Use of Technology in Older Adults with Type 1 Diabetes: Clinical Characteristics and Glycemic Metrics

Associations between use of diabetes technology and diabetes distress: a Danish cross-sectional survey of adults with type 1 diabetes

INTRODUCTION

The study aimed to investigate independent and combined associations between insulin delivery method (insulin pump therapy (IPT) vs multiple daily injections (MDI)), glucose monitoring method (intermittently scanned continuous glucose monitoring (isCGM) and real-time continuous glucose monitoring (rtCGM) vs blood glucose metre (BGM)) and diabetes distress (DD) in adults with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

We combined data from two Danish questionnaire-based surveys, the Steno Tech Survey (n=1591) and the Type 1 Diabetes Distress Scale (T1-DDS) validation survey (n=4205), in which individuals aged ≥18 years with T1D were invited to participate. The 28-item T1-DDS was used to measure DD and DD scores were categorised as little or no distress (score <2.0), moderate distress (2.0-2.9) and high distress (score ≥3.0). Associations between insulin delivery, glucose monitoring methods and DD were assessed using linear regression.

RESULTS

Among 2068 adults with T1D who responded to one of the surveys, the use of IPT was associated with a lower total T1-DDS score (-0.09, 95% CI 0.16 to -0.03) compared with MDI and adjusted for glucose monitoring method. The use of CGM was associated with a higher total T1-DDS score (0.11, 95% CI 0.05 to 0.18) compared with BGM and adjusted for the insulin delivery method. IPT was still associated with a lower T1-DDS score, regardless of being combined with BGM (-0.17, 95% CI -0.28 to -0.06) or CGM (-0.13, 95% CI -0.21 to -0.05), compared with MDI with CGM. No association was found between the type of CGM (isCGM vs rtCGM) and DD among either IPT or MDI users when restricting analysis to individuals using CGM.

CONCLUSIONS

Among Danish adults with T1D, the use of IPT was associated with lower levels of DD, while CGM use was associated with higher levels of DD. DD should be addressed when introducing people with T1D to diabetes technology, CGM in particular.

TRIAL REGISTRATION NUMBER

NCT04311164 (Results).

Social Support, eHealth Literacy, and mHealth Use in Older Adults With Diabetes: Moderated Mediating Effect of the Perceived Importance of App Design

Mobile healthcare has emerged as a prominent technological solution for self-management of health. However, the development and utilization of tailored mobile healthcare applications for older adults with diabetes mellitus remain limited. This study examined the relationship between social support and mobile healthcare use and further explored how this relationship varies with eHealth literacy and application design among older adults with diabetes mellitus. A descriptive cross-sectional trial was conducted with a structured self-report questionnaire, surveying 252 South Korean older adults with diabetes mellitus via offline and online modes. The mediating effect and moderated mediating effect were analyzed with the PROCESS macro of SPSS. eHealth literacy mediated the relationship between social support and mobile healthcare use. High levels of eHealth literacy and social support may increase mobile healthcare use among older adults with diabetes. Application design aesthetics facilitated mobile healthcare use. Future researchers, healthcare providers, and developers can contribute to the development of tailored mobile healthcare applications for older adults with diabetes mellitus by considering application design aspects such as font size, color, and menu configuration.

Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition)

With the deepening of aging in China, the prevalence of diabetes in older people has increased noticeably, and standardized diabetes management is critical for improving clinical outcomes of diabetes in older people. In 2021, the National Center of Gerontology, Chinese Society of Geriatrics, and Diabetes Professional Committee of Chinese Aging Well Association organized experts to write the first guideline for diabetes diagnosis and treatment in older people in China, the Guideline for the Management of Diabetes Mellitus in the Elderly in China (2021 Edition). The guideline emphasizes that older patients with diabetes are a highly heterogeneous group requiring comprehensive assessment and stratified and individualized management strategies. The guideline proposes simple treatments and de-intensified treatment strategies for older patients with diabetes. This edition of the guideline provides clinicians with practical and operable clinical guidance, thus greatly contributing to the comprehensive and full-cycle standardized management of older patients with diabetes in China and promoting the extensive development of clinical and basic research on diabetes in older people and related fields. In the past 3 years, evidence-based medicine for older patients with diabetes and related fields has further advanced, and new treatment concepts, drugs, and technologies have been developed. The guideline editorial committee promptly updated the first edition of the guideline and compiled the Guideline for the Management of Diabetes Mellitus in the Elderly in China (2024 Edition). More precise management paths for older patients with diabetes are proposed, for achieving continued standardization of the management of older Chinese patients with diabetes and improving their clinical outcomes.

