People with diabetes hold major responsibility for the day‐to‐day management of their chronic condition. The management that, amongst others, includes blood glucose monitoring, medication taking, ...diet and physical activity, aims at normalizing blood glucose levels. In many individuals, the level of glycaemia, however, frequently exceeds the recommendations. This observation, together with patients' and practitioners' reports, suggests that active self‐management is suboptimal. Various reasons, both individual and environment related, contribute to the suboptimal concordance with treatment regimen. The aim of this review is to discuss some of the barriers to optimal diabetes self‐management.
The American Diabetes Association, JDRF, the European Association for the Study of Diabetes, and the American Association of Clinical Endocrinologists convened a research symposium, "The ...Differentiation of Diabetes by Pathophysiology, Natural History and Prognosis" on 10-12 October 2015. International experts in genetics, immunology, metabolism, endocrinology, and systems biology discussed genetic and environmental determinants of type 1 and type 2 diabetes risk and progression, as well as complications. The participants debated how to determine appropriate therapeutic approaches based on disease pathophysiology and stage and defined remaining research gaps hindering a personalized medical approach for diabetes to drive the field to address these gaps. The authors recommend a structure for data stratification to define the phenotypes and genotypes of subtypes of diabetes that will facilitate individualized treatment.
Aim: Assess safety/tolerability and efficacy of the DPP‐4 inhibitor vildagliptin in 515 patients with type 2 diabetes mellitus (T2DM) and moderate or severe renal impairment (RI).
Methods: ...Double‐blind, randomized, parallel‐group, placebo‐controlled, 24‐week clinical trial assessing safety and efficacy of vildagliptin (50 mg qd) added to current antidiabetic therapy, in patients with T2DM and moderate or severe RI (GFR ≥ 30 to <50 or <30 ml/min/1.73 m2).
Results: The study population comprised of 165 and 129 patients with moderate RI and 124 and 97 patients with severe RI randomized to vildagliptin and placebo, respectively, with most patients receiving background insulin therapy (68 and 81% for moderate and severe RI, respectively). After 24 weeks, the between‐treatment difference in the adjusted mean change in A1C was −0.5 ± 0.1% (p < 0.0001) in moderate RI (baseline A1C = 7.9%) and −0.6 ± 0.1% (p < 0.0001) in severe RI (baseline A1C = 7.7%). In patients with moderate RI, similar proportions of those receiving vildagliptin or placebo experienced any AE (68 vs. 73%), any SAE (9 vs. 9%), any AE leading to discontinuation (3 vs. 5%) or death (1 vs. 1%). This was also true for patients with severe RI: AEs (73 vs. 74%), SAEs (19 vs. 21%), AEs leading to discontinuation (9 vs. 6%) and death (2 vs. 4%).
Conclusions: In this 24‐week study of 515 patients with T2DM and moderate or severe RI, vildagliptin added to ongoing antidiabetic therapy had a safety profile similar to placebo. Further, relative to placebo, vildagliptin elicited a statistically and clinically significant decrease in A1C in patients with moderate or severe RI.
Background
We aimed to assess whether remnant cholesterol concentration and variability predict the progression of diabetic nephropathy (DN) and severe diabetic retinopathy (SDR) in type 1 diabetes.
...Methods
This observational prospective study covered 5150 FinnDiane Study participants. Remnant cholesterol was calculated as total cholesterol – LDL cholesterol – HDL cholesterol and variability as the coefficient of variation. DN category was based on consensus albuminuria reference limits and the progression status was confirmed from medical files. SDR was defined as retinal laser treatment. For 1338 individuals, the severity of diabetic retinopathy (DR) was graded using the ETDRS classification protocol. Median (IQR) follow‐up time was 8.0 (4.9–13.7) years for DN and 14.3 (10.4–16.3) for SDR.
