Volume 15 · Issue 01 · 2023

With the progress of aging society, the number of elderly diabetic patients in China has increased dramatically, and sarcopenia as one of the comorbidities of elderly diabetes has been gradually paid attention to. Diabetes exacerbates the age-related rate of decline in muscle mass and muscle strength. Diabetes mellitus with sarcopenia in the elderly will further deteriorate metabolic disorders, increase the risk of falls and fractures in the elderly, lead to a serious decline in their quality of life, and promote the occurrence of senile weakness. This paper discusses the pathogenesis, epidemiology, diagnosis, prevention and treatment strategies of sarcopenia in the elderly diabetes mellitus, and proposes that clinicians should improve their understanding of this disease, and advocates to carry out more related research in the future.

Insulin resistance is a common clinical phenomenon, which is the common pathophysiological basis of obesity, diabetes and other diseases. This article briefly introduces the history of insulin resistance and insulin resistance syndrome, the mechanism of insulin resistance and management strategies.

To evaluate the suitability of upper arm circumference as a surrogate marker of low muscle mass for the diagnosis of sarcopenia in older Chinese patients with type 2 diabetes mellitus (T2DM).

A total of 652 patients with T2DM aged over 60 years from Department of Endocrinology of nine different hospitals in Beijing were involved in this study. The maximum upper arm circumference and grip strength were measured. Appendicular skeletal muscle mass (ASM) and appendicular skeletal muscle mass index (ASMI) was calculated by using bioimpedance analysis (BIA). The diagnostic criteria for low muscle mass are ASMI<7.18 kg/m² for men and <5.73 kg/m² for women. According to these criteria, the patients of different genders were divided into normal muscle mass group and low muscle mass group. According to body mass index (BMI), the participants of different genders were divided into BMI≤25 kg/m² group and BMI>25 kg/m² group. The t test or rank sum test was used for comparison between groups. Pearson correlation analysis was used to explore the correlation between upper arm circumference and muscle mass, and the receiver operating characteristic (ROC) curve was drawn and the area under the curve (AUC) was calculated to evaluate the diagnostic ability of upper arm circumference for low muscle mass. The optimal cut-off point was calculated by determining the shortest distance between the ROC curve and upper left corner of the graph. An external validation was performed in another population including 336 hospitalized diabetes patients aged over 60 years from Beijing Hospital in 2019.

There were 327 males and 325 females in all 652 participants. There were 82 and 245 male participants, 34 and 291 female participants in low muscle mass group and normal muscle mass group, respectively. Upper arm circumference [male: (29.6±2.3) vs. (32.5±2.3) cm, respectively; female: (27.9±1.7) vs. (31.3±2.3) cm, respectively] and grip strength [male: (28±6) vs. (32±6) kg, respectively; female: (23±6) vs. (26±4) kg, respectively] were lower significantly in low muscle mass group than in normal muscle mass group, both in male and female (all P<0.001). Upper arm circumference was positively correlated with BIA-measured ASMI (men: r=0.637, women: r=0.662, both P<0.01). The AUC (95%CI) for screening low muscle mass were 0.812 (0.760-0.863) for men and 0.881 (0.834-0.929) for women, respectively. The optimal upper arm circumference cut-offs for low muscle mass screening were 30.3 cm (sensitivity 85.3%, specificity 61.0%) for men and 29.8 cm (sensitivity 86.6%, specificity 88.2%) for women, respectively. In the subgroup with BMI≤25 kg/m², the optimal upper arm circumference cut-offs for low muscle mass were 30.3 cm (sensitivity 85.3%, specificity 74.2%) for men (162 cases) and 28.1 cm (sensitivity 89.9%, specificity 62.1%) for women (132 cases), respectively. In the subgroup with BMI>25 kg/m², the optimal upper arm circumference cut-offs for low muscle mass were 33.0 cm (sensitivity 89.1%, specificity 87.5%) for men (165 cases) and 30.9 cm (sensitivity 84.6%, specificity 99.0%) for women (193 cases), respectively. External validation found diagnostic accordance rate was 76.1% and 79.6%, Kappa index was 0.534 and 0.517 for men and women, respectively.

