Food Insecurity and Hypoglycemia among Older Patients with Type 2 Diabetes Treated with Insulin or Sulfonylureas: The Diabetes & Aging Study.

BACKGROUND: Severe hypoglycemia is a serious adverse drug event associated with hypoglycemia-prone medications; older patients with diabetes are particularly at high risk. Economic food insecurity (food insecurity due to financial limitations) is a known risk factor for hypoglycemia; however, less is known about physical food insecurity (due to difficulty cooking or shopping for food), which may increase with age, and its association with hypoglycemia. OBJECTIVE: Study associations between food insecurity and severe hypoglycemia. DESIGN: Survey based cross-sectional study. PARTICIPANTS: Survey responses were collected in 2019 from 1,164 older (≥ 65 years) patients with type 2 diabetes treated with insulin or sulfonylureas. MAIN MEASURES: Risk ratios (RR) for economic and physical food insecurity associated with self-reported severe hypoglycemia (low blood glucose requiring assistance) adjusted for age, financial strain, HbA1c, Charlson comorbidity score and frailty. Self-reported reasons for hypoglycemia endorsed by respondents. KEY RESULTS: Food insecurity was reported by 12.3% of the respondents; of whom 38.4% reported economic food insecurity only, 21.1% physical food insecurity only and 40.5% both. Economic food insecurity and physical food insecurity were strongly associated with severe hypoglycemia (RR = 4.3; p = 0.02 and RR = 4.4; p = 0.002, respectively). Missed meals ("skipped meals, not eating enough or waiting too long to eat") was the dominant reason (77.5%) given for hypoglycemia. CONCLUSIONS: Hypoglycemia prevention efforts among older patients with diabetes using hypoglycemia-prone medications should address food insecurity. Standard food insecurity questions, which are used to identify economic food insecurity, will fail to identify patients who have physical food insecurity only.

Race and ethnicity and pharmacy dispensing of SGLT2 inhibitors and GLP-1 receptor agonists in type 2 diabetes.

Background: Sodium-Glucose Cotransporter 2 Inhibitors (SGLT2i) and Glucagon-Like Peptide-1 Receptor Agonists (GLP-1 RA) improve cardiorenal outcomes in patients with type 2 diabetes. Equitable use of SGLT2i and GLP-1 RA has the potential to reduce racial and ethnic health disparities. We evaluated trends in pharmacy dispensing of SGLT2i and GLP-1 RA by race and ethnicity. Methods: Retrospective cohort study of patients (≥18 years) with type 2 diabetes using 2014-2022 electronic health record data from six US care delivery systems. Entry was at earliest pharmacy dispensing of any type 2 diabetes medication. We used multivariable logistic regression to evaluate the association between pharmacy dispensing of SGLT2i and GLP1-RA and race and ethnicity. Findings: Our cohort included 687,165 patients (median 6 years of dispensing data; median 60 years; 0.3% American Indian/Alaska Native (AI/AN), 16.6% Asian, 10.5% Black, 1.4% Hawaiian or Pacific Islander (HPI), 31.1% Hispanic, 3.8% Other, and 36.3% White). SGLT2i was lower for AI/AN (OR 0.80, 95% confidence interval 0.68-0.94), Black (0.89, 0.86-0.92) and Hispanic (0.87, 0.85-0.89) compared to White patients. GLP-1 RA was lower for AI/AN (0.78, 0.63-0.97), Asian (0.50, 0.48-0.53), Black (0.86, 0.83-0.90), HPI (0.52, 0.46-0.57), Hispanic (0.69, 0.66-0.71), and Other (0.78, 0.73-0.83) compared to White patients. Interpretation: Dispensing of SGLT2is, and GLP-1 RAs was lower in minority group patients. There is a need to evaluate approaches to increase use of these cardiorenal protective drugs in patients from racial and ethnic minority groups with type 2 diabetes to reduce adverse cardiorenal outcomes and improve health equity. Funding: Patient-Centered Outcomes Research Institute and National Institutes of Health.

Willingness to take less medication for type 2 diabetes among older patients: The Diabetes & Aging Study.