Results
Remnant cholesterol (mmol L−1) was higher with increasing baseline DN category (P < 0.001). A difference was also seen comparing non‐progressors (0.41 0.32–0.55) with progressors (0.55 0.40–0.85), P < 0.001. In a Cox regression analysis, remnant cholesterol predicted DN progression, independently of diabetes duration, sex, HbA1c, systolic blood pressure, smoking, BMI, estimated glucose disposal rate and estimated glomerular filtration rate (HR: 1.51 1.27–1.79). Remnant cholesterol was also higher in those who developed SDR (0.47 0.36–0.66) than those who did not (0.40 0.32–0.53), P < 0.001, and the concentration increased stepwise with increasing DR severity (P < 0.001). Regarding SDR, the HR for remnant cholesterol was 1.52 (1.26–1.83) with the most stringent adjustment. However, remnant cholesterol variability was not independently associated with the outcomes.
Conclusions
Remnant cholesterol concentration, but not variability, predicts DN progression and development of SDR. However, it remains to be elucidated whether the associations are causal or not.
Background
Type 1 diabetes (T1D) is an autoimmune disease affecting individuals in the early years of life. Although previous studies have identified genetic loci influencing T1D diagnosis age, these ...studies did not investigate the genome with high resolution.
Objective and methods
We performed a genome‐wide meta‐analysis for age at diagnosis with cohorts from Finland (Finnish Diabetic Nephropathy Study), the United Kingdom (UK Genetic Resource Investigating Diabetes) and Sardinia. Through SNP associations, transcriptome‐wide association analysis linked T1D diagnosis age and gene expression.
Results
We identified two chromosomal regions associated with T1D diagnosis age: multiple independent variants in the HLA region on chromosome 6 and a locus on chromosome 17q12. We performed gene‐level association tests with transcriptome prediction models from two whole blood datasets, lymphocyte cell line, spleen, pancreas and small intestine tissues. Of the non‐HLA genes, lower PNMT expression in whole blood, and higher IKZF3 and ZPBP2, and lower ORMDL3 and GSDMB transcription levels in multiple tissues were associated with lower T1D diagnosis age (FDR = 0.05). These genes lie on chr17q12 which is associated with T1D, other autoimmune diseases, and childhood asthma. Additionally, higher expression of PHF20L1, a gene not previously implicated in T1D, was associated with lower diagnosis age in lymphocytes, pancreas, and spleen. Altogether, the non‐HLA associations were enriched in open chromatin in various blood cells, blood vessel tissues and foetal thymus tissue.
Conclusion
Multiple genes on chr17q12 and PHF20L1 on chr8 were associated with T1D diagnosis age and only further studies may elucidate the role of these genes for immunity and T1D onset.
Aim
Assess long‐term safety and efficacy of the dipeptidlyl peptidase-4 (DPP‐4) inhibitor vildagliptin in 369 patients with type 2 diabetes mellitus (T2DM) and moderate or severe renal impairment ...(RI).
Methods
Double‐blind, randomized, parallel‐group, 52‐week clinical trial comparing safety and efficacy of vildagliptin (50 mg qd, n = 216) and placebo (n = 153) added to ongoing stable antihyperglycaemic treatment, in patients with T2DM and moderate or severe (glomerular filtration rate GFR ≥30 to <50 ml/min/1.73 m2and < 30 ml/min/1.73 m2) RI.
Results
The study population comprised 122 and 89 patients with moderate RI and 94 and 64 patients with severe RI randomized to vildagliptin and placebo, respectively, with the majority of patients receiving background insulin therapy (72% and 82% for moderate and severe RI, respectively). After 1 year, the between‐treatment difference in adjusted mean change in A1C was −0.4 ± 0.2% (p = 0.005) in moderate RI (baseline = 7.8%) and −0.7 ± 0.2% (p < 0.0001) in severe RI (baseline = 7.6%). In patients with moderate RI, similar proportions of patients experienced any adverse event (AE) (84 vs. 85%), any serious adverse event (SAE) (21 vs. 19%), any AE leading to discontinuation (5% vs. 6%) and death (1% vs. 0%) with vildagliptin and placebo, respectively. This was also true for patients with severe RI: AEs (85% vs. 88%), SAEs (25% vs. 25%), AEs leading to discontinuation (10% vs. 6%) and death (3% vs. 2%).