Supporting the 'lived expertise' of older adults with type 1 diabetes: An applied focus group analysis to characterize barriers, facilitators, and strategies for self-management in a growing and understudied population

INTRODUCTION

There is a growing number of older adults (≥65 years) who live with type 1 diabetes. We qualitatively explored experiences and perspectives regarding type 1 diabetes self-management and treatment decisions among older adults, focusing on adopting care advances such as continuous glucose monitoring (CGM).

METHODS

Among a clinic-based sample of older adults ≥65 years with type 1 diabetes, we conducted a series of literature and expert informed focus groups with structured discussion activities. Groups were transcribed followed by inductive coding, theme identification, and inference verification. Medical records and surveys added clinical information.

RESULTS

Twenty nine older adults (age 73.4 ± 4.5 years; 86% CGM users) and four caregivers (age 73.3 ± 2.9 years) participated. Participants were 58% female and 82% non-Hispanic White. Analysis revealed themes related to attitudes, behaviours, and experiences, as well as interpersonal and contextual factors that shape self-management and outcomes. These factors and their interactions drive variability in diabetes outcomes and optimal treatment strategies between individuals as well as within individuals over time (i.e. with ageing). Participants proposed strategies to address these factors: regular, holistic needs assessments to match people with effective self-care approaches and adapt them over the lifespan; longitudinal support (e.g., education, tactical help, sharing and validating experiences); tailored education and skills training; and leveraging of caregivers, family, and peers as resources.

CONCLUSIONS

Our study of what influences self-management decisions and technology adoption among older adults with type 1 diabetes underscores the importance of ongoing assessments to address dynamic age-specific needs, as well as individualized multi-faceted support that integrates peers and caregivers.

Prevalence of impaired awareness of hypoglycaemia in people with diabetes mellitus: A systematic review and meta-analysis from 21 countries and regions

AIMS

Impaired awareness of hypoglycaemia (IAH) is a complication of glucose-lowering therapies for diabetes. The purpose of this review was to estimate the pooled prevalence of IAH and unawareness of hypoglycaemia (UAH).

METHODS

We searched the major databases from inception to 8 August 2022 and included all cross-sectional and cohort studies reporting IAH prevalence in people with diabetes. A random-effects model was used to pool effect values. Subgroup analysis and meta-regression were used to identify study-level characteristics affecting prevalence.

RESULTS

Sixty-two studies from 21 countries published between 2000 and 2022 were included, with 39,180 participants (type 1 diabetes: 19,304 vs. Type 2 diabetes: 14,650). The pooled prevalence was 23.2% (95% CI: 18.4%-29.3%) via the Clarke questionnaire, 26.2% (95% CI: 22.9%-29.9%) via the Gold score, and 58.5% (95% CI: 53.0%-64.6%) via the Pedersen-Bjergaard method, all from studies classified as presenting a moderate and low risk of bias. The prevalence of IAH was generally higher in people with type 1 diabetes than in those with type 2 diabetes and lowest in Europe. Meta-regression results show that the duration of diabetes was a factor influencing the prevalence of IAH. The prevalence of UAH by the Pedersen-Bjergaard method was 17.6 (95% CI: 14.9%-20.3%).

CONCLUSIONS

IAH is a prevalent risk event among people with type 1 and type 2 diabetes, showing clinical heterogeneity and regional variability. UAH, an adverse progression of IAH, is also a serious burden. More primary research on the prevalence of IAH is needed in areas with a high diabetes burden.