Upper arm circumference is positively correlated with BIA-measured muscle mass and is a simple surrogate marker of muscle mass for diagnosing sarcopenia.

To explore the association between inflammatory cytokines and sarcopenia in geriatric hospitalized patients with type 2 diabetes mellitus (T2DM).

A total of 508 patients with T2DM aged>60 years old who were hospitalized in the Department of Endocrinology from April 2017 to April 2019 in Xuanwu Hospital of Capital Medical University were retrospectively enrolled. General information of the patients, including height and weight was collected and body mass index (BMI) was calculated. Glycated hemoglobin A_1c (HbA_1c) and inflammatory cytokines (C-reactive protein and interleukin-6) were tested. The appendicular skeletal muscle mass, grip strength and walking speed were measured, moreover, appendicular skeletal muscle mass index (ASMI) was calculated. The patients were divided into non-sarcopenia group and sarcopenia group according to the Asian diagnostic criteria of sarcopenia. The t-test, Mann-Whitney U test and χ² test were used to compare the general clinical data between the two groups. Linear and logistic regression was used to explore the influencing factors of sarcopenia.

Of the 508 patients, 41 were sarcopenia and 467 were non-sarcopenia. Compared to the non-sarcopenia group, patients with sarcopenia were older [(74.04±7.79) vs. (67.03±6.60) years, respectively], had lower BMI [(22.90±3.37) vs. (25.98±3.51) kg/m², respectively], and had higher levels of HbA_1c [(9.16±2.17) % vs. (8.43±1.83) %, respectively] and C-reactive protein [2.89 (1.55, 5.26) vs. 2.18 (1.31, 3.77) mg/L, respectively] (all P<0.05). Linear regression analysis showed that after adjusting for age, gender and BMI, C-reactive protein (β=-0.101, 95%CI -0.150- -0.045) and interleukin-6 (β=-0.057, 95%CI -0.149- -0.003) were negatively correlated with ASMI (P<0.05). Logistic regression analysis showed that after adjusting for age, gender, BMI and HbA_1c, C-reactive protein remained an independent risk factor for sarcopenia (OR=1.357, 95%CI 1.024-1.798, P<0.05).

C-reactive protein is independently associated with the risk of sarcopenia in geriatric hospitalized patients with T2DM.

To investigate the relationship between sarcopenia and polyvascular disease (PVD) in diabetic foot patients.

This was a cross-sectional study. A total of 255 patients with diabetic foot who were hospitalized in the Department of Endocrinology, First Affiliated Hospital of Chongqing Medical University from January 2014 to September 2018 were enrolled in this study. General data of all patients were collected, including age, duration of diabetes, history of essential hypertension, history of coronary heart disease, and presence of chronic complications of diabetes [diabetic kidney disease, peripheral arterial disease (PAD)]. Blood routine was tested. Body fractions were detected by dual energy X-ray absorptiometry. The diagnostic criteria for sarcopenia were appendicular skeletal muscle mass index (ASMI)<7.01 kg/m² in males and ASMI<5.42 kg/m² in females. PVD was defined as symptomatic atherosclerotic disease in at least two major blood vessels (neck vessels, cerebral vessels, coronary arteries, and peripheral arteries of the lower extremities). According to the above criteria, participants were divided into non-PVD group (47 cases) and PVD group (208 cases). The t test or χ² test was used for comparison between the two groups. The logistic regression analysis was used to analyze the influencing factors of PVD.