BACKGROUND: To examine the willingness of older patients to take less diabetes medication (de-intensify) and to identify characteristics associated with willingness to de-intensify treatment. METHODS: Survey conducted in 2019 in an age-stratified, random sample of older (65-100 years) adults with diabetes on glucose-lowering medications in the Kaiser Permanente Northern California Diabetes Registry. We classified survey responses to the question: "I would be willing to take less medication for my diabetes" as willing, neutral, or unwilling to de-intensify. Willingness to de-intensify treatment was examined by several clinical characteristics, including American Diabetes Association (ADA) health status categories used for individualizing glycemic targets. Analyses were weighted to account for over-sampling of older individuals. RESULTS: A total of 1337 older adults on glucose-lowering medication(s) were included (age 74.2 ± 6.0 years, 44% female, 54.4% non-Hispanic white). The proportions of participants willing, neutral, or unwilling to take less medication were 51.2%, 27.3%, and 21.5%, respectively. Proportions of willing to take less medication varied by age (65-74 years: 54.2% vs. 85+ years: 38.5%) and duration of diabetes (0-4 years: 61.0% vs. 15+ years: 44.2%), both p < 0.001. Patients on 1-2 medications were more willing to take less medication(s) compared with patients on 10+ medications (62.1% vs. 46.6%, p = 0.03). Similar proportions of willingness to take less medications were seen across ADA health status, and HbA1c. Willingness to take less medication(s) was similar across survey responses to questions about patient-clinician relationships. CONCLUSIONS: Clinical guidelines suggest considering treatment de-intensification in older patients with longer duration of diabetes, yet patients with these characteristics are less likely to be willing to take less medication(s).

Care Partner Engagement in Secure Messaging Between Patients With Diabetes and Their Clinicians: Cohort Study.

BACKGROUND: Patient engagement with secure messaging (SM) via digital patient portals has been associated with improved diabetes outcomes, including increased patient satisfaction and better glycemic control. Yet, disparities in SM uptake exist among older patients and racial and ethnic underserved groups. Care partners (family members or friends) may provide a means for mitigating these disparities; however, it remains unclear whether and to what extent care partners might enhance SM use. OBJECTIVE: We aim to examine whether SM use differs among older patients with diabetes based on the involvement of care partner proxies. METHODS: This is a substudy of the ECLIPPSE (Employing Computational Linguistics to Improve Patient-Provider Secure Emails) project, a cohort study taking place in a large, fully integrated health care delivery system with an established digital patient portal serving over 4 million patients. Participants included patients with type 2 diabetes aged ≥50 years, newly registered on the patient portal, who sent ≥1 English-language message to their clinician between July 1, 2006, and December 31, 2015. Proxy SM was identified by having a registered proxy. To identify nonregistered proxies, a computational linguistics algorithm was applied to detect words and phrases more likely to appear in proxy messages compared to patient-authored messages. The primary outcome was the annual volume of secure messages (sent or received); secondary outcomes were the length of time to the first SM sent by patient or proxy and the number of annual SM exchanges (unique message topics generating ≥1 reply). RESULTS: The mean age of the cohort (N=7659) at this study's start was 61 (SD 7.16) years; 75% (n=5573) were married, 15% (n=1089) identified as Black, 10% (n=747) Chinese, 12% (n=905) Filipino, 13% (n=999) Latino, and 30% (n=2225) White. Further, 49% (n=3782) of patients used a proxy to some extent. Compared to nonproxy users, proxy users were older (P<.001), had lower educational attainment (P<.001), and had more comorbidities (P<.001). Adjusting for patient sociodemographic and clinical characteristics, proxy users had greater annual SM volume (20.7, 95% CI 20.2-21.2 vs 10.9, 95% CI 10.7-11.2; P<.001), shorter time to SM initiation (hazard ratio vs nonusers: 1.30, 95% CI 1.24-1.37; P<.001), and more annual SM exchanges (6.0, 95% CI 5.8-6.1 vs 2.9, 95% CI 2.9-3.0, P<.001). Differences in SM engagement by proxy status were similar across patient levels of education, and racial and ethnic groups. CONCLUSIONS: Among a cohort of older patients with diabetes, proxy SM involvement was independently associated with earlier initiation and increased intensity of messaging, although it did not appear to mitigate existing disparities in SM. These findings suggest care partners can enhance patient-clinician telecommunication in diabetes care. Future studies should examine the effect of care partners' SM involvement on diabetes-related quality of care and clinical outcomes.

Continuous Glucose Monitor Metrics Are Associated with Emergency Department Visits and Hospitalizations for Hypoglycemia and Hyperglycemia, but Have Low Predictive Value.