Use of Telemedicine in Adults with Type 1 Diabetes: Do Age and Use of Diabetes-Related Technology Matter?

Objective: Older adults are generally less proficient in technology use compared with younger adults. Data on telemedicine use during the COVID-19 pandemic in older persons with type 1 diabetes (T1D) and the association of telemedicine with the use of diabetes-related technology are limited. We evaluated care delivery to older adults compared with younger adults with T1D in a prepandemic and pandemic period. Methods: Data from electronic health records were evaluated for visit types (in-person, phone, and video) from two sequential 12-month intervals: prepandemic (April 2019-March 2020) and pandemic (April 2020-March 2021). Results: Data from 2,832 unique adults with T1D were evaluated in two age cohorts: younger (40-64 years) and older (≥65 years). Half of each group used continuous glucose monitoring (CGM), whereas 54% of the younger and 37% of the older cohort used pump therapy (p < 0.001). During the pandemic compared with the prepandemic period, visit frequency increased in both the younger (0.65 vs. 0.76 visits/patient/quarter; p < 0.01) and older (0.72 vs. 0.80 visits/patient/quarter; p < 0.01) cohorts. During the pandemic, older adults used more phone visits compared with younger adults (48% vs. 32%; p = 0.001). Patients using either pump therapy or CGM were more likely to use video visits compared with phone visits in both younger (41% vs. 24%; p < 0.001) and older cohorts (53% vs. 42%; p < 0.001). Conclusions: Adults using diabetes-related technologies, independent of age, accessed more video visits than those not using devices. Telemedicine visits appeared to maintain continuity of care for younger and older adults with T1D, supporting the future of a hybrid-care model.

Effect of diabetes technologies on the fear of hypoglycaemia among people living with type 1 diabetes: a systematic review and meta-analysis

Background

Fear of hypoglycaemia (FOH) significantly disrupts the daily management of type 1 diabetes (T1D) and increases the risk of complications. Recent technological advances can improve glucose metrics and reduce hypoglycaemia frequency, yet their impact on FOH is unclear. This systematic review and meta-analysis (SRMA) aimed to synthesize the current literature to understand the impact of diabetes technologies on FOH in T1D.

Methods

In this SRMA, we searched PubMed, Medline, Scopus, and Web of Science from inception up to May 21st, 2023 for studies assessing the effect of using real-time or intermittently scanned continuous glucose monitors (rtCGM or isCGM); insulin pumps (CSII); and their combinations on FOH as the primary outcome, measured using the Hypoglycaemia Fear Survey (HFS; including total, worries [HFS-W], and behaviours [HFS-B] scores), in non-pregnant adults with T1D. Data was extracted by the first and second authors. Results were pooled using a random-effects model based on study design (RCT and non-RCT), with subgroup analysis based on the type of technology, reported change in hypoglycaemia frequency, and duration of use. Risk of bias was evaluated with Cochrane and Joanna Briggs Institute tools. This study is registered with PROSPERO, CRD42021253618.

Findings

A total of 51 studies (n = 8966) were included, 22 of which were RCTs. Studies on rtCGM and CSII reported lower FOH levels with ≥8 weeks of use. Studies on CSII and rtCGM combinations reported lower FOH levels after ≥13 weeks of automated insulin delivery (AID) use or 26 weeks of sensor-augmented pump (SAP) use. The meta-analysis showed an overall lower FOH with technologies, specifically for the HFS-W subscale. The RCT meta-analysis showed lower HFS-W scores with rtCGM use (standard mean difference [95%CI]: -0.14 [-0.23, -0.05], I2 = 0%) and AID (-0.17 [-0.33, -0.01], I2 = 0%). Results from non-RCT studies show that SAP users (-0.33 [-0.38, -0.27], I2 = 0%) and rtCGM users (-0.38 [-0.61, -0.14], I2 = 0%) had lower HFS-W.