Compared with the non-PVD group, the age [(68.33±10.05) vs. (58.89±10.89) years old, respectively], the duration of diabetes [(12.56±8.67) vs. (9.48±7.29) years, respectively], the prevalence of hypertension [70.2% (146/208) vs. 42.6%(20/47), respectively], and the prevalence of PAD [82.7% (172/208) vs. 29.8 (14/47), respectively] in the PVD group were statistically significantly higher (all P<0.05). There was no significant difference in the prevalence of sarcopenia between the two groups [41.8% (87/208) vs. 29.8% (14/47), P=0.127]. Binary logistic regression analysis showed that PAD [OR value (95%CI): 46.792 (13.736-159.404)], coronary heart disease [OR value (95%CI): 40.537 (7.320-224.488)], essential hypertension [OR value (95%CI): 5.533 (1.747-17.523)] and sarcopenia [OR value (95%CI): 3.230 (1.069-9.758)] were risk factors for PVD (all P<0.05). Multiple logistic regression analysis showed that sarcopenia was an influencing factor for the number of PVD vascular lesions in diabetic foot patients [OR value (95%CI): 7.024 (1.711-28.826), P=0.007].

Sarcopenia is an influencing factor of PVD in diabetic foot patients.

To explore the efficacy and safety of biphasic insulin aspart 30 (Ruisulin^®30 and NovoMix^®30) in treatment of patients with type 2 diabetes mellitus.

This was a multicenter, randomized, open-labeled, parallel, positive drug-controlled phase Ⅲ clinical trial. This trial included the 588 T2DM patients having poor glucose control after using oral hypoglycemic drugs. All patients were treated with Ruisulin^®30 or NovoMix^®30 for 24 weeks in both groups by a ratio of 3∶1 according to block random method. The decreased value and qualification rates of glycosylated hemoglobin A_1c (HbA_1c), fasting blood glucose (FPG), 2-hour standard postprandial venous plasma glucose (2hPG), the incidence of hypoglycemic and adverse events, and the positive rate of aspartic islet specific antibody were compared at the end of 24 weeks. The full analysis set and per-protocol dataset were used for the effectiveness index analysis, and the safety set was used for the security index analysis. Analysis of matched samples t-test, t-test, χ² test and Wilcoxon test were used.

The trial included all 588 cases, and 528 of them were completely in accordance with the design plan (395 cases received Ruisulin^®30 therapy and 133 cases received NovoMix^®30 therapy). There were 583 cases in full analysis set and safety data set (439 cases received Ruisulin^®30 therapy and 144 cases received NovoMix^®30 therapy), and 515 cases met per-protocol dataset (386 cases received Ruisulin^®30 therapy and 129 cases received NovoMix^®30 therapy). At the end of 24-week treatment period, HbA_1c in Ruisulin^®30 group and NovoMix^®30 group decreased by (1.73±1.27)% and (1.77±1.40)%, FPG decreased by (2.34±2.69) and (2.68±2.84) mmol/L, and 2hPG decreased by (4.37±4.59) and (4.81±4.43) mmol/L, respectively. There was no statistically significant differences in above parameters between the two groups (all P>0.05). After 24 weeks of treatment, the incidence of hypoglycemic events was 74.3% (326/439) and 68.1% (98/144) in Ruisulin^®30 group and NovoMix^®30 group, respectively. The incidence of adverse events [ 68.1% (299/439) and 66.7% (96/144), respectively] was similar to the rate of anti-insulin Aspart antibody positivity [51.9% (228/439) and 50.7% (73/144), respectively], and none of the differences were statistically significant (all P>0.05).

Ruisulin^®30 has good safety, and provides similar glycemic control profiles to NovoMix^®30, indicating that Ruisulin^®30 has clinical application value.

To investigate the interaction between dyslipidemia and family history of diabetes mellitus on the risk of diabetes mellitus among adults in Hebei Province.

This study was a cross-sectional study. Using data from the China Chronic Disease and Risk Factor Surveillance (CCDRFS), residents aged≥18 years were selected through multistage clustering sampling from October to December 2018. The data of individual′s blood glucose and lipid were collected. Complex weighting was used to estimate the prevalence of diabetes in the subjects. The additive model was used to analyze the interaction between dyslipidemia and family history of diabetes mellitus in adult residents of Hebei Province. The relative excess risk of interaction (RERI), the attributable proportion of interaction (AP), and the synergy index (SI) were calculated to assess the interaction effect on the additive scale.

