Predictors of success and failure in achieving glycemic control targets in patients with type 2 diabetes on basal insulin: review of the real-world evidence studies

Basal insulin (BI) is the main therapeutic option for patients with type 2 diabetes (T2D) who have not reached glycemic targets on oral antidiabetic drugs and/or glucagon-like peptide-1 receptor agonists. The results of epidemiological studies indicate that the majority of patients with T2D do not achieve the targeted parameters of glycemic control on BI in the real-world settings. In this review the results of real-world evidence studies assessing predictors of success or failure of BI therapy in patients with T2D are we summarized. A number of studies have demonstrated that delayed initiation of insulin therapy with a high level of glycated hemoglobin A1c (HbA1c) at the start of the treatment reduces achieving glycemic control targets on BI. Hypoglycemia in the first weeks or months of BI treatment may reduce the adherence and persistence to treatment and likelihood of achieving treatment targets. In real-world evidence studies, glargine 300 U/mL and degludec, the long-acting second-generation insulin analogues, have shown greater potential in reduction of HbA1c levels with a lower risk of hypoglycaemia compared to other BIs. In the DUNE, ATOS, and some others studies, a lack of insulin dose titration in newly initiated BI users and those who needed treatment intensification was demonstrated. Poor treatment adherence and persistence (missed injections, incorrect dose selection, and temporary or permanent discontinuation of insulin therapy), deviations in insulin injection technique, and formation of lipohypertrophy at the injection sites are also common problems that prevent good glycemic control in these patients. Therefore, patient education with a focus on injection technique, dose titration and prevention of hypoglycemia, as well as the use of the second-generation BI analogs, increases the chances for achieving glycemic control targets in patients with T2D who initiate or need to intensify BI therapy

Impaired hypoglycemia awareness in diabetes: epidemiology, mechanisms and therapeutic approaches

Impaired awareness of hypoglycemia (IAH) is a frequent complication of insulin therapy. Up to half insulin-treated individuals with type 1 and type 2 diabetes report the problems with hypoglycemia awareness, and 15–25% of patients have a permanent IAH. A recurrent hypoglycemia is a cornerstone in IAH formation. The repeated episodes of hypoglycemia impair neurohumoral response to hypoglycemia, reduce its symptoms and induce inadequate brain adaptation to low glucose levels. In this regard, the IAH phenomenon can be considered as an example of "metabolic memory" in diabetes. The IAH is associated with episodes of severe hypoglycemia, fear of hypoglycemia and cognitive dysfunction. These associates can be combined into IAH syndrome. Development of IAH becomes a serious barrier in diabetes management. A growing body of evidence indicates that IAH is a reversible condition. If the syndrome is present, the hypoglycemia avoidance should be primary goal of the treatment. Structured training under specialized programs with psychological support is the most reasonable therapeutic approach to IAH amending. Technological approaches, including continuous subcutaneous insulin infusion, real-time continuous glucose monitoring, closed-loop insulin delivery systems ("artificial pancreas"), and islet transplantation also showed efficacy in hypoglycemia awareness improvement in some clinical studies. The diabetes management in patients with IAH is time-consuming and expensive. Therefore, step-by-step approach, from insulin personalization and therapeutic training to advanced medical technologies, should be recommended for these patients

1,5-anhydroglucitol in diabetes: its role in diagnostics, screening, glycemic status assessment, and the prediction of complications