Interpretation

We found consistent, yet small to moderate, effects supporting that diabetes technologies (specifically rtCGM, SAP, and AID) may reduce hypoglycaemia-related worries in adults with T1D. Current literature, however, has limitations including discrepancies in baseline characteristics and limited, mainly descriptive, statistical analysis. Thus, future studies should assess FOH as a primary outcome, use validated surveys, and appropriate statistical analysis to evaluate the clinical impacts of technology use beyond just glucose metrics.

Funding

Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation Ltd.

Gender differences in reported frequency and consequences of hypoglycemia among adults living with type 1 diabetes: results from the BETTER registry

AIMS

To evaluate the frequency and consequences of level 2 (L2H, glucose level <3.0 mmol/L with autonomous management) and level 3 hypoglycemia (L3H requiring external assistance to treat), in adults living with type 1 diabetes (T1D), while investigating the role of gender.

METHODS

Cross-sectional analysis of self-reported retrospective data from a Canadian registry of 900 adults living with T1D using logistic regression models adjusted for age, T1D management modalities, hypoglycemia history, and validated patient-reported outcomes scales. Changes in diabetes management, seeking healthcare resources, and impacts on daily well-being were explored.

RESULTS

Of the 900 adults (66% women, mean age 43.7 ± 14.8 years, mean T1D duration 25.5 ± 14.6 years), 87% used wearable diabetes technology. L3H in the past year was reported by 15% participants, similar between genders. Women reported more L2Hstudy analysis than men (median (Q1, Q3): 4 (2, 10) vs 3 (1,8), p=0.015), and were more likely to report persistent fatigue after both L2H and L3H (Odds ratio [95% confidence interval]: 1.95 [1.16, 3.28] and 1.86 [1.25, 2.75], respectively) and anxiety (1.70 [1.05, 2.75]) after a L3H.

CONCLUSIONS

The findings suggest taking a gender-based differential approach when addressing hypoglycemia and its various consequences for people living with T1D.

Self-care barriers and facilitators in older adults with T1D during a time of sudden isolation

Older adults with type 1 diabetes (T1D) have unique challenges and needs. In this mixed-methods study, we explored the impact of isolation during a pandemic on diabetes management and overall quality of life in this population. Older adults (age ≥ 65 years) with T1D receiving care at a tertiary care diabetes center participated in semi-structured interviews during COVID-19 pandemic isolation between June and August 2020. A multi-disciplinary team coded transcripts and conducted thematic analysis. Thirty-four older adults (age 71 ± 5 years, 97% non-Hispanic white, diabetes duration of 38 ± 7 years, A1C of 7.4 ± 0.9% (57.3 ± 10.1 mmol/mol) were recruited. Three themes related to diabetes self-care emerged regarding impact of isolation on: (1) diabetes management and self-care behaviors (how isolation prompted changes in physical activity and dietary habits); (2) emotional stress and anxiety (related to isolation and lack of support system, economic concerns); and (3) concerns regarding the COVID-19 pandemic (impact on timely medical care and access to information). Our findings identify modifiable barriers and challenges faced by older adults with T1D during isolation. As this population has a higher risk of decline in physical and psychosocial support even during non-pandemic times, clinicians will benefit from understanding these issues to improve care of this population.

MiniMed 780G Six-Month Use in Children and Adolescents with Type 1 Diabetes: Clinical Targets and Predictors of Optimal Glucose Control