A total of 7 725 subjects aged≥18 years were finally included in this study, and the prevalence of diabetes mellitus was 13.1%. The results of the model analysis showed that the risk of dyslipidemia residents who had family history of diabetes mellitus was of 5.407 times higher (95%CI 4.306-6.790, P<0.001) than those in the normal group with RERI, AP and SI of 1.224 (95%CI 0.015-2.433), 0.226 (95%CI 0.035-0.417) and 1.384 (95%CI 1.012-1.894), respectively. The residents with high-density lipoprotein cholesterol (HDL-C) and family history of diabetes mellitus group had a 5.398 times greater risk of developing diabetes than those with the normal group (95%CI 3.995-7.294, P<0.001) with RERI, AP and SI of 2.203 (95%CI 0.710-3.696), 0.408 (95%CI 0.231-0.585) and 2.004 (95%CI 1.361-2.951), respectively.

The exposures of both dyslipidemia and family history of diabetes mellitus could result in an additive interaction effect on diabetes mellitus.

To investigate the relationship between carotid intima media thickness (CIMT) and serum wingless-type MMTV integration site family member 5a (Wnt5a) and related factors in patients with type 2 diabetes mellitus (T2DM).

Patients with T2DM hospitalized in the Department of Endocrinology of Henan Provincial People′s Hospital from September 2020 to December 2021 were selected as participants. The levels of serum Wnt5a, interleukin-6 (IL-6), tumor necrosis-α (TNF-α) and transforming growth factor (TGF)-β1 were detected, and the CIMT was measured. According to CIMT, the patients were divided into three groups: without thickened group (CIMT<1.0 mm), thickened group (1.0 mm≤CIMT<1.5 mm) and plaque group (CIMT≥1.5 mm). One-way analysis of variance (ANOVA), Kruskal-Wallis H test or χ² test were used to compare the general clinical data of patients in the three groups. Spearman correlation analysis was used to analyze the correlation between CIMT and Wnt5a, IL-6, TNF-α, TGF-β1, and serum Wnt5a with IL-6, TNF-α, TGF-β1. The influencing factors of CIMT, serum Wnt5a were analyzed by multiple linear regression analysis.

A total of 163 patients were included. There were 60 cases in without thickened group, 48 cases in thickened group and 55 cases in plaque group. The levels of CIMT, Wnt5a, IL-6, TNF-α and TGF-β1 in plaque group were higher than those in without thickened group and thickened group (all P<0.001). Correlation analysis showed that CIMT was positively correlated with Wnt5a (r=0.717), IL-6 (r=0.544), TNF-α (r=0.524) and TGF-β1 (r=0.803) (all P<0.001). Serum Wnt5a was positively correlated with IL-6 (r=0.465), TNF-α (r=0.453) and TGF-β1 (r=0.631) (all P<0.001). Multiple linear regression analysis showed that Wnt5a, IL-6 and TGF-β1 were influencing factors of CIMT (all P<0.05), while IL-6 and TGF-β1 were influencing factors of serum Wnt5a (all P<0.05).

CIMT in T2DM patients was closely related to Wnt5a, IL-6 and TGF-β1.

Based on the perspective of life course epidemiology, to explore the effects of adverse childhood experiences (ACE) and perinatal stressful life events (SLE) on the risk of gestational diabetes mellitus (GDM) and their modes of action.

This study was a retrospective study. Pregnant women in the first trimester who were examined in Ma′anshan Maternal and Child Health Hospital from May to September 2019 were enrolled. The history of SLE, type of SLE and cumulative number of SLE events, as well as the history of ACE, type of ACE and cumulative score of ACE in the past 1 year were collected. At gestational 24-28 weeks, 75 g oral glucose tolerance test (OGTT) was performed to diagnose GDM. Logistic regression model was used to analyze the independent effects of ACE and SLE on the risk of GDM. Additive or multiplicative interaction between ACE and SLE were analyzed through interaction analysis. Stratified analysis was used to determine whether ACE had a modifying effect on SLE.