1,5-anhydroglucitol (1,5-AG) is a short-term indicator of glycemic status, reflecting hyperglycemic glucose excursions over the prior 1–2 weeks. As glucose level remains in the normal range, plasma concentration of 1,5-AG is maintained stable due to the balance between intake with the food and renal excretion. Under hyperglycemic conditions, when the renal threshold for glucose is exceeded, concentration of 1,5-AG decreases due to competitive inhibition of 1,5-AG reabsorption by glucose. In clinical practice, plasma 1,5-AG is used for retrospective assessment of postprandial glucose fluctuations in diabetic subjects with mild or moderate elevation of HbA1c. The marker is also applied in clinical trials of new agents affecting postprandial glycemia. The advantages of 1,5-AG as a marker of glycemic status are stability, independence on the physiological state when sampling, applicability for patients with abnormalities of hemoglobin and lifespan of erythrocytes. Meantime, the value of this marker is limited in subjects with renal tubular acidosis, 4-5 stages of chronic kidney disease, renal glucosuria, in those receiving acarbose and SGLT2 inhibitors. Application of 1,5-AG for the diagnosis and screening of type 2 diabetes, gestational diabetes and prediabetes has been tested. It was revealed that sensitivity of 1,5-AG as screening tool may be insufficient in individuals with mild hyperglycemia, especially if fasting hyperglycemia prevails. Therefore, it has been proposed to combine 1,5-AG with assessment of fasting glucose for the screening purposes. In type 2 diabetic subjects low plasma 1,5-AG is a predictor of renal failure, cardiovascular events, including ischemic heart disease, heart failure and stroke. Decreased 1,5-AG concentration in pregnant women is a risk factor for gestational diabetes and macrosomia. Chromatography and enzymatic methods are used to determine 1,5-AG in blood, urine and other biological fluids. Currently, the relatively high cost and lack of standardization restrain the use of 1,5-AG in clinical practice. Further studies are needed for estimation of 1,5-AG value as a marker of glycemic status in type 1 diabetes, in patients with different levels of HbA1c and different magnitude of glucose variability, as well as in situations where the clinical value of HbA1c is limited

Lymphatic system and adipose tissue: Crosstalk in health and disease

The lymphatic system (LS) is one of the main integrative systems of the body, providing protective and transport functions. In recent years, interactions between LS and adipose tissue (AT) have been of particular interest. Lymphatic vessels play an important role in metabolic and regulatory functions of AT, acting as a collector of lipolysis products and adipokines. In its turn, hormones and adipocytokines that produced in adipocytes (including leptin, adiponectin, IL-6, TNF-α, etc.) affect the function of lymphatic endothelial cells and control the growth of lymphatic vessels. Cooperation between LS and AT becomes pathogenetically and clinically important in lymphedema and obesity. It is known that both primary and secondary lymphedema are characterized by increased fat accumulation which is associated with the severity of lymphostasis and inflammation. Similarly, in obesity, the drainage function of LS is impaired, which is accompanied by perilymphatic mononuclear infiltration in the AT. The development of these changes is facilitated by endocrine dysfunction of adipocytes and impaired production of adipocytokines. The increase in the production of inflammatory mediators and the disruption of the traffic of inflammatory cells causes a further deterioration in the outflow of interstitial fluid and exacerbates the inflammation of the AT, thereby forming a vicious circle. The role of lymphangiogenesis in AT remodeling in obesity needs further research. Another promising area of research is the study of the role of intestinal LS in the development of obesity and related disorders. It has been shown that the transport of chylomicrons from the intestine depends on the expression of a number of molecular mediators (VEGF-C, DLL-4, neuropilin-1, VEGFR-1, CD36/FAT, etc.)in the endotheliocytes of the intestinal lymphatic vessels, as well as the functioning of «push-button» and “zippering” junctions between endothelial cells. New approach to the treatment of obesity based on blockade of lymphatic chylomicrontransport has been experimentally substantiated. Further identification of the molecular mechanisms and signaling pathways that determine the remodeling of AT in lymphedema and obesity are likely to provide new approaches to the treatment of these diseases

Artificial intelligence in diabetology

This review presents the applications of artificial intelligence for the study of the mechanisms of diabetes development and generation of new technologies of its prevention, monitoring and treatment. In recent years, a huge amount of molecular data has been accumulated, revealing the pathogenic mechanisms of diabetes and its complications. Data mining and text mining open up new possibilities for processing this information. Analysis of gene networks makes it possible to identify molecular interactions that are important for the development of diabetes and its complications, as well as to identify new targeted molecules. Based on the big data analysis and machine learning, new platforms have been created for prediction and screening of diabetes, diabetic retinopathy, chronic kidney disease, and cardiovascular disease. Machine learning algorithms are applied for personalized prediction of glucose trends, in the closed-loop insulin delivery systems and decision support systems for lifestyle modification and diabetes treatment. The use of artificial intelligence for the analysis of large databases, registers, and real-world evidence studies seems to be promising. The introduction of artificial intelligence systems is in line with global trends in modern medicine, including the transition to digital and distant technologies, personification of treatment, high-precision forecasting and patient-centered care. There is an urgent need for further research in this field, with an assessment of the clinical effectiveness and economic feasibility

