Management and efficacy of intensified insulin therapy starting in outpatients

Diabetic patients under multiple injection insulin therapy (i.e., intensified insulin therapy, IIT) usually start this treatment during hospitalization. We report here on the logistics, efficacy, and safety of IIT, started in outpatients. Over 8 months, 52 type I and type II diabetics were followed up whose insulin regimens consecutively had been changed from conventional therapy to IIT. Two different IIT strategies were compared: free mixtures of regular and intermediate (12 hrs)-acting insulin versus the basal and prandial insulin treatment with preprandial injections of regular insulin, and ultralente (24 hrs-acting) or intermediate insulin for the basal demand. After 8 months HbA1 levels had decreased from 10.6%±2.4% to 8.0%±1.3% (means±SD). There was no difference between the two regimens with respect to metabolic control; but type II patients maintained the lowered HbA1 levels better than type I patients. Only two patients were hospitalized during the follow-up time because of severe hypoglycemia. An increase of body weight due to the diet liberalization during IIT became a problem in one-third of the patients. Our results suggest that outpatient initiation of IIT is safe and efficacious with respect to near-normoglycemic control. Weight control may become a problem in IIT patients

Patterns of Regional Brain Atrophy and Brain Aging in Middle- and Older-Aged Adults With Type 1 Diabetes

Importance: Little is known about structural brain changes in type 1 diabetes (T1D) and whether there are early manifestations of a neurodegenerative condition like Alzheimer disease (AD) or evidence of premature brain aging. Objective: To evaluate neuroimaging markers of brain age and AD-like atrophy in participants with T1D in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study, identify which brain regions are associated with the greatest changes in patients with T1D, and assess the association between cognition and brain aging indices. Design, Setting, and Participants: This cohort study leveraged data collected during the combined DCCT (randomized clinical trial, 1983-1993) and EDIC (observational study, 1994 to present) studies at 27 clinical centers in the US and Canada. A total of 416 eligible EDIC participants and 99 demographically similar adults without diabetes were enrolled in the magnetic resonance imaging (MRI) ancillary study, which reports cross-sectional data collected in 2018 to 2019 and relates it to factors measured longitudinally in DCCT/EDIC. Data analyses were performed between July 2020 and April 2022. Exposure: T1D diagnosis. Main Outcomes and Measures: Psychomotor and mental efficiency were evaluated using verbal fluency, digit symbol substitution test, trail making part B, and the grooved pegboard. Immediate memory scores were derived from the logical memory subtest of the Wechsler memory scale and the Wechsler digit symbol substitution test. MRI and machine learning indices were calculated to predict brain age and quantify AD-like atrophy. Results: This study included 416 EDIC participants with a median (range) age of 60 (44-74) years (87 of 416 [21%] were older than 65 years) and a median (range) diabetes duration of 37 (30-51) years. EDIC participants had consistently higher brain age values compared with controls without diabetes, indicative of approximately 6 additional years of brain aging (EDIC participants: β, 6.16; SE, 0.71; control participants: β, 1.04; SE, 0.04; P <.001). In contrast, AD regional atrophy was comparable between the 2 groups. Regions with atrophy in EDIC participants vs controls were observed mainly in the bilateral thalamus and putamen. Greater brain age was associated with lower psychomotor and mental efficiency among EDIC participants (β, -0.04; SE, 0.01; P <.001), but not among controls. Conclusions and Relevance: The findings of this study suggest an increase in brain aging among individuals with T1D without any early signs of AD-related neurodegeneration. These increases were associated with reduced cognitive performance, but overall, the abnormal patterns seen in this sample were modest, even after a mean of 38 years with T1D

Quality of life in Type 1 (insulin-dependent) diabetic patients prior to and after pancreas and kidney transplantation in relation to organ function

Improvement of the quality of life in Type 1 (insulin-dependent) diabetic patients with severe late complications is one of the main goals of pancreas and/or kidney grafting. To assess the influences of these treatment modalities on the different aspects of the quality of life a cross-sectional study in 157 patients was conducted. They were categorized into patients pre-transplant without dialysis (n=29; Group A), pre-transplant under dialysis (n=44; Group B), post-transplant with pancreas and kidney functioning (n=31; Group C), post-transplant with functioning kidney, but insulin therapy (n=29; Group D), post-transplant under dialysis and insulin therapy again (n=15; Group E) and patients after single pancreas transplantation and rejection, with good renal function, but insulin therapy (n=9; Group F). All patients answered a mailed, self-administered questionnaire (217 questions) consisting of a broad spectrum of rehabilitation criteria. The results indicate a better quality of life in Groups C and D as compared to the other groups. In general the scores are highest in C, but without any significant difference to D. Impressive significant differences between C or D and the other groups were found especially in their satisfaction with physical capacity, leisure-time activities or the overall quality of life. The satisfaction with the latter is highest in C (mean±SEM: 4.0±0.2 on a 1 to 5-rating scale; significantly different from A: 3.1±0.1, B: 2.7±0.2 and E: 2.6±0.3; p<0.01), followed by D (3.8±0.2; significantly different from B and E; p<0.01). Group F shows a mean of 3.1±0.4, which is not significantly different from C. The percentages of patients in each group, who are not working: A: 38 %, B: 64 %, C: 74 %, D: 66 %, E: 87 % and F: 78 % indicate that there is no marked improvement in the vocational situation after successful grafting