A total of 1 001 participants were included. The reporting rates of ACE and SLE were 19.1% (191/1 001) and 38.5% (385/1 001), respectively. The results of logistic regression model showed that experienced ACE or not, the type of ACE and the cumulative score of ACE, experienced SLE or not, the type of SLE and the cumulative number of SLE had no statistical significance on the risk of GDM (all P>0.05). Stratified analysis showed that among pregnant women with ACE, those with SLE≥2 and had a 1.64-fold increased the risk of GDM compared with those without SLE (OR＝2.64, 95%CI 1.08-6.47, P_{heterogeneity} = 0.036).

The occurrence of GDM is unaffected by ACE or SLE alone, but ACE has a significant moderating effect on the association between SLE and GDM. Perinatal SLE increases the risk of GDM only in pregnant women who have had an ACE.

In this study, the detection rate of adult-type diabetes mellitus (MODY) related genes in adolescent-onset patients with early-onset diabetes mellitus was investigated in a tertiary hospital in Xinjiang. The clinical data of 334 patients with early-onset diabetes mellitus admitted to the Endocrinology Department of Xinjiang Uygur Autonomous Region People's Hospital from January 2015 to December 2020 were collected, and 122 of them were genetically tested. Based on the genetic test results, the differences in clinical phenotypes of MODY patients and non-MODY patients were compared. The results showed that 5 (4.1%) patients could be definitively diagnosed with MODY, including 2 MODY3, 1 MODY5, 1 MODY8 and 1 MODY10. Compared with non-MODY patients, the age of onset in MODY patients was earlier [(19.60 ± 10.53) and (30.48 ± 10.72) years, respectively,P=0.28], higher total cholesterol levels [(6.30 ± 1.25) and (4.67 ± 1.62) mmol/L, respectively,P=0.49], which may be related to different MODY type characteristics. In summary, the detection rate of MODY in this region is 4.1%, and genetic testing is helpful for accurate typing and individualized treatment of MODY.

In recent years, sarcopenia obesity (SO) has been gradually paid attention to. The pathogenesis of SO is complex, and it is of great significance to explain its pathogenesis and formulate accurate treatment plans. This article reviewed the diagnostic criteria and epidemiological characteristics of SO, and focused on the research progress of the pathogenesis and treatment strategies of SO.

N-glycomics is mainly an emerging subject to study the structure and function of N-glycans in the body. In recent years, there are more and more studies on the correlation between N-glycomic changes and various diseases. Diabetes is a chronic disease with high incidence in the world. Many pathophysiological changes and metabolic disorders occur in diabetic patients, with glucose metabolism disorders being the most prominent. At present, many studies have reported that diabetes mellitus is related to the changes of N-glycogome. The quantity, structure and immunoglobulin G N-glycan of N-glycoprotein in serum of diabetic patients have changed, and it indicates that N-glycan may be used as a diabetes biomarker. In this paper, the progress of N-glycomics in diabetes mellitus is briefly reviewed.

Peritoneal dialysis is one of the main renal replacement therapies in patients with end-stage renal disease (ESRD). In recent years, the proportion of diabetic patients among patients on peritoneal dialysis has been increasing. Scientific use of insulin in clinic has become an important issue for stably controlling blood sugar and preventing cardiovascular events. Based on the consensus and progress in the treatment of diabetic ESRD at home and abroad, this article focuses on the insulin use strategies of diabetic ESRD patients on peritoneal dialysis, including the target value of blood glucose control, selection of peritoneal dialysis fluid and determination of insulin dose, so as to improve the prognosis of patients.

Food addiction disorder is an important contributor to obesity. The Yale Food Addiction Scale can be used to assess and diagnose food addiction disorders. The formation mechanism of food addiction disorder involves neurobiology, psychopathy, genetic factors and sociocultural risk factors. Food addiction can be improved by managing diet, improving lifestyle, increasing exercise, nutritional guidance, psychological intervention, adjusting public health policy, internal medicine intervention, bariatric surgery, and traditional Chinese medicine treatment.