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Program Chair’s Summary and Vision Statement .The Foundational Role of Sensor-Based Glucose Monitoring Technology—How Should Clinicians and Patients Collaborate and Use Sensor-Based Technology to Improve Diabetes Care?
From MDI to the MiniMed™ 670G system: a 10-day Initiation Protocol
WORKSHOP IS ORGANIZED AND SUPPORTED BY Medtronic
The brain as a target of diabetes complications in children
Background and Aims / Part 1
Severe hypoglycemia may affect the developing brain, yet exposure to chronic hyperglycemia may also adversely impact brain development, particularly in children with early-onset T1D. In the Diabetes Research in Children Network, we are studying cognitive and neurodevelopmental consequences of T1D in a cohort of 144 children (initially 4-9 years old), and 70 age-matched non-diabetic controls.
Methods / Part 2
We performed unsedated structural MRI, using contemporary software, and age-appropriate cognitive testing. Lifetime A1c and glucose sensor data were also assessed.
Results / Part 3
We observed significant differences in total brain, gray matter (GM) and white matter (WM) volumes, and altered WM microstructure in T1D compared to controls, and slower brain growth after longitudinal, 18-months follow-up. These differences were highly correlated with metrics of hyperglycemia. Subsequent longitudinal follow-up through puberty shows that children with T1D had slower growth of total cortical and subcortical GM and WM than controls at all time-points; also lower verbal IQ and working memory scores, differences again associated with higher lifetime A1c. Using functional MRI, brain activation patterns showed increased recruitment of executive control areas in T1D, which possibly act to offset diabetes-related impairments in the default mode network (the brain’s “idle “system). We posit these findings may be compensatory mechanisms to facilitate cognitive and behavioral performance.
Conclusions / Part 4
In conclusion, these and other studies demonstrate that hyperglycemia is detrimental to the developing brain during the critical period of rapid brain maturation in children. The impact of improved glycemic control on the brain using artificial pancreas technologies, e.g., is being actively investigated and requires long-term study.
Epidemiologic evidence linking diabetes to cognitive decline and dementia
Background and Aims / Part 1There is growing evidence linking hyperglycemia and diabetes to cognitive decline and dementia risk. Because cognitive decline is a precursor to dementia, identifying risk factors for cognitive decline can suggest avenues for prevention and individuals to target for early intervention. Our results from the Atherosclerosis Risk in Communities (ARIC) Study suggest that prevention of diabetes and maintaining glucose control in midlife may slow or prevent late-life cognitive decline. Cognitive impairment can pose challenges for diabetes management, leading to a cycle of harm whereby diabetes contributes to cognitive dysfunction and cognitive dysfunction leads to poorly controlled diabetes. There is epidemiologic evidence that episodes of sustained hypoglycemia may also contribute to cognitive impairment and dementia, although mechanisms are uncertain. The current evidence suggests a strong link between diabetes and cognitive outcomes. In older adults with diabetes, assessment of cognitive impairment is important, especially in the setting of a history of hypoglycemia.
HYBRID CLOSED-LOOP SYSTEM IMPROVES GLUCOSE CONTROL IN PATIENTS TREATED WITH MULTIPLE DAILY INJECTION AND CGM OR INTEGRATED INSULIN PUMP AND CGM OR SENSOR-AUGMENTED PUMP
Background and Aims
The MiniMed™ 670G Hybrid Closed-Loop (HCL) System improves glucose control and reduces glucose variability. There are no data whether HCL Systems achieve different results in T1DM patients treated with multiple daily injection and continuous glucose monitoring (MDI+CGM) or integrated insulin pump and CGM (CSII+CGM) or sensor-augmented pump therapy with predictive low glucose suspend (PLSG) feature. Aim of our study was to evaluate the effect on metabolic control of the switch from MDI+CGM, CSII+CGM or SAP with PLGS in type 1 diabetic patients.
Baseline clinical characteristics were presented as means and SD. One-way repeated measures ANOVA test was used to verify changes at 12 weeks from baseline in mean blood glucose, SD, TIR, TAR, TBR, Total Insulin dose and % of Basal Insulin.
32 adults with type 1 diabetes (mean age 41,9 + 9,7; duration of diabetes 22 + 12,5; BMI 24,7 + 4,1), who had been using MDI + CGM (n=12) or CSII + CGM (n=11) or SAP therapy (n=9) were evaluated after switching to the 670G System. After 12 weeks a reduction of HbA1c (-0,39% p <0.001), mean glucose and SD (-9,7 mg/dl and 5,8 mg/dl p 0,003 and < 0,001) were observed. TIR increased significantly (+9,7% p < 0,001), in parallel with a reduction in TAR (-8,6% p 0,003) and TBR (-0,87% p 0,044).
Switching to the 670G System significantly improved glucose control in patients previously treated with MDI+CGM and CSII+CGM. Furthermore, similar results were obtained in patients treated with SAP with PLGS feature.