Reference values of 24-hour, day-time and nocturnal glucose variability parameters in subjects with normal glucose tolerance

BACKGROUND: Glucose variability (GV) is recognized as a risk factor for microvascular and macrovascular complications of diabetes and hypoglycemia. A number of indices have been proposed to assess GV, but there are no generally accepted normal reference values for these indices.AIM: To establish the reference values of 24-hour, day-time and nocturnal GV parameters derived from continuous glucose monitoring (CGM) data in young and middle-aged subjects with normal glucose tolerance.MATERIALS AND METHODS: A blind 6–7-day CGM was performed in 50 subjects, 20 men and 30 women, aged from 22 to 56 years, with normal values of the oral glucose tolerance test and glycated hemoglobin A1c. GV parameters: Standard Deviation (SD), Coefficient of Variation (CV), Mean Amplitude of Glycemic Excursions (MAGE), 2-hour Сontinuous Overlapping Net Glycemic Action (CONGA), Lability Index (LI), J-index, Mean Absolute Glucose rate of change (MAG), М-value, High Blood Glucose Index (HBGI), Low Blood Glucose Index (LBGI) were calculated for 24-hour records, day-time (6.00–23.59) and night (0.00–5.59) hours.RESULTS: 95% confidence intervals for 24-hour records were: mean glucose 5.2–6.6 mmol/L, SD 0.5–1.3 mmol/L, CV 9.1–23.2%, MAGE 1.2–3.2 mmol/L, CONGA 4.3–5.9 mmol/L, MAG 0.5–2.1 mmol×L-1×h-1, LI 0.1–1.3 (mmol/L)2×h-1, J-index 11.3–18.6 (mmol/L)2, M-value 0.4–4.4, HBGI 0.1–1.9, LBGI 0.3–3.2.The following day-time values were estimated: mean glucose 5.3–6.7 mmol/L, SD 0.5–1.4 mmol/L, CV 8.7–24.5%, MAGE 1.2–3.4 mmol/L, CONGA 4.3–5.9 mmol/L, MAG 0.6–2.5 mmol×L-1×h-1, LI 0.2–1.6 (mmol/L)2×h-1, J-index 11.2–19.6 (mmol/L)2, M-value 0.2–3.8, HBGI 0.1–1.9, LBGI 0.3–3.0. The values for nocturnal hours were: mean glucose 4.7–6.4 mmol/L, SD 0.3–0.9 mmol/L, CV 5.3–17.9%, MAGE 0.7–2.7 mmol/L, CONGA 4.1–5.8 mmol/L, MAG 0.3–1.8 mmol×L-1×h-1, LI 0.05–0.8 (mmol/L)2×h-1, J-index 8.5–17.5 (mmol/L)2, M-value 0.2–5.2, HBGI 0–0.9, LBGI 0.3–3.6.CONCLUSION: The obtained reference values of the GV indices should be taken into account in research and in clinical practice when interpreting the results of CGM in young and middle-aged people

Factors associated with high glucose variability in patients with type 1 diabetes