Objective: Determine whether continuous glucose monitor (CGM) metrics can provide actionable advance warning of an emergency department (ED) visit or hospitalization for hypoglycemic or hyperglycemic (dysglycemic) events. Research Design and Methods: Two nested case-control studies were conducted among insulin-treated diabetes patients at Kaiser Permanente, who shared their CGM data with their providers. Cases included dysglycemic events identified from ED and hospital records (2016-2021). Controls were selected using incidence density sampling. Multiple CGM metrics were calculated among patients using CGM >70% of the time, using CGM data from two lookback periods (0-7 and 8-14 days) before each event. Generalized estimating equations were specified to estimate odds ratios and C-statistics. Results: Among 3626 CGM users, 108 patients had 154 hypoglycemic events and 165 patients had 335 hyperglycemic events. Approximately 25% of patients had no CGM data during either lookback; these patients had >2 × the odds of a hypoglycemic event and 3-4 × the odds of a hyperglycemic event. While several metrics were strongly associated with a dysglycemic event, none had good discrimination. Conclusion: Several CGM metrics were strongly associated with risk of dysglycemic events, and these can be used to identify higher risk patients. Also, patients who are not using their CGM device may be at elevated risk of adverse outcomes. However, no CGM metric or absence of CGM data had adequate discrimination to reliably provide actionable advance warning of an event and thus justify a rapid intervention.

Preventing severe hypoglycemia in adults with type 2 diabetes (PHT2): Design, delivery and evaluation framework for a randomized controlled trial.

BACKGROUND: Severe hypoglycemia is a common and feared complication of medications used to lower blood glucose levels in individuals with diabetes. Psychoeducational interventions can prevent severe hypoglycemia in individuals with type 1 diabetes (T1D). We aim to determine the effectiveness of this approach among adults with type 2 diabetes (T2D) at elevated risk for severe hypoglycemia. METHODS: Preventing Hypoglycemia in Type 2 diabetes (PHT2) is a two-arm, parallel, randomized controlled trial. Participants are eligible if they are adults with T2D receiving care at an integrated group practice in Washington state and have experienced one or more episodes of severe hypoglycemia in the prior 12 months or have impaired awareness of hypoglycemia (Gold score ≥ 4). Participants are randomized to proactive nurse care management with or without my hypo compass, an evidence-based, psychoeducational intervention combining group and individual self-management training. For this study, my hypo compass was adapted to be suitable for adults with T2D and from an in-person to a virtual intervention over videoconference and telephone. The primary outcome is any self-reported severe hypoglycemia in the 12 months following the start of the intervention. Secondary outcomes include biochemical measures of hypoglycemia, self-reported hypoglycemia awareness, fear of hypoglycemia, and emergency department visits and hospitalizations for severe hypoglycemia. The study includes a process evaluation to assess implementation fidelity and clarify the causal pathway. CONCLUSION: The PHT2 trial will compare the effectiveness of two approaches for reducing severe hypoglycemia in adults with T2D. TRIAL REGISTRATION: clinicaltrials.gov, # NCT04863872.

Severe hypoglycemia and falls in older adults with diabetes: The Diabetes & Aging Study.

Objective: To estimate rates of severe hypoglycemia and falls among older adults with diabetes and evaluate their association. Research Design and Methods: Survey in an age-stratified, random sample adults with diabetes age 65-100 years; respondents were asked about severe hypoglycemia (requiring assistance) and falls in the past 12 months. Prevalence ratios (adjusted for age, sex, race/ethnicity) estimated the increased risk of falls associated with severe hypoglycemia. Results: Among 2,158 survey respondents, 79 (3.7%) reported severe hypoglycemia, of whom 68 (86.1%) had no ED visit or hospitalization for hypoglycemia. Falls were reported by 847 (39.2%), of whom 745 (88.0%) had no fall documented in outpatient or inpatient records. Severe hypoglycemia was associated with a 70% greater prevalence of falls (adjusted prevalence ratio = 1.7 (95% CI, 1.3-2.2)). Conclusion: While clinical documentation of events likely reflects severity or care-seeking behavior, severe hypoglycemia and falls are common, under-reported life-threatening events.

Racial and Ethnic Differences in the Association Between Mean Glucose and Hemoglobin A1c.

