Closed-Loop Insulin Delivery Versus Sensor-Augmented Pump Therapy in Older Adults With Type 1 Diabetes (ORACL): A Randomized, Crossover Trial

Effect of automated insulin delivery systems on person-reported outcomes in people with diabetes: a systematic review and meta-analysis

Background

Conclusive evidence on the benefits of automated insulin delivery (AID) systems on person-reported outcomes (PROs) is missing.

Methods

In this systematic review and meta-analysis, four databases (PubMed, PsycINFO, Cochrane, and GoogleScholar) were searched from inception up to August 7th, 2024. All types of studies were included if studies reported on PROs in people with diabetes using an AID system. All types of control groups in randomised controlled trials (RCT) were included. Summary data were extracted by three reviewers. Main outcomes focused on diabetes distress, fear of hypoglycaemia and quality of life. Meta-analyses were conducted for RCTs and observational studies separately. When five or more studies could be pooled, random-effects meta-analysis was used, otherwise common-effects meta-analysis was used. Risk of bias was evaluated with Cochrane tools. This study was registered with PROSPERO, CRD42022352502.

Findings

A total of 62 studies (n = 9253) were included reporting on 45 different questionnaires. Twenty-seven studies were RCTs and 25 were observational studies. RCT meta-analyses showed reduced diabetes distress (standardised mean difference [95% CI]: -0.159 [-0.309, -0.010], I2 = 23.0%), reduced fear of hypoglycaemia (-0.339 [-0.566, -0.111], I2 = 42.6%), and improved hypoglycaemia unawareness (-0.231 [-0.424, -0.037], I2 = 0.0%), quality of life in adults (0.347 [0.134, 0.560], I2 = 0.0%) and children/adolescents (0.249 [0.050, 0.448], I2 = 0.0%). Observational meta-analyses corroborated improvements in diabetes distress (-0.217 [-0.403, -0.031], I2 = 68.5%), fear of hypoglycaemia (-0.445 [-0.540, -0.349], I2 = 0.0%), hypoglycaemia unawareness (-0.212 [-0.419, -0.004], I2 = 0.0%), and showed improved sleep quality (-0.158 [-0.255, -0.061], I2 = 0.0%).

Interpretation

We found low to moderate effect sizes indicating that AID therapy is associated with reduced burden and improved well-being in people with diabetes. Evidence comes from both RCTs and observational studies. However, for some PROs only a limited number of studies could be pooled with a large heterogeneity in questionnaires used. More research is needed with a more uniformed assessment of PROs to demonstrate the added value of AID therapy on psychosocial outcomes.

Funding

None.

Ageing well with diabetes: the role of technology

Over the past two decades there has been a substantial rise in the adoption of diabetes therapeutic technology among children, adolescents and younger adults with type 1 diabetes, and its use is now also advocated for older individuals. Older people with diabetes are more prone to experience hypoglycaemia because of numerous predisposing factors and are at higher risk of hypoglycaemic events requiring third-party assistance as well as other adverse sequelae. Hypoglycaemia may also have long-term consequences, including cognitive impairment, frailty and disability. Diabetes in older people is often characterised by marked glucose variability related to age-associated changes such as variable appetite and levels of physical activity, comorbidities and polypharmacotherapy. Preventing hypoglycaemia and mitigating glucose excursions may have considerable positive impacts on physical and cognitive function and general well-being and may even prevent or improve frailty. Technology for older people includes continuous glucose monitoring systems, insulin pumps, automated insulin delivery systems and smart insulin pens. Clinical trials and real-world studies have shown that older people with diabetes benefit from technology in terms of glucose management, reductions in hypoglycaemic events, emergency department attendance and hospital admissions, and improvement in quality of life. However, ageing may bring physical impairments and other challenges that hinder the use of technology. Healthcare professionals should identify older adults with diabetes who may benefit from therapeutic technology and then adopt an individualised approach to education and follow-up for individuals and their caregivers. Future research should explore the impact of diabetes technology on outcomes relevant to older people with diabetes.

Closed-loop systems: recent advancements and lived experiences

INTRODUCTION

Hybrid closed loop systems are now commercially available for people with type 1 diabetes and are increasingly being adopted into clinical practice. Real-world data reflect both the glycemic and quality of life benefits reported in trials.

AREAS COVERED

In this review, we summarize the key clinical efficacy and safety evidence for hybrid closed-loop systems, and the lived experience of users with type 1 diabetes across different age groups and during pregnancy. We comment on recent and emerging advancements addressing performance limitations and user experience, as well as the use of closed-loop systems in other types of diabetes.

EXPERT OPINION

Emerging technological developments in closed-loop systems focus on improving performance and increasing automation to further optimize glycemic outcomes and improve quality of life for users. Workforce developments are now urgently required to ensure widespread equitable access to this life-changing technology. Future applications of closed-loop technology are expected to expand into other types of diabetes including type 2 diabetes.