Background: The aim of this multicenter observational real-world study was to investigate glycemic outcomes in children and adolescents with type 1 diabetes over the first 6-month use of MiniMed™ 780G. The secondary objective was to evaluate demographic and clinical factors that may be significantly associated with the achievement of therapeutic goals. Methods: Demographic, anamnestic, and clinical data of study participants were collected at the time of enrollment. Data on ambulatory glucose profile were acquired at 3 and 6 months after activating automatic mode. Aggregated glucose metrics and device settings of the entire study period were analyzed to identify predictors of optimal glycemic control, assessed by the concomitant achievement of time in range (TIR) >70%, coefficient of variation (CV) <36%, glucose management indicator (GMI) <7%, and time below range (TBR) <4%. Results: Our study cohort consisted of 111 children and adolescents (54.1% female) aged 7-18 years. All the most relevant clinical targets were achieved according to recommendations from the International Consensus both at 3 and 6 months. When considering aggregated data, primary goals in terms of TIR, CV, GMI, and TBR were achieved, respectively, by 72.1%, 74.8%, 68.5%, and 74.8% of participants. In addition, 44 individuals (39.6%) concomitantly addressed all the above clinical targets. Regression analysis revealed that older age, briefer duration of disease, and shorter active insulin time were significant predictors of optimal glucose control. Comparing two groups of individuals stratified according to the glycated hemoglobin (HbA1c) mean value in the year preceding MiniMed 780G use, achieving glycemic targets was observed in the subgroup with lower HbA1c. Conclusions: Our study highlights the effectiveness and safety of MiniMed 780G in the pediatric population. More extensive and personalized training on advanced hybrid closed-loop use should be considered for younger people and those with long disease duration.

Past, Present, and Future of Continuous Glucose Monitors (CGMs)

n/a.

"Nothing is linear": Characterizing the determinants and dynamics of CGM use in older adults with type 1 diabetes

AIMS

Continuous glucose monitoring (CGM) can reduce hypoglycemia in older adults with type 1 diabetes (T1D). We aimed to characterize factors that influence effective use in this age group.

METHODS

Older adults with type T1D (age ≥ 65) and their caregivers participated in one of a series of parallel group model building workshops, a participatory approach to system dynamics involving drawing and scripted group activities. Data were synthesized in a qualitative model of the hypothesized system of factors producing distinct patterns of CGM use in older adults. The model was validated through virtual follow-up interviews.

RESULTS

Data were collected from 33 participants (four patient-caregiver dyads, mean age 73.8 ± 4.4 years [range 66-85 years]; 16 % non-CGM users, 79 % pump users). The system model delineates drivers of CGM uptake, drivers of ongoing CGM use, and feedback loops that either reinforce or counteract future CGM use. Participants emphasized the importance of different sets of feedback loops at different points in the duration of CGM use.

CONCLUSIONS

The holistic system model underscores that factors and feedback loops driving effective CGM use in older adults are both individualized and dynamic (e.g., changing over time), suggesting opportunities for staged and tailored age-specific education and support.

Type 2 diabetes mellitus and cognitive function: understanding the connections

PURPOSE OF REVIEW

To review the connection between type 2 diabetes and cognitive dysfunction, including its epidemiology, potential mechanisms of pathophysiology, risk factors, possible prevention, and treatment considerations.

RECENT FINDINGS

Diabetes is a risk factor for mild cognitive decline, in addition to Alzheimer's disease and vascular dementia. Duration of diabetes, concomitant vascular or associated co-morbidities, hyper- and hypoglycemia may lead to worsening cognitive dysfunction. Unfortunately, there is a lack of evidence-based guidance on the prevention of cognitive dysfunction in the diabetes population. Studies of diabetes medications, including metformin, glucagon-like peptide-1 (GLP-1) receptor agonists, and sodium-glucose cotransporter-2 inhibitors (SGLT2) have shown some benefit with cardiovascular morbidity and may affect cognition. In the absence of clearly defined preventive tools, diabetes practice guidelines recommend annual cognitive screening as standard of care in adults with diabetes aged 65 years or older.

SUMMARY

People living with diabetes are at risk for significant decline in cognitive function. Epidemiology and risk factors are well defined. Prevention and treatment strategies are limited and require further study.

Estimation of a Machine Learning-Based Decision Rule to Reduce Hypoglycemia Among Older Adults With Type 1 Diabetes: A Post Hoc Analysis of Continuous Glucose Monitoring in the WISDM Study

BACKGROUND

The Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) study demonstrated continuous glucose monitoring (CGM) reduced hypoglycemia over 6 months among older adults with type 1 diabetes (T1D) compared with blood glucose monitoring (BGM). We explored heterogeneous treatment effects of CGM on hypoglycemia by formulating a data-driven decision rule that selects an intervention (ie, CGM vs BGM) to minimize percentage of time <70 mg/dL for each individual WISDM participant.