Background: Studies have reported significantly higher hemoglobin A1c (A1C) in African American patients than in White patients with the same mean glucose, but less is known about other racial/ethnic groups. We evaluated racial/ethnic differences in the association between mean glucose, based on continuous glucose monitor (CGM) data, and A1C. Methods: Retrospective study among 1788 patients with diabetes from Kaiser Permanente Northern California (KPNC) who used CGM devices during 2016 to 2021. In this study population, there were 5264 A1C results; mean glucose was calculated from 124,388,901 CGM readings captured during the 90 days before each A1C result. Hierarchical mixed models were specified to estimate racial/ethnic differences in the association between mean glucose and A1C. Results: Mean A1C was 0.33 (95% confidence interval: 0.23-0.44; P < 0.0001) percentage points higher among African American patients relative to White patients for a given mean glucose. A1C results for Asians, Latinos, and multiethnic patients were not significantly different from those of White patients. The slope of the association between mean glucose and A1C did not differ significantly across racial/ethnic groups. Variance for the association between mean glucose and A1C was substantially greater within groups than between racial/ethnic groups (65% vs. 9%, respectively). Conclusions: For African American patients, A1C results may overestimate glycemia and could lead to premature diabetes diagnoses, overtreatment, or invalid assessments of health disparities. However, most of the variability in the mean glucose-A1C association was within racial/ethnic groups. Treatment decisions driven by guideline-based A1C targets should be individualized and supported by direct measurement of glycemia.

Glycemic control and diabetes complications across health status categories in older adults treated with insulin or insulin secretagogues: The Diabetes & Aging Study.

BACKGROUND: For older adults with type 2 diabetes (T2D) treated with insulin or sulfonylureas, Endocrine Society guideline recommends HbA1c between 7% to <7.5% for those in good health, 7.5% to <8% for those in intermediate health, and 8% to <8.5% for those in poor health. Our aim was to examine associations between attained HbA1c below, within (reference), or above recommended target range and risk of complication or mortality. METHODS: Retrospective cohort study of adults ≥65 years old with T2D treated with insulin or sulfonylureas from an integrated healthcare delivery system. Cox proportional hazards models of complications during 2019 were adjusted for sociodemographic and clinical variables. Primary outcome was a combined outcome of any microvascular or macrovascular event, severe hypoglycemia, or mortality during 12-month follow-up. RESULTS: Among 63,429 patients (mean age: 74.2 years, 46.8% women), 8773 (13.8%) experienced a complication. Complication risk was significantly elevated for patients in good health (n = 16,895) whose HbA1c was above (HR 1.97, 95% CI 1.62-2.41) or below (HR 1.29, 95% CI 1.02-1.63) compared to within recommended range. Among those in intermediate health (n = 30,129), complication risk was increased for those whose HbA1c was above (HR 1.45, 95% CI 1.30-1.60) but not those below the recommended range (HR 0.99, 95% CI 0.89-1.09). Among those in poor health (n = 16,405), complication risk was not significantly different for those whose HbA1c was below (HR 0.98, 95% CI 0.89-1.09) or above (HR 0.96, 95% CI 0.88-1.06) recommended range. CONCLUSIONS: For older adults with T2D in good health, HbA1c below or above the recommended range was associated with significantly elevated complication risk. However, for those in poor health, achieving specific HbA1c levels may not be helpful in reducing the risk of complications.

Use of Real-World Data in Population Science to Improve the Prevention and Care of Diabetes-Related Outcomes.

The past decade of population research for diabetes has seen a dramatic proliferation of the use of real-world data (RWD) and real-world evidence (RWE) generation from non-research settings, including both health and non-health sources, to influence decisions related to optimal diabetes care. A common attribute of these new data is that they were not collected for research purposes yet have the potential to enrich the information around the characteristics of individuals, risk factors, interventions, and health effects. This has expanded the role of subdisciplines like comparative effectiveness research and precision medicine, new quasi-experimental study designs, new research platforms like distributed data networks, and new analytic approaches for clinical prediction of prognosis or treatment response. The result of these developments is a greater potential to progress diabetes treatment and prevention through the increasing range of populations, interventions, outcomes, and settings that can be efficiently examined. However, this proliferation also carries an increased threat of bias and misleading findings. The level of evidence that may be derived from RWD is ultimately a function of the data quality and the rigorous application of study design and analysis. This report reviews the current landscape and applications of RWD in clinical effectiveness and population health research for diabetes and summarizes opportunities and best practices in the conduct, reporting, and dissemination of RWD to optimize its value and limit its drawbacks.

Development and Validation of the Life Expectancy Estimator for Older Adults with Diabetes (LEAD): the Diabetes and Aging Study.