BACKGROUND: High glucose variability (GV) is recognized as a risk factor for vascular diabetic complications and hypoglycemia. Factors affecting GV in patients with diabetes needed to be clarified.AIM: To determine the factors associated with high GV in adult patients with type 1 diabetes.MATERIALS AND METHODS: We conducted a single center cross-sectional observational study. In-patients with type 1 diabetes aged 18 to 65 years on basal bolus insulin therapy were included. Day-time and nocturnal Coefficient of Variation (CV), Mean Amplitude of Glycemic Excursions (MAGE), Mean Absolute Glucose (MAG) were calculated from continuous glucose monitoring data. The values of CV, MAGE, MAG within the upper quartile were considered high.RESULTS: The study included 400 individuals, including 111 on continuous subcutaneous insulin infusion (CSII). Patients with high GV had lower fasting and postprandial C-peptide levels and higher insulin doses. According to ROC analysis, daily insulin dose >0.69 U/kg and estimated glomerular filtration rate (eGFR) ≥90.5 ml/min×1.73 m2 were associated with high nocturnal CV values. Dose of basal insulin >0.292 U/kg and bolus insulin >0.325 U/day were associated with nocturnal MAGE. Body mass index (BMI) ≤23.2 kg/m2, waist circumference ≤80.5 cm, daily insulin dose ≥0.69 U/kg, HbA1c ≥8.3%, eGFR ≥89.5 ml/ min×1.73m2 increased risk of high MAG at night. High day-time CV values were associated with daily insulin dose ≥0.675 U/kg and daily dose of BI ≥0.286 U/kg. The risk of high MAGE was increased with HbA1c ≥8.24% and basal insulin dose ≥0.286 U/kg. BMI ≤23.2 kg/m2, waist circumference ≤80.5 cm, daily insulin dose ≥0.69 U/kg, daily dose of bolus and basal insulin ≥0.325 and ≥0.29 U/kg respectively, and HbA1c ≥8.33% were the risk factors for high day-time MAG. Patients on CSII had lower MAGE (p<0.001) and MAG (p=0.008) compared to those on multiple daily injections.CONCLUSION: In type 1 diabetes, high GV is associated with undetectable residual insulin secretion, normal or reduced body weight, preserved kidney function, supraphysiological doses of insulin, and non-target HbA1c. Patients on CSII have a lower GV than those on multiple daily injections

Risk factors for decreased bone mineral density in men with type 2 diabetes.

BACKGROUND: Type 2 diabetes and osteoporosis are widespread diseases in the middle-aged and elderly people. Most studies of osteoporosis in patients with type 2 diabetes have been performed in women; meantime risk factors for lowering bone mineral density (BMD) in men have been little studied.AIMS: to identify risk factors for decreased BMD at the lumbar spine, femoral neck and forearm in men with type 2 diabetes.METHODS: Eighty two men from 50 to 75 years old, with duration of diabetes for at least one year, were included in the study. Individuals with known risk factors for secondary osteoporosis were not included. Twenty-three men with normal BMD having no diabetes or obesity were acted as control. The T-score at the lumbar spine, femoral neck and forearm of a non-dominant arm, as well as body composition parameters, were evaluated by dual-energy X-ray absorptiometry. The levels of hormones that affect bone metabolism (parathyroid hormone, free testosterone, 25-OH vitamin D) were measured in blood serum by ELISA. Risk factors for reducing BMD were identified using multivariate regression analysis and receiver operating characteristic (ROC) curves.RESULTS: Among patients with diabetes, 49 individuals had normal BMD and 33 showed decreased T-score values (<-1 SD). Free testosterone <5.92 pg/ml was predictor for decreased BMD at the lumbar spine (OR=4.4, p=0.04). For femoral neck, the risk factors were body weight <95.5 kg (OR=2.8, p=0.04), total fat mass <27 kg (OR=3.3, p=0.03), truncal fat mass<17.5 kg(OR=4.5, p=0.006), android (central abdominal) fat mass <3.2 kg(OR=4.0, p=0.01), gynoid (hip) fat mass <3.5 kg(OR=3.3, p=0.02), and lean mass <59 kg(OR=3.0, p=0.04). Risk factors for reduced BMD at the forearm were diabetes duration>15.5 years (OR=3.7, p=0.03) and HbA1c <8.15% (OR=3.8, p=0.03). Parathyroid hormone and 25-OH-vitamin D did not predict BMD independently.CONCLUSIONS: In men with type 2 diabetes, low free testosterone is a risk factor for decreased BMD in the lumbar spine, and diabetes duration is a risk factor for decreased BMD in the forearm. The presence of obesity is associated with an increase in BMD in the femoral neck; a high HbA1c is associated with an increase in BMD in the forearm

POLYMORPHISMS OF EXTRACELLULAR CONNECTIVE TISSUE REMODELING PROTEINASES AND <i>MMP2, MMP3, MMP9</i> GENES, AND NEOANGIGENESIS <i>VEGF</i> GENE IN RETINAL MICROANGIOPATHY IN THE PATIENTS WITH TYPE 2 DIABETES MELLITUS