METHOD

The precision medicine analyses used data from participants with complete data (n = 194 older adults, including those who received CGM [n = 100] and BGM [n = 94] in the trial). Policy tree and decision list algorithms were fit with 14 baseline demographic, clinical, and laboratory measures. The primary outcome was CGM-measured percentage of time spent in hypoglycemic range (<70 mg/dL), and the decision rule assigned participants to a subgroup reflecting the treatment estimated to minimize this outcome across all follow-up visits.

RESULTS

The optimal decision rule was found to be a decision list with 3 steps. The first step moved WISDM participants with baseline time-below range >1.35% and no detectable C-peptide levels to the CGM subgroup (n = 139), and the second step moved WISDM participants with a baseline time-below range of >6.45% to the CGM subgroup (n = 18). The remaining participants (n = 37) were left in the BGM subgroup. Compared with the BGM subgroup (n = 37; 19%), the group for whom CGM minimized hypoglycemia (n = 157; 81%) had more baseline hypoglycemia, a lower proportion of detectable C-peptide, higher glycemic variability, longer disease duration, and higher proportion of insulin pump use.

CONCLUSIONS

The decision rule underscores the benefits of CGM for older adults to reduce hypoglycemia. Diagnostic CGM and laboratory markers may inform decision-making surrounding therapeutic CGM and identify older adults for whom CGM may be a critical intervention to reduce hypoglycemia.

Continuous Glucose Monitor, Insulin Pump, and Automated Insulin Delivery Therapies for Type 1 Diabetes: An Update on Potential for Cardiovascular Benefits

PURPOSE OF REVIEW

The incidence of type 1 diabetes (T1D) is rising in all age groups. T1D is associated with chronic microvascular and macrovascular complications but improving glycemic trends can delay the onset and slow the progression of these complications. Utilization of technological devices for diabetes management, such as continuous glucose monitors (CGM) and insulin pumps, is increasing, and these devices are associated with improvements in glycemic trends. Thus, device use may be associated with long-term prevention of T1D complications, yet few studies have investigated the direct impacts of devices on chronic complications in T1D. This review will describe common diabetes devices and combination systems, as well as review relationships between device use and cardiovascular outcomes in T1D.

RECENT FINDINGS

Findings from existing cohort and national registry studies suggest that pump use may aid in improving cardiovascular risk factors such as hypertension and dyslipidemia. Furthermore, pump users have been shown to have lower arterial stiffness and better measures of myocardial function. In registry and case-control longitudinal data, pump use has been associated with fewer cardiovascular events and reduction of cardiovascular disease (CVD) and all-cause mortality. CVD is the leading cause of morbidity and mortality in T1D. Consistent use of diabetes devices may protect against the development and progression of macrovascular complications such as CVD through improvement in glycemic trends. Existing literature is limited, but findings suggest that pump use may reduce acute cardiovascular risk factors as well as chronic cardiovascular complications and overall mortality in T1D.

Use of Telecommunication and Diabetes-Related Technologies in Older Adults With Type 1 Diabetes During a Time of Sudden Isolation: Mixed Methods Study

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.

Predictors of time in target glucose range in real-world users of the MiniMed 780G system

AIM

Automated insulin delivery systems have improved glycaemic control in people with type 1 diabetes mellitus. The analysis investigated predictors of improved sensor glucose time-in-range (TIR; 70-180 mg/dl) based on real-world use of the MiniMed 780G advanced hybrid closed-loop (AHCL) system.

METHODS

Data uploaded by MiniMed 780G system users from August 2020-July 2021 were analysed using univariate and multivariable models to identify baseline, demographic and system use characteristics associated with TIR after AHCL initiation (post-AHCL). System settings associated with improved TIR post-AHCL were identified and their impact on time below range (TBR, <70 mg/dl) post-AHCL was explored.