BACKGROUND: Estimated life expectancy for older patients with diabetes informs decisions about treatment goals, cancer screening, long-term and advanced care, and inclusion in clinical trials. Easily implementable, evidence-based, diabetes-specific approaches for identifying patients with limited life expectancy are needed. OBJECTIVE: Develop and validate an electronic health record (EHR)-based tool to identify older adults with diabetes who have limited life expectancy. DESIGN: Predictive modeling based on survival analysis using Cox-Gompertz models in a retrospective cohort. PARTICIPANTS: Adults with diabetes aged ≥ 65 years from Kaiser Permanente Northern California: a 2015 cohort (N = 121,396) with follow-up through 12/31/2019, randomly split into training (N = 97,085) and test (N = 24,311) sets. Validation was conducted in the test set and two temporally distinct cohorts: a 2010 cohort (n = 89,563; 10-year follow-up through 2019) and a 2019 cohort (n = 152,357; 2-year follow-up through 2020). MAIN MEASURES: Demographics, diagnoses, utilization and procedures, medications, behaviors and vital signs; mortality. KEY RESULTS: In the training set (mean age 75 years; 49% women; 48% racial and ethnic minorities), 23% died during 5 years follow-up. A mortality prediction model was developed using 94 candidate variables, distilled into a life expectancy model with 11 input variables, and transformed into a risk-scoring tool, the Life Expectancy Estimator for Older Adults with Diabetes (LEAD). LEAD discriminated well in the test set (C-statistic = 0.78), 2010 cohort (C-statistic = 0.74), and 2019 cohort (C-statistic = 0.81); comparisons of observed and predicted survival curves indicated good calibration. CONCLUSIONS: LEAD estimates life expectancy in older adults with diabetes based on only 11 patient characteristics widely available in most EHRs and claims data. LEAD is simple and has potential application for shared decision-making, clinical trial inclusion, and resource allocation.

Glycemic Control Over Multiple Decades and Dementia Risk in People With Type 2 Diabetes.

Importance: The levels of glycemic control associated with the lowest risk of dementia in people with type 2 diabetes are unknown. This knowledge is critical to inform patient-centered glycemic target setting. Objective: To examine the associations between cumulative exposure to various ranges of glycated hemoglobin (HbA1c) concentrations with dementia risk across sex and racial and ethnic groups and the association of current therapeutic glycemic targets with dementia risk. Design, Setting, and Participants: This cohort study included members of the Kaiser Permanente Northern California integrated health care system with type 2 diabetes who were aged 50 years or older during the study period from January 1, 1996, to September 30, 2015. Individuals with fewer than 2 HbA1c measurements during the study period, prevalent dementia at baseline, or less than 3 years of follow-up were excluded. Data were analyzed from February 2020 to January 2023. Exposures: Time-updated cumulative exposure to HbA1c thresholds. At each HbA1c measurement, participants were categorized based on the percentage of their HbA1c measurements that fell into the following categories: less than 6%, 6% to less than 7%, 7% to less than 8%, 8% to less than 9%, 9% to less than 10%, and 10% or more of total hemoglobin (to convert percentage of total hemoglobin to proportion of total hemoglobin, multiply by 0.01). Main Outcomes and Measures: Dementia diagnosis was identified using International Classification of Diseases, Ninth Revision codes from inpatient and outpatient encounters. Cox proportional hazards regression models estimated the association of time-varying cumulative glycemic exposure with dementia, adjusting for age, race and ethnicity, baseline health conditions, and number of HbA1c measurements. Results: A total of 253 211 participants were included. The mean (SD) age of participants was 61.5 (9.4) years, and 53.1% were men. The mean (SD) duration of follow-up was 5.9 (4.5) years. Participants with more than 50% of HbA1c measurements at 9% to less than 10% or 10% or more had greater risk of dementia compared with those who had 50% or less of measurements in those categories (HbA1c 9% to <10%: adjusted hazard ratio [aHR], 1.31 [95% CI, 1.15-1.51]; HbA1c≥10%: aHR, 1.74 [95% CI, 1.62-1.86]). By contrast, participants with more than 50% of HbA1c concentrations less than 6%, 6% to less than 7%, or 7% to less than 8% had lower risk of dementia (HbA1c<6%: aHR, 0.92 [95% CI, 0.88-0.97]; HbA1c 6% to <7%: aHR, 0.79 [95% CI, 0.77-0.81]; HbA1c 7% to <8%: aHR, 0.93 [95% CI, 0.89-0.97]). Conclusions and Relevance: In this study dementia risk was greatest among adults with cumulative HbA1c concentrations of 9% or more. These results support currently recommended relaxed glycemic targets for older people with type 2 diabetes.