Type 1 diabetes and frailty: A scoping review

AIMS

Advances in type 1 diabetes management are enabling more to reach older ages. Frailty is known to complicate type 2 diabetes. However, frailty in people with type 1 diabetes has not been extensively researched. This review summarises the available evidence on frailty in those with type 1 diabetes.

METHODS

A systematic search strategy was applied to multiple databases (Medline, Embase, CINAHL and Cochrane) including grey literature (Scopus, OAIster, OpenGrey, dissertation and thesis database). All evidence types were considered. English articles published after 2001 were eligible. For inclusion, participants must have been over 55 with type 1 diabetes. Frailty must have been clearly defined or assessed. The results were synthesised into a descriptive format to identify key themes.

RESULTS

Of 233 papers subject to full-text review, 23 were included. Older adult diabetes research frequently does not specify the type of diabetes; 100 articles were excluded for this reason. No articles were found specifically researching frailty in older adults with type 1 diabetes. Fourteen different definitions and nine assessments of frailty were outlined. Generally, the papers supported relaxation of glucose targets and greater adoption of diabetes technology.

CONCLUSIONS

This review highlights the paucity of evidence in older adults with type 1 diabetes and frailty. Consensus on standardised definitions and assessments of frailty would aid future research, which is urgently needed as more people with type 1 diabetes reach older ages. Identifying and addressing the key issues in this population is vital to support individuals through the challenges of ageing.

What difference does sleep make? Continuous glucose monitoring metrics during fixed-overnight time versus sleep periods among older adults with type 1 diabetes

Hypoglycaemia during sleep is a common and clinically important issue for people living with insulin-treated diabetes. Continuous glucose monitoring devices can help to identify nocturnal hypoglycaemia and inform treatment strategies. However, sleep is generally inferred, with diabetes researchers and physicians using a fixed-overnight period as a proxy for sleep-wake status when analysing and interpretating continuous glucose monitoring data. No study to date has validated such an approach with established sleep measures. Continuous glucose monitoring and research-grade actigraphy devices were worn and sleep diaries completed for 2 weeks by 28 older adults (mean age 67 years [SD 5]; 17 (59%) women) with type 1 diabetes. Using continuous glucose monitoring data from a total of 356 nights, fixed-overnight (using the recommended period of 00:00 hours-06:00 hours) and objectively-measured sleep periods were compared. The fixed-overnight period approach missed a median 57 min per night (interquartile range: 49-64) of sleep for each participant, including five continuous glucose monitoring-detected hypoglycaemia episodes during objectively-measured sleep. Twenty-seven participants (96%) had at least 1 night with continuous glucose monitoring time-in-range and time-above-range discrepancies both ≥ 10 percentage points, a clinically significant discrepancy. The utility of fixed-overnight time continuous glucose monitoring as a proxy for sleep-awake continuous glucose monitoring is inadequate as it consistently excludes actual sleep time, obscures glycaemic patterns, and misses sensor hypoglycaemia episodes during sleep. The use of validated measures of sleep to aid interpretation of continuous glucose monitoring data is encouraged.

Impaired Awareness of Hypoglycemia in Older Adults With Type 1 Diabetes: A Post Hoc Analysis of the WISDM Study

OBJECTIVE

Up to one-third of older adults with type 1 diabetes experience impaired awareness of hypoglycemia (IAH), yet the factors associated with IAH remain underexplored in older adults.

RESEARCH DESIGN AND METHODS

This post hoc analysis evaluated the clinical and glycemic correlates of IAH in adults ≥60 years old with type 1 diabetes in the WISDM study. IAH and normal awareness of hypoglycemia (NAH) were defined by a Clarke score of ≥4 or <4, respectively. Demographic, clinical, and glycemic metrics were compared in those with IAH and NAH at baseline and in whom IAH did or did not improve over 26 weeks, using descriptive statistics and a multiple logistic regression variable selection procedure.

RESULTS

Of the 199 participants (age 68.1 ± 5.7 years, 52% female), 30.6% had IAH. At baseline, participants with IAH had a longer diabetes duration and greater daytime hypoglycemia and glycemic variability, and more participants had nondetectable C-peptide levels than those with NAH. Logistic regression associated longer diabetes duration (odds ratio [OR] 1.03, 95% CI 1.01-1.05; P = 0.008) and greater daytime hypoglycemia (OR 1.31, 95% CI, 1.15-1.51; P < 0.0001) with a greater odds of IAH. A similar modeling procedure identified less daytime hypoglycemia (OR per additional percentage point 0.55, 95% CI 0.32-0.94; P = 0.029) and shorter diabetes duration (OR per additional year 0.96, 95% CI 0.91-1.004; P = 0.07) as predictors of restored awