A multi-center, randomized, crossover trial consisting of three sequential 12-week periods, with the HCL feature used during one period, the PLGS feature used during one period and SAP therapy (control) during one period. The crossover trial will be preceded by a run-in phase in which participants will receive training using the study devices (Dexcom G6 and Tandem t:slim X2 pump). After the last crossover period, participants will be given the opportunity to use study devices for an additional 12 weeks to assess preference of system use (PLGS, HCL or SAP) and associated characteristics, durability and safety in a more real-world setting with less frequent study contact.
Automated insulin delivery (AID) technologies hold the promise of optimizing glycemic control and reducing the burden of diabetes care for patients with Type 1 Diabetes (T1D). However, clinical trials of lower burden AID technologies have not included older adults in sufficient numbers to allow for focused evaluation of efficacy and quality of life (QOL) impacts that may differ from those observed in younger age groups. Most notably, primary endpoints have focused on reducing hyperglycemia, while avoidance of hypoglycemia is of upmost concern for older adults with T1D. T1D Exchange clinic registry data have shown severe hypoglycemia (SH) occurs more commonly in older adults with longstanding T1D than in younger individuals with events occurring just as often with HbA1c levels \>8.0% as with HbA1c levels \<7.0%. These data do not support the strategy of "raising the HbA1c" as being an effective approach for hypoglycemia prevention in older adults with T1D. In addition to acutely altered mental status, hypoglycemia is associated with an increased risk for falls leading to fractures, car accidents, emergency room (ER) visits, hospitalizations, and mortality resulting in substantial societal costs. The occurrence of hypoglycemia, hypoglycemia unawareness and fear of hypoglycemia have adverse effects on overall QOL of both individuals with T1D and their families. While continuous glucose monitoring (CGM) technology alone has the potential to be beneficial in reducing hypoglycemia in older patients, our preliminary data from the Wireless Innovations for Seniors with Diabetes Mellitus (WISDM) trial shows a majority of patients still have frequent hypoglycemia even when using CGM. Thus, knowledge of CGM alone may not be sufficient to avoid hypoglycemia in this population. Predictive low-glucose suspend algorithms have particular promise when the primary goal is hypoglycemia avoidance rather than glucose reduction. Whether the added complexity of closed loop systems provides additional glycemic benefit is not known. There is a critical need to determine whether automated insulin delivery can reduce hypoglycemia in the older adult population with T1D.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
NONE
Enrollment
82
The system components include the t:slim X2 with Control-IQ Technology and the Dexcom CGM G6. The modular control algorithm has a safety supervision module that limits insulin delivery to prevent hypoglycemia at all times. The algorithm gradually decreases hyperglycemia from bedtime to reach a target of 120 mg/dL by waking time. During awake hours, the control algorithm attempts to maintain glucose within a target range (112.5 to 160 mg/dL) with meal time insulin boluses delivered based on usual bolus procedures undertaken by patients on an insulin pump (Hybrid closed loop). The system components include the t:slim X2 with with Basal-IQ Technology and the Dexcom CGM G6. The PLGS System is able to stop and resume basal insulin delivery automatically in response to predicted or low sensor glucose values, thereby reducing the incidence and duration of hypoglycemic episodes. The pump includes the hypoglycemia minimization strategy that will issue insulin delivery commands.
AdventHealth Diabetes Institute
Orlando, Florida, United States
Mayo Clinic
Rochester, Minnesota, United States
SUNY Upstate
Syracuse, New York, United States
University of Pennsylvania
Philadelphia, Pennsylvania, United States
CGM Measured Time <70 mg/dL
Primary Outcome: Percentage of sensor glucose values \<70 mg/dL. The first 4 weeks of CGM data in each period were excluded to reduce the chance of a carryover effect. A minimum of 168 hours of data was required to calculate CGM metrics. Since the hypoglycemia endpoints had skewed distributions, values were winsorized at the 10th and 90th percentiles.
Time frame: weeks 5-12 of 12 weeks for each intervention of the crossover
CGM Measured Time <54 mg/dL
Percentage of sensor glucose values \<54 mg/dL. The first 4 weeks of CGM data in each period were excluded to reduce the chance of a carryover effect. A minimum of 168 hours of data was required to calculate CGM metrics. Since the hypoglycemia endpoints had skewed distributions, values were winsorized at the 10th and 90th percentiles.
Time frame: weeks 5-12 of 12 weeks for each intervention of the crossover
Hypoglycemia
Rate of CGM-measured hypoglycemic events per week. A hypoglycemic event is defined as 15 consecutive minutes with a sensor glucose value \<54 mg/dl. At least 2 sensor values \<54 mg/dl that are 15 or more minutes apart plus no intervening values \>54 mg/dl are required to define an event. The end of the hypoglycemic event is defined as a minimum of 15 consecutive minutes with a sensor glucose concentration \>70 mg/dl. At least 2 sensor values \>70 mg/dl that are 15 or more minutes apart with no intervening values \<70 mg/dl, are required to define the end of an event. When a hypoglycemic event ends, the study participant becomes eligible for a new event.
Time frame: weeks 5-12 of 12 weeks for each arm of the crossover
Glucose Control
Mean glucose (mg/dL)
Time frame: weeks 5-12 of 12 weeks for each arm of the crossover
% Time 70-180 mg/dL
Percentage of sensor glucose values 70 to 180 mg/dL. The first 4 weeks of CGM data in each period were excluded to reduce the chance of a carryover effect. A minimum of 168 hours of data was required to calculate CGM metrics.
Time frame: weeks 5-12 of 12 weeks for each intervention of the crossover
Glucose Control - Coefficient of Variation
Coefficient of variation (%)
Time frame: weeks 5-12 of 12 weeks for each arm of the crossover
% Time > 180 mg/dL
Percentage of values \>180 mg/dL. The first 4 weeks of CGM data in each period were excluded to reduce the chance of a carryover effect. A minimum of 168 hours of data was required to calculate CGM metrics.
Time frame: weeks 5-12 of 12 weeks for each intervention of the crossover
% Time > 250 mg/dL
Percentage of values \>250 mg/dL. The first 4 weeks of CGM data in each period were excluded to reduce the chance of a carryover effect. A minimum of 168 hours of data was required to calculate CGM metrics.
Time frame: weeks 5-12 of 12 weeks for each intervention of the crossover
HbA1c
HbA1c %
Time frame: at 12 week visit for each arm of the crossover
Hypoglycemia Unawareness - Gold Survey
The Gold score asks subjects to indicate their awareness of hypoglycemia with '1' being always aware and '7' being never aware. Score scale 1-7; A higher score indicates more unawareness.
Time frame: at 12 week visit for each arm of the crossover
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