Data-driven classification of health status of older adults with diabetes: The diabetes and aging study.

BACKGROUND: We set out to identify empirically-derived health status classes of older adults with diabetes based on clusters of comorbid conditions which are associated with future complications. METHODS: We conducted a cohort study among 105,786 older (≥65 years of age) adults with type 2 diabetes enrolled in an integrated healthcare delivery system. We used latent class analysis of 19 baseline comorbidities to derive health status classes and then compared incident complication rates (events per 100 person-years) by health status class during 5 years of follow-up. Complications included infections, hyperglycemic events, hypoglycemic events, microvascular events, cardiovascular events, and all-cause mortality. RESULTS: Three health status classes were identified: Class 1 (58% of the cohort) had the lowest prevalence of most baseline comorbidities, Class 2 (22%) had the highest prevalence of obesity, arthritis, and depression, and Class 3 (20%) had the highest prevalence of cardiovascular conditions. The risk for incident complications was highest for Class 3, intermediate for Class 2 and lowest for Class 1. For example, the age, sex and race-adjusted rates for cardiovascular events (per 100 person-years) for Class 3, Class 2 and Class 1 were 6.5, 2.3, and 1.6, respectively; 2.1, 1.2, 0.7 for hypoglycemia; and 8.0, 3.8, and 2.3 for mortality. CONCLUSIONS: Three health status classes of older adults with diabetes were identified based on prevalent comorbidities and were associated with marked differences in risk of complications. These health status classes can inform population health management and guide the individualization of diabetes care.

Development and Validation of a Diabetic Retinopathy Risk Stratification Algorithm.

OBJECTIVE: Although diabetic retinopathy is a leading cause of blindness worldwide, diabetes-related blindness can be prevented through effective screening, detection, and treatment of disease. The study goal was to develop risk stratification algorithms for the onset of retinal complications of diabetes, including proliferative diabetic retinopathy, referable retinopathy, and macular edema. RESEARCH DESIGN AND METHODS: Retrospective cohort analysis of patients from the Kaiser Permanente Northern California Diabetes Registry who had no evidence of diabetic retinopathy at a baseline diabetic retinopathy screening during 2008-2020 was performed. Machine learning and logistic regression prediction models for onset of proliferative diabetic retinopathy, diabetic macular edema, and referable retinopathy detected through routine screening were trained and internally validated. Model performance was assessed using area under the curve (AUC) metrics. RESULTS: The study cohort (N = 276,794) was 51.9% male and 42.1% White. Mean (±SD) age at baseline was 60.0 (±13.1) years. A machine learning XGBoost algorithm was effective in identifying patients who developed proliferative diabetic retinopathy (AUC 0.86; 95% CI, 0.86-0.87), diabetic macular edema (AUC 0.76; 95% CI, 0.75-0.77), and referable retinopathy (AUC 0.78; 95% CI, 0.78-0.79). Similar results were found using a simpler nine-covariate logistic regression model: proliferative diabetic retinopathy (AUC 0.82; 95% CI, 0.80-0.83), diabetic macular edema (AUC 0.73; 95% CI, 0.72-0.74), and referable retinopathy (AUC 0.75; 95% CI, 0.75-0.76). CONCLUSIONS: Relatively simple logistic regression models using nine readily available clinical variables can be used to rank order patients for onset of diabetic eye disease and thereby more efficiently prioritize and target screening for at risk patients.

Validation of a Hypoglycemia Risk Stratification Tool Using Data From Continuous Glucose Monitors.

This cohort study uses data from continuous glucose monitoring to validate a hypoglycemia risk stratification tool.

Racial and Ethnic Differences in Medication Initiation Among Adults Newly Diagnosed with Type 2 Diabetes.

