Continuous Glucose Monitoring in Older Adults: What We Know and What We Have Yet to Learn.

OBJECTIVE: To assess the growing use of continuous glucose monitoring (CGM) systems by older adults and explore additional areas integration that could benefit adults with frailty. BACKGROUND: The use of CGM devices has expanded rapidly in the last decade. This has been supported by substantial data showing significant benefit in glycemic metrics: hemoglobin A1c improvements, less hypoglycemia, and improved quality of life. However, sub-populations, such as older persons, exist where available data are limited. Furthermore, frail older adults represent a heterogeneous population with their own unique challenges to the management of diabetes. This group has some of the poorest outcomes related to the sequela of diabetes. For example, hypoglycemia resulting in significant morbidity and mortality is more frequent in older person with diabetes than in younger persons with diabetes. METHOD: We present a concise literature review on CGM use in the older adult as well as expand upon glycemic and nonglycemic benefits of CGM for patients, caregivers, and providers. Retrospective analysis of inpatient glycemic data of 16,935 older adults with Type 2 diabetes mellitus at Atrium Health Wake Forest Baptist indicated those with fraility managed with insulin or sulfonylurea had the highest rates of delirium (4.8%), hypoglycemia (3.5%), cardiovascular complications (20.2%) and ED visits/hospitalizatoins (49%). In addition, we address special consideration of specific situations including inpatient, palliative and long term care settings. CONCLUSION: This review article summarizes the available data for CGM use in older adults, discusses the benefits and obstacles with CGM use in this population, and identifies areas of future research needed for improved delivery of care to older persons with diabetes.

Long-term Impact of a 10-Year Intensive Lifestyle Intervention on a Deficit Accumulation Frailty Index: Action for Health in Diabetes Trial.

BACKGROUND: Multidomain lifestyle interventions may slow aging as captured by deficit accumulation frailty indices; however, it is unknown whether benefits extend beyond intervention delivery. METHODS: We developed a deficit accumulation frailty index (FI-E) to span the 10 years that the Action for Health in Diabetes (Look AHEAD) randomized controlled clinical trial delivered interventions (a multidomain lifestyle intervention focused on caloric restriction, increased physical activity, and diet compared to a control condition) and to extend across an additional 8 years post-delivery. The study cohort included 5 145 individuals, aged 45-76 years at enrollment, who had type 2 diabetes and either obesity or overweight. RESULTS: Overall, FI-E scores were relatively lower among lifestyle participants throughout follow-up, averaging 0.0130 [95% confidence interval: 0.0104, 0.0156] (p < .001) less across the 18 years. During Years 1-8, the mean relative difference between control and lifestyle participants' FI-E scores was 0.0139 [0.0115, 0.0163], approximately 10% of the baseline level. During Years 9-18, this average difference was 0.0107 [0.0066, 0.0148]. Benefits were comparable for individuals grouped by baseline age and body mass index and sex but were not evident for those entering the trial with a history of cardiovascular disease. CONCLUSIONS: Multidomain lifestyle intervention may slow biological aging long term, as captured by an FI-E. Clinical Trials Registration Number: NCT00017953.

Efficacy of Control-IQ Technology in a General Endocrine Clinic.

OBJECTIVE: Recent advances in technology have allowed for the expanded use of hybrid closed-loop insulin pump therapy and automated insulin delivery systems for the management of diabetes mellitus. We assessed the outcomes of introducing Tandem t:slim X2 with the Control-IQ technology in a general endocrine clinic. METHODS: Data from 66 adults with type 1 (n = 61) and type 2 (n = 5) diabetes mellitus were aggregated for analysis. Patients were either transitioned from traditional insulin pump therapy or multiple daily injection therapy to Tandem t:slim X2 with the Control-IQ technology from January 2020 to June 2021. The assessed clinical end points included changes in time below range, time above range, and time in target range. Changes in hemoglobin A1C before and after Control-IQ technology implementation were noted. The primary outcome was a change in time in target range with the Control-IQ technology. RESULTS: There was a significant increase in time in target range when comparing pre- and post-Control-IQ technology (49.5% vs 63.3%, P < .0003) values. There was a reduction in time above range (46.8% vs 34.9%, P < .0013), a decrease in time below range (4.0% vs 1.7%, P = .017), and a decrease in hemoglobin A1C after transitioning to the Control-IQ technology (7.7% [61 mmol/mol] vs 7.1% [54 mmol/mol], P < .017). The patient dropout rate was low (7%). CONCLUSION: The Control-IQ technology system was effective in reducing hyperglycemia while increasing time in target range and decreasing hypoglycemia. This technology is a useful and effective addition to the growing number of automated insulin delivery systems. The clinical outcomes mirror the results found in the key adult pivotal trials.

Using an Electronic Health Record and Deficit Accumulation to Pragmatically Identify Candidates for Optimal Prescribing in Patients With Type 2 Diabetes.

