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OBJECTIVE To assess the relationship between the glucose management indicator (GMI) and HbA1c in non-White individuals with diabetes. RESEARCH DESIGN AND METHODS We performed a retrospective analysis of continuous glucose monitoring metrics in individuals with diabetes divided by race into non-White and White cohorts. RESULTS We evaluated 316 individuals (non-White n = 68; White n = 248). Although GMI was not different (7.6 vs. 7.7; P = not significant) between the cohorts, HbA1c was higher in the non-White cohort (8.7% vs. 8.1%; P = 0.004). HbA1c higher than GMI by ≥0.5% was more frequently observed in the non-White cohort (90% vs. 75%; P = 0.02). In the non-White cohort only, duration of hypoglycemia was longer among those with HbA1c higher than GMI by ≥0.5% compared with those with HbA1c and GMI within 0.5%. CONCLUSIONS A differential relationship between HbA1c and GMI in non-White versus White individuals with diabetes was observed. In non-White individuals, a greater difference between HbA1c and GMI was associated with higher risk of hypoglycemia.

Background The COVID-19 lockdown imposed a sudden change in lifestyle with self-isolation and a rapid shift to the use of technology to maintain clinical care and social connections. Objective In this mixed methods study, we explored the impact of isolation during the lockdown on the use of technology in older adults with type 1 diabetes (T1D). Methods Older adults (aged ≥65 years) with T1D using continuous glucose monitoring (CGM) participated in semistructured interviews during the COVID-19 lockdown. A multidisciplinary team coded the interviews. In addition, CGM metrics from a subgroup of participants were collected before and during the lockdown. Results We evaluated 34 participants (mean age 71, SD 5 years). Three themes related to technology use emerged from the thematic analysis regarding the impact of isolation on (1) insulin pump and CGM use to manage diabetes, including timely access to supplies, and changing Medicare eligibility regulations; (2) technology use for social interaction; and (3) telehealth use to maintain medical care. The CGM data from a subgroup (19/34, 56%; mean age 74, SD 5 years) showed an increase in time in range (mean 57%, SD 17% vs mean 63%, SD 15%; P=.001), a decrease in hyperglycemia (>180 mg/dL; mean 41%, SD 19% vs mean 35%, SD 17%; P<.001), and no change in hypoglycemia (<70 mg/dL; median 0.7%, IQR 0%-2% vs median 1.1%, IQR 0%-4%; P=.40) during the lockdown compared to before the lockdown. Conclusions These findings show that our cohort of older adults successfully used technology during isolation. Participants provided the positive and negative perceptions of technology use. Clinicians can benefit from our findings by identifying barriers to technology use during times of isolation and developing strategies to overcome these barriers.

Background: In recent years, professional continuous glucose monitoring (CGM) has become a beneficial tool in pattern management in older adults with type 2 diabetes (T2D) on insulin, however the need for use of professional CGM in this population had not been shown. Methods: We evaluated electronic health record (EHR) data of a tertiary diabetes center to identify the use of professional CGM in patients over the age of 65 years with T2D using insulin. Professional CGM data from this cohort were analyzed when a minimum of 70% of data was available (≥10 days). Results: A total of 2,481 patients over the age of 65 years with type 2 diabetes using insulin were seen at the Joslin Diabetes Center from January 2017-March 2020. Average age of the total cohort was 72±7 yrs, A1c was 8.2±1.5% and diabetes duration was 21±10 years. Professional CGM was used in 169 older adults with T2D using insulin (7% of the total patients seen). CGM data from 139/169 was sufficient for analysis. The average age of this cohort (139 patients) was 77±8 yrs, A1c 8.0±1.5%, duration of diabetes 21±12 yrs. The mean duration of hypoglycemia was 80±92 min/day &lt;70 mg/dL and 32±51 min/day ≤54 mg/dL. A total of 86% of the cohort had ≥1 episode of hypoglycemia. The measure of high glycemic variability (CV &gt;36%) was seen in 59 (42%) of the cohort, with a high A1c (8.2±1.2%). When comparing those people with and without hypoglycemia on CGM, there was no difference in age, A1c, or duration of diabetes. Conclusion: In the real world, a small percentage of older adults with T2D on insulin therapy received professional CGM. Our data shows a high burden of hypoglycemia in this population, despite suboptimal A1c. Broader use of professional CGM would be beneficial in recognizing hypoglycemia in this vulnerable population. Disclosure C. Slyne: None. E. Toschi: Consultant; Self; Medtronic. A. Michals: None. A. Atakov-castillo: None. K. Sifre: None. R. Dewar: None. D. J. Davis: None. M. Munshi: Consultant; Self; Sanofi. Funding National Institutes of Health (1DP3DK112214-01)

Background: Older adults with type 1 diabetes (T1D) face unique challenges, especially when their support structure is disrupted, as happened during the Covid-19 lockdown. We evaluated the clinical and psychological impact of this imposed isolation on the older population with T1D. Methods: We conducted semi-structured interviews with older adults with T1D who were part of an ongoing study, which was paused from March - August 2020. The interviews were performed between May - August 2020, and were transcribed, coded, and analyzed using content analysis to derive theme. A multidisciplinary team of 12 individuals coded the interviews to identify the themes and included geriatricians, endocrinologists, a nurse educator, infomaticists, an economist, a methodologist, and research assistants. Results: We have analyzed 12/35 interviews at this time; mean age 74±4 years, 50% female, 92% non-Hispanic white, mean duration of diabetes 37±18 years, and A1C 7.3±0.7%. Three main themes have emerged. The challenges related to diabetes care included fear of hypoglycemia, interruption in supply chain related to diabetes technology (insulin pump and continuous glucose monitoring (CGM) supplies), use of telehealth, diabetes-related distress, and adapting to new routines in self-care (diet and exercise). Challenges related to the Covid-19 pandemic included fear of getting Covid-19 infection, and a lack of reliable information on pandemic. The challenges related to psychological well-being included a feeling of isolation, loneliness, inability to spend time with family and friends, lack of in-person communication, and lack of recreational activity. Conclusion: The results of this qualitative study help to understand critical areas of need when social support structures are unavailable to older adults with T1D. Our results will help develop intervention strategies to overcome barriers in maintaining support for this vulnerable population. Disclosure M. Munshi: Consultant; Self; Sanofi. S. Neuwahl: None. S. Cummings: None. S. L. Brown: Stock/Shareholder; Self; Pfizer Inc., Siemens Corporation. K. Weinger: None. E. Toschi: Consultant; Self; Medtronic. C. Slyne: None. K. Sifre: None. D. J. Davis: None. R. Dewar: None. S. M. Sy: None. A. Atakov-castillo: None. A. Michals: None. S. N. Haque: None. Funding National Institutes of Health (1DP3DK112214-01)