OBJECTIVE: Given persistent racial/ethnic differences in type 2 diabetes outcomes and the lasting benefits conferred by early glycemic control, we examined racial/ethnic differences in diabetes medication initiation during the year following diagnosis. METHODS: Among adults newly diagnosed with type 2 diabetes (2005-2016), we examined how glucose-lowering medication initiation differed by race/ethnicity during the year following diagnosis. We specified modified Poisson regression models to estimate the association between race/ethnicity and medication initiation in the entire cohort and within subpopulations defined by HbA1c, BMI, age at diagnosis, comorbidity, and neighborhood deprivation index (a census tract-level socioeconomic indicator). RESULTS: Among the 77,199 newly diagnosed individuals, 47% started a diabetes medication within 12 months of diagnosis. The prevalence of medication initiation ranged from 32% among Chinese individuals to 58% among individuals of Other/Unknown races/ethnicities. Compared to White individuals, medication initiation was less likely among Chinese (relative risk: 0.78 (95% confidence interval 0.72, 0.84)) and Japanese (0.82 (0.75, 0.90)) individuals, but was more likely among Hispanic/Latinx (1.27 (1.24, 1.30)), African American (1.14 (1.11, 1.17)), other Asian (1.13 (1.08, 1.18)), South Asian (1.10 (1.04, 1.17)), Other/Unknown (1.31 (1.24, 1.39)), American Indian or Alaska Native (1.11 (1.04, 1.18)), and Native Hawaiian/Pacific Islander (1.28 (1.19, 1.37)) individuals. Racial/ethnic differences dissipated among individuals with higher HbA1c values. CONCLUSIONS: Initiation of glucose-lowering treatment during the year following type 2 diabetes diagnosis differed markedly by race/ethnicity, particularly for those with lower HbA1c values. Future research should examine how patient preferences, provider implicit bias, and shared decision-making contribute to these early treatment differences.

Comparison of cognitive function in older adults with type 1 diabetes, type 2 diabetes, and no diabetes: results from the Study of Longevity in Diabetes (SOLID).

INTRODUCTION: The incidence of both type 1 diabetes (T1D) and type 2 diabetes (T2D) is increasing. Life expectancy is improving in T1D, resulting in a growing population of elderly adults with diabetes. While it is well established that older adults with T2D are at increased risk of cognitive impairment, little is known regarding cognitive aging in T1D and how their cognitive profiles may differ from T2D. RESEARCH DESIGN AND METHODS: We compared baseline cognitive function and low cognitive function by diabetes status (n=734 T1D, n=232 T2D, n=247 without diabetes) among individuals from the Study of Longevity in Diabetes (mean age=68). We used factor analysis to group cognition into five domains and a composite measure of total cognition. Using linear and logistic regression models, we examined the associations between diabetes type and cognitive function, adjusting for demographics, comorbidities, depression, and sleep quality. RESULTS: T1D was associated with lower scores on total cognition, language, executive function/psychomotor processing speed, and verbal episodic memory, and greater odds of low executive function/psychomotor processing speed (OR=2.99, 95% CI 1.66 to 5.37) and verbal episodic memory (OR=1.92, 95% CI 1.07 to 3.46), compared with those without diabetes. T2D was associated with lower scores on visual episodic memory. Compared with T2D, T1D was associated with lower scores on verbal episodic memory and executive function/psychomotor processing speed and greater odds of low executive function/psychomotor processing speed (OR=1.74, 95% CI 1.03 to 2.92). CONCLUSIONS: Older adults with T1D had significantly poorer cognition compared with those with T2D and those without diabetes even after accounting for a range of comorbidities. Future studies should delineate how to reduce risk in this vulnerable population who are newly surviving to old age.

Continuous Glucose Monitor Use Prevents Glycemic Deterioration in Insulin-Treated Patients with Type 2 Diabetes.

Continuous glucose monitoring (CGM) is indicated in poorly controlled insulin-treated patients with type 2 diabetes (T2D) to improve glycemic control and reduce the risk of hypoglycemia, but the benefits of CGM for lower risk patients have not been well studied. Among 17,422 insulin-treated patients with T2D with hemoglobin A1c (HbA1c) <8% and no recent severe hypoglycemia (based on emergency room visits or hospitalizations), CGM initiation occurred in 149 patients (17,273 noninitiators served as reference). Changes in HbA1c and severe hypoglycemia rates for the 12 months before and after CGM initiation were calculated. CGM initiation was associated with decreased HbA1c (-0.06%), whereas noninitiation was associated with increased HbA1c (+0.32%); a weighted adjusted difference-in-difference model of change in HbA1c yielded a net benefit of -0.30%; 95% CI -0.50%, -0.10%; P = 0.004). No significant differences were observed for severe hypoglycemia. CGM may be useful in preventing glycemic deterioration in well-controlled patients with insulin-treated T2D.