The aim of our study was to perform an association analysis between MMP2, MMP3, MMP9, VEGF gene polymorphisms and development of non-proliferative diabetic retinopathy (DR) in the type 2 diabetic patients (DM).201 DM patients: 90 cases of DR and 111 subjects without DR features were included into the study. Polymorphic variants of MMP2 (rs2438650), MMP3 (rs3025058), MMP9 (rs3918242), and VEGF (rs699947 and rs3025039) genes were assayed. The genetic typing was carried out by restriction fragment length polymorphism and TaqMan methods.The analysis of complex genotypes at the five polymorphic positions has revealed some significant findings in positive and negatively incorporated complexes. Increased frequencies of MMP2-1306 CC genotype in the group of patients with “early” development of complication, and more frequent combination of high-level HbA1c with MMP2-1306CC and MMP9-1562CT genotypes were shown in DR patients. Computerassisted modelling with visual reconstruction of network interactions between the genotypes involved into the destruction events and angiogenesis, as well as altered HbA1с levels (an integral parameter of glycemia), has revealed some differences in structural and functional organization of gene-gene and gene- protein interactions between the groups of patients with DR versus those without this disorder. Сonclusion. A design of interactome biological networks based on transcription regulation and metabolic pathways, as well as their topological analysis allows to build and study interactions of genes and proteins, with reference to pathogenetic studies of DM2 complications aiming for development of approaches to personalized prevention and therapy in future times

Clinical and laboratory characteristics of the patterns of chronic kidney disease in patients with type 2 diabetes

BACKGROUND: A growing body of evidence demonstrates increasing prevalence of normoalbuminuric chronic kidney disease (NA-CKD) in subjects with type 2 diabetes (T2D), while proportion of albuminuric pattern is decreasing. AIMS: To determine the clinical and laboratory parameters associated with different patterns of CKD in patients with T2D. METHODS: This observational, single-center, cross-sectional study included 360 patients with T2D duration &ge;10 years. Patients with urinary albumin/creatinine ratio (UACR) &lt;3 mg/mmol and estimated glomerular filtration rate (eGFR) &gt;60 ml/min/1.73 m2 were classified as no-CKD group (n=89). Patients with UACR &lt;3 mg/mmol and eGFR &lt;60 ml/min/1.73 m2 formed NA-CKD group (n=111). Individuals with eGFR &ge;60 ml/min/1.73 m2 and UACR mg/mmol &ge;3 were recorded as albuminuric with preserved renal function (A-CKD&ndash;, n=87). Patients with eGFR &lt;60 ml/min/1.73 m2 and UACR mg/mmol &ge;3 mg/mmol were considered as albuminuric CKD group (A-CKD+, n=73). Urinary nephrin and podocin, the podocyte injury markers, and whey acidic protein four-disulfide core domain protein 2 (WFDC-2), a marker of tubulointerstitial involvement, was assessed by ELISA and compared to control (20 non-diabetic subjects). RESULTS: Age &ge;65 years (p=0.0001), duration of T2D &ge;15 years (p=0.0009), female sex (p=0.04), and therapy with diuretics (p=0.0005) were found as risk factors for NA-CKD. The risk factors for A-CKD were male sex (p=0.01), smoking (p=0.01), waist-to-hip ratio &gt;1 (p=0.01) and HbA1c levels &gt;8% (p=0.005). The duration of T2D &ge;15 years (p=0.01) and the use of dihydropyridine calcium channel blockers (p=0.01) were associated with A-CKD+. In T2D groups, the urinary excretion of nephrin and podocin was increased (all p&lt;0.001), more markedly in albuminuric individuals (p&lt;0.01 vs. NA-CKD). WFDC-2 excretion was increased in men from all diabetic groups (p&lt;0.05) and in women with decreased eGFR only (p&lt;0.05 vs. the control and NA-CKD). CONCLUSIONS: The CKD patterns in T2D are heterogeneous according to their clinical and laboratory characteristics. The changes in the excretion of nephrin and podocin indicate the association of albuminuric patterns with podocyte injury. A decrease in eGFR in women with T2D is associated with an increase in urinary excretion of WFDC-2, tubulointerstitial fibrosis marker