Conclusions
In patients with T2DM and moderate or severe RI, vildagliptin added to ongoing antidiabetic therapy had a safety profile similar to placebo during 1‐year observation. Furthermore, relative to placebo, a clinically significant decrease in A1C was maintained throughout 1‐year treatment with vildagliptin.
Aims
To study the association between dietary intake and glycaemia in Type 1 diabetes.
Methods
Data on energy and nutrient intakes, and the mean and coefficient of variation of self‐monitored blood ...glucose measurements were obtained from records completed by 1000 adults with Type 1 diabetes. Associations between these measures of glycaemia and dietary intake were investigated using generalized linear regression, with and without macronutrient substitution.
Results
In the first set of analyses, fibre intake was associated with lower mean self‐monitored blood glucose values (β = –0.428, 95% CI –0.624 to –0.231; P<0.001). In these same analyses, carbohydrate (β = 0.011, 95% CI 0.002 to 0.020; P=0.014), alcohol (β = 0.013, 95% CI 0.003 to 0.023; P=0.009) and monounsaturated fatty acid intakes (β=0.012, 95% CI 0.001 to 0.023; P=0.029) were associated with higher variability in blood glucose measurements. In the macronutrient substitution analyses, substituting proteins for either carbohydrates (β = –0.026, 95% CI –0.040 to –0.013; P<0.001), fats (β = –0.018, 95% CI –0.033 to –0.004; P=0.014), or alcohol (β = –0.026, 95% CI –0.045 to –0.006; P=0.010), or fats for carbohydrates (β=–0.009, 95% CI –0.017 to –0.001; P=0.030), were all associated with lower variability in the measured blood glucose values. After adjusting for fibre intake, no significant results were observed in analyses of mean self‐monitored blood glucose.
Conclusions
This observational, cross‐sectional study indicates that dietary fibre is associated with lower mean blood glucose concentrations in people with Type 1 diabetes. Glycaemic excursions were reduced when protein was substituted for other macronutrients and when fat replaced carbohydrate, after adjusting for fibre intake.
What's new?
Data on the association between dietary intake and glycaemia in people with Type 1 diabetes are mixed and fibre intake is not always accounted for in analyses.
In this study, conducted in a large cohort of well‐defined individuals with Type 1 diabetes, reported fibre intake was associated with lower mean blood glucose measurements.
Reported protein intake, compared with all other macronutrients, was associated with lower glucose variability.
Background and purpose
Acknowledging the conflicting evidence for diabetes as a predictor of short‐ and long‐term mortality following an intracerebral hemorrhage (ICH), we compared baseline ...characteristics and 30‐day and long‐term mortality between patients with and without diabetes after an ICH, paying special attention to differences between type 1 (T1D) and type 2 (T2D) diabetes.
Methods
Patients with a first‐ever ICH were followed for a median of 2.3 years. Adjusting for demographics, comorbidities and documented ICH characteristics increasing mortality after ICH, logistic regression analysis assessed factors associated with case fatality and 1‐year survival among the 30‐day survivors. Diabetes was compared with patients without diabetes in separate models as (i) any diabetes and (ii) T1D or T2D.
Results
Of our 969 patients, 813 (83.9%) had no diabetes, 41 (4.2%) had T1D and 115 (11.9%) had T2D. Compared with patients without diabetes, those with diabetes were younger, more often men and more frequently had hypertension, coronary heart disease and chronic kidney disease, with similar ICH characteristics. Patients with T1D were younger, more often had chronic kidney disease and brainstem ICH, and less often had atrial fibrillation and lobar ICH, than did patients with T2D. Diabetes had no impact on case fatality. Any diabetes (odds ratio, 2.57; 1.19–5.52), T1D (odds ratio, 7.04; 1.14–43.48) and T2D (odds ratio, 2.32; 1.04–5.17) were independently associated with 1‐year mortality.