RESULTS

In total, 12 870 users were included, of which 2977 had baseline sensor glucose data. Baseline TIR and time in AHCL (defined as the percentage of time the system was in Auto-mode) were positively associated with TIR post-AHCL with larger values predicting greater mean TIR post-AHCL. Characteristics inversely associated with TIR post-AHCL included the percentage of daily basal insulin dose, daily autocorrection dose, number of daily AHCL exits triggered by the system and number of daily alarms, wherein larger values of these characteristics predicted lower mean TIR post-AHCL. System settings that predicted the largest mean TIR post-AHCL were active insulin time of 2 h and glucose target of 100 mg/dl. Active insulin time was not associated with TBR post-AHCL.

CONCLUSION

Modifiable factors, including optimized pump settings, can allow users to achieve glycaemic targets with >80% TIR. The findings from this analysis will potentially guide the optimal use of the MiniMed 780G system and facilitate meaningful improvements in safe glycaemic control.

Distress and Living with Diabetes: Defining Characteristics Through an Online Survey

INTRODUCTION

There is considerable evidence for diabetes reducing quality of life. The impact of such a diagnosis on mental health is less well understood and was subsequently explored here.

METHODS

Online PHQ-9 scores (which calculate the severity of depression), Diabetes Distress Screening Scale (DDSS) and EQ-5D-5L (quality-of-life) questionnaires were completed by patients with diabetes, followed by the extraction of data where possible from responders' clinical records.

RESULTS

A total of 133 people submitted questionnaires. However, not all data items could be completed by each patient; 35% (45/130) had type I diabetes mellitus (T1DM); 55% (64/117) were women. The overall median age of 117 responders was 60 (IQR 50-68 years). The median aggregated response scores were: EQ-5D-5L 0.74 (IQR 0.64-0.85) (lower quality of life than UK population median of 0.83), DDSS 1.9 (IQR1.3-2.7) (≥ 2 indicates moderate distress) and PHQ-9 5 (IQR2-11) (≥ 5 indicates depression). Higher diabetes distress (DDSS)/lower quality of life EQ-5D-5L/higher depressive symptoms (PHQ-9) linked to female sex (DDSS 0.5/25% above median), younger age (< 50 years DDSS 0.7/35% above median), fewer years after diagnosis (< 10 years DDSS 0.8/40% above median), and obesity (BMI > 35 DDSS 0.6/30% above median). Additionally, a HbA1c reading of ≤ 48 mmol/mol was associated with higher DDSS scores, as did a reduction of more than 5 mmol/mol in HbA1c over the last three HbA1c measurements. The 30 individuals with a history of prescribed antidepressant medication also showed higher diabetes distress scores (DDSS 0.9, equating to 45% above the median). The DDSS score elevation came from an increase in emotional burden and regimen-related distress. DDSS scores were not significantly linked to diabetes type, insulin use, absolute level/change in blood glucose HbA1c. Physician-related distress showed a similar pattern.

CONCLUSIONS

A low level of stress in relation to diabetes management may be associated with lower HbA1c. The larger impact of diabetes on mental health in younger women/people with shorter diabetes duration should be noted when considering psychosocial intervention/behavior change messaging. Physician-related distress is a potentially remediable factor. However, this sample was self-selecting, limiting generalization to other samples.

Equity in Medical Care for People Living With Diabetes

Disparities and inequities exist for individuals with diabetes in marginalized communities of color, especially among people with low socioeconomic status. Although these barriers are apparent, only a few care models have been designed for and examined in racially and ethnically diverse individuals. This article reviews models that have been developed and examined in a variety of different populations and focuses on how to implement elements from these programs in clinical practice. Health equity-promoting ideas and approaches that can be applied throughout the life span (children to seniors) are also included. As diabetes health care providers, researchers, educators, policymakers, and advocates, we must now combine our efforts and focus on historically excluded populations to bridge the gap to essential diabetes care.