Objective: Despite guidelines recommending less stringent glycemic goals for older adults with type 2 diabetes, overtreatment is prevalent. Pragmatic approaches for prioritizing patients for optimal prescribing are lacking. We describe glycemic control and medication patterns for older adults with type 2 diabetes in a contemporary cohort, exploring variability by frailty status. Research Design and Methods: This was a cross-sectional observational study based on electronic health record (EHR) data, within an accountable care organization (ACO) affiliated with an academic medical center/health system. Participants were ACO-enrolled adults with type 2 diabetes who were ≥65 years of age as of 1 November 2020. Frailty status was determined by an automated EHR-based frailty index (eFI). Diabetes management was described by the most recent A1C in the past 2 years and use of higher-risk medications (insulin and/or sulfonylurea). Results: Among 16,973 older adults with type 2 diabetes (mean age 75.2 years, 9,154 women [53.9%], 77.8% White), 9,134 (53.8%) and 6,218 (36.6%) were classified as pre-frail (0.10 < eFI ≤0.21) or frail (eFI >0.21), respectively. The median A1C level was 6.7% (50 mmol/mol) with an interquartile range of 6.2-7.5%, and 74.1 and 38.3% of patients had an A1C <7.5% (58 mmol/mol) and <6.5% (48 mmol/mol), respectively. Frailty status was not associated with level of glycemic control (P = 0.08). A majority of frail patients had an A1C <7.5% (58 mmol/mol) (n = 4,544, 73.1%), and among these patients, 1,755 (38.6%) were taking insulin and/or a sulfonylurea. Conclusion: Treatment with insulin and/or a sulfonylurea to an A1C levels <7.5% is common in frail older adults. Tools such as the eFI may offer a scalable approach to targeting optimal prescribing interventions.

Telehealth Technologies and Their Benefits to People With Diabetes.

This article reviews the current diabetes technology landscape and how recent advancements are being used to help overcome barriers in the management of diabetes. The authors offer case examples of how digital tools and platforms can facilitate diabetes care via telehealth and remote patient monitoring for individuals in special populations. They also provide tips to ensure success in implementing diabetes technology to provide the best possible care for people with diabetes in outpatient settings.

Real-World Efficacy of the Hybrid Closed-Loop System.

BACKGROUND: Hybrid closed-loop (HCL) insulin pump therapy (Medtronic 670G) is an emerging technology that is growing in use worldwide. Initial clinical trials demonstrated the effectiveness of HCL in reducing hypoglycemia and improving glucose control; however, these subjects were intensely monitored and supervised. There has been concern regarding the ability of patients to remain in auto mode. We aimed to assess HCL when used in a typical outpatient endocrine clinic. METHODS: We initially analyzed data from 80 individuals with type 1 diabetes managed in an endocrine clinic by a single certified diabetes educator (CDE). We then included our other providers and had 230 subjects by the end of the study. Patients were either transitioned from traditional insulin pump or multiple daily insulin injection therapy (MDI) to HCL. Patients initiated to HCL pump therapy from July 2017 through February 2020 were studied. Endpoints of change in time in hypoglycemic/hyperglycemic range and time in target range were analyzed. The primary outcome was a change in percent time in the target range during manual mode compared with auto mode. RESULTS: There was an 18.2% increase in average time in target range when comparing manual mode to auto mode (59.3% vs 70.1%, P < .0001). Average time in hyperglycemic range was significantly reduced by 26.7% (39.0% vs 28.6%, P < .0001) but without increasing average time in hypoglycemic range (1.7% vs 1.3%, P = 0.95). CONCLUSIONS: HCL was effective in reducing hyperglycemia and increasing time in the target range but did not increase hypoglycemia. These data suggest HCL will improve the metrics of glucose control.

Influence of Diabetes Mellitus on Outcomes in Patients After Left Ventricular Assist Device Implantation.

BACKGROUND: Despite previous studies, the mortality risk of patients with diabetes mellitus after left ventricular assist device (LVAD) implant remains unclear. In addition, the relationship between the degree of glycemic control and long-term mortality risk in LVAD patients with diabetes has not been established. METHODS: Ninety-five nondiabetic patients and 96 diabetic patients from the University of Rochester Medical Center who received a HeartMate II (Thoratec, Pleasanton, CA) continuous-flow LVAD between May 2008 and June 2014 were included in this study. The primary outcome was all-cause mortality. Secondary outcomes included rates of infection, neurologic dysfunction, renal dysfunction, and rehospitalization. Kaplan-Meier survival analyses and Cox models were utilized. RESULTS: During follow-up, 32 diabetic patients (33%) and 15 nondiabetic patients (16%) died after LVAD implantation. Cumulative probability of death was higher for diabetic patients when compared with nondiabetic patients (42% versus 21% at 3 years, p = 0.013). There were no significant differences in overall rates of infection, neurologic dysfunction, and rehospitalization between the two groups. However, after an initial secondary outcome event, diabetic patients continued to have a higher mortality rate when compared with nondiabetic patients. There was no statistically significant difference in the risk of death between diabetic patients with pre-LVAD hemoglobin A1c less than 7.0% and diabetic patients with pre-LVAD hemoglobin A1c 7.0% or greater (hazard ratio 1.71, 95% confidence interval: 0.72 to 4.08, p = 0.223). CONCLUSIONS: Diabetic patients who underwent LVAD implantation had a higher risk of death compared with nondiabetic patients. Adverse event rates did not differ between the two groups. Finally, the degree of glycemic control in diabetic patients before LVAD was not found to influence mortality.