Conclusions
Patients with ICH with diabetes exhibited a distinct pattern of comorbidities and disease characteristics with specific differences between T1D and T2D. Despite their younger age, T1D seems to carry a substantially higher likelihood of long‐term mortality after an ICH than does T2D.
Aims/hypothesis Diabetic nephropathy has been associated with low-grade inflammation and activation of the complement system in cross-sectional studies. Data from prospective studies are sparse. We ...investigated the associations of the complement activator mannose-binding lectin (MBL) and the inflammatory marker high-sensitivity C-reactive protein (hsCRP) with the development of nephropathy in a large prospective study of patients with type 1 diabetes from the Finnish Diabetic Nephropathy (FinnDiane) Study. Methods Baseline MBL and hsCRP were measured in 1,564 type 1 diabetes patients from the FinnDiane study, of whom 1,010 had a normal albumin excretion rate, 236 had microalbuminuria and 318 had macroalbuminuria. The main outcome was progression in renal disease during follow-up. Results Both baseline MBL (p = 0.038) and hsCRP (p < 0.001) increased with increasing level of albuminuria. During 5.8 ± 2.2 years of follow-up, progression to a higher albuminuria level or end-stage renal disease (ESRD) occurred in 201 patients. MBL levels were higher in progressors compared with non-progressors at all steps of progression, and in a covariate adjusted multivariate Cox-regression analysis MBL levels above the median were significantly associated with progression from macroalbuminuria to ESRD (hazard ratio 1.88, 95% CI 1.06-3.32, p = 0.030). In a univariate analysis, hsCRP levels above the median were significantly associated with progression from normal albumin excretion rate to microalbuminuria, but the association was only borderline significant after adjustment for covariates (hazard ratio 1.56, 95% CI 0.97-2.51, p = 0.068). Conclusions/interpretation This study demonstrates that concentrations of both MBL and hsCRP are associated with the progression of renal disease in type 1 diabetes.
Background
Diabetes increases the risk of infections and coronary heart disease (CHD). Whether infections increase the risk of CHD and how this applies to individuals with diabetes is unclear.
...Objectives
To investigate the association between bacterial infections and the risk of CHD in type 1 diabetes.
Methods
Individuals with type 1 diabetes (n = 3781) were recruited from the Finnish Diabetic Nephropathy Study (FinnDiane), a prospective follow‐up study. CHD was defined as incident events: fatal or nonfatal myocardial infarction, coronary artery bypass surgery or percutaneous coronary intervention, identified through national hospital discharge register data. Infections were identified through national register data on all antibiotic purchases from outpatient care. Register data were available from 1 January 1995 to 31 December 2015. Bacterial lipopolysaccharide (LPS) activity was measured from serum samples at baseline. Data on traditional risk factors for CHD were collected during baseline and consecutive visits.
Results
Individuals with an incident CHD event (n = 370) had a higher mean number of antibiotic purchases per follow‐up year compared to those without incident CHD (1.34 95% CI: 1.16–1.52, versus 0.79 0.76–0.82, P < 0.001), as well as higher levels of LPS activity (0.64 0.60–0.67, versus 0.58 EU mL−1 0.57–0.59, P < 0.001). In multivariable‐adjusted Cox proportional hazards models, the mean number of antibiotic purchases per follow‐up year was an independent risk factor for incident CHD (HR 1.21, 95% CI: 1.14–1.29, P < 0.0001). High LPS activity was a risk factor for incident CHD (HR 1.93 1.34–2.78, P < 0.001) after adjusting for static confounders.
Conclusion
Bacterial infections are associated with an increased risk of incident CHD in individuals with type 1 diabetes.
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