c<8.5%), HbA_1cThe increase was mainly associated with postprandial hyperglycemia, and postprandial glycemia was also an independent predictor of cardiovascular events and all-cause mortality in type 2 diabetes^[2]。 Therefore, improving postprandial blood glucose is important for achieving HbA_1cIt is critical to achieve standards and control the complications of type 2 diabetes.