HbA_1c variability is associated with increased mortality and earlier hospital admission in people with Type 1 diabetes

Aim: Despite evidence of morbidity, no evidence exists on the relationship between HbA1c variability and mortality in Type 1 diabetes. We performed an observational study to investigate whether the association between HbA1c variability and mortality exists in a population of people with Type 1 diabetes. As a secondary outcome, we compared onset of first hospital admission between groups. Methods: People with Type 1 diabetes were identified for inclusion from the Scottish Care Information – Diabetes data set. This database includes data of all people known to have diabetes who live within Scotland. A survival analysis was carried out over a 47‐month period comparing two groups; group 1 with a HbA1c coefficient of variation (CV) above the median CV value, and group 2 with a CV below the median value. Time to death or first admission was also analysed. A Cox proportional hazard model was used to compare time to death, adjusting for appropriate covariables. Results: Some 6048 individuals with Type 1 diabetes were included in the analysis. Median HbA1c CV was 7.9. The hazard ratio (HR) for mortality for those with an HbA1c CV above the median value is 1.5 over 47 months of follow‐up (P &lt; 0.001). HR for survival to either the first admission to hospital or death for those with an HbA1c CV above the median value was 1.35 (95% confidence interval 1.25–1.45) over 730 days of follow‐up (P &lt; 0.001). Conclusion: Our results show that people with greater HbA1c variability have a higher rate of mortality and earlier hospital admission in Type 1 diabetes

Prevalence of diabetic peripheral neuropathy and relation to glycemic control therapies at baseline in the BARI 2D cohort

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74968/1/j.1529-8027.2009.00200.x.pd

Flash Glucose-Sensing Technology as a Replacement for Blood Glucose Monitoring for the Management of Insulin-Treated Type 2 Diabetes: a Multicenter, Open-Label Randomized Controlled Trial

Introduction Glycemic control in participants with insulin-treated diabetes remains challenging. We assessed safety and efficacy of new flash glucose-sensing technology to replace self-monitoring of blood glucose (SMBG). Methods This open-label randomized controlled study (ClinicalTrials.gov, NCT02082184) enrolled adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers. Following 2 weeks of blinded sensor wear, 2:1 (intervention/control) randomization (centrally, using biased-coin minimization dependant on study center and insulin administration) was to control (SMBG) or intervention (glucose-sensing technology). Participants and investigators were not masked to group allocation. Primary outcome was difference in HbA1c at 6 months in the full analysis set. Prespecified secondary outcomes included time in hypoglycemia, effect of age, and patient satisfaction. Results Participants (n = 224) were randomized (149 intervention, 75 controls). At 6 months, there was no difference in the change in HbA1c between intervention and controls: −3.1 ± 0.75 mmol/mol, [−0.29 ± 0.07% (mean ± SE)] and −3.4 ± 1.04 mmol/mol (−0.31 ± 0.09%) respectively; p = 0.8222. A difference was detected in participants aged <65 years [−5.7 ± 0.96 mmol/mol (−0.53 ± 0.09%) and −2.2 ± 1.31 mmol/mol (−0.20 ± 0.12%), respectively; p = 0.0301]. Time in hypoglycemia <3.9 mmol/L (70 mg/dL) reduced by 0.47 ± 0.13 h/day [mean ± SE (p = 0.0006)], and <3.1 mmol/L (55 mg/dL) reduced by 0.22 ± 0.07 h/day (p = 0.0014) for intervention participants compared with controls; reductions of 43% and 53%, respectively. SMBG frequency, similar at baseline, decreased in intervention participants from 3.8 ± 1.4 tests/day (mean ± SD) to 0.3 ± 0.7, remaining unchanged in controls. Treatment satisfaction was higher in intervention compared with controls (DTSQ 13.1 ± 0.50 (mean ± SE) and 9.0 ± 0.72, respectively; p < 0.0001). No serious adverse events or severe hypoglycemic events were reported related to sensor data use. Forty-two serious events [16 (10.7%) intervention participants, 12 (16.0%) controls] were not device-related. Six intervention participants reported nine adverse events for sensor-wear reactions (two severe, six moderate, one mild). Conclusion Flash glucose-sensing technology use in type 2 diabetes with intensive insulin therapy results in no difference in HbA1c change and reduced hypoglycemia, thus offering a safe, effective replacement for SMBG

Practical steps to improving the management of type 1 diabetes: recommendations from the Global Partnership for Effective Diabetes Management

The Diabetes Control and Complications Trial (DCCT) led to considerable improvements in the management of type 1 diabetes, with the wider adoption of intensive insulin therapy to reduce the risk of complications. However, a large gap between evidence and practice remains, as recently shown by the Pittsburgh Epidemiology of Diabetes Complications (EDC) study, in which 30-year rates of microvascular complications in the ‘real world’ EDC patients were twice that of DCCT patients who received intensive insulin therapy. This gap may be attributed to the many challenges that patients and practitioners face in the day-to-day management of the disease. These barriers include reaching glycaemic goals, overcoming the reality and fear of hypoglycaemia, and appropriate insulin therapy and dose adjustment. As practitioners, the question remains: how do we help patients with type 1 diabetes manage glycaemia while overcoming barriers? In this article, the Global Partnership for Effective Diabetes Management provides practical recommendations to help improve the care of patients with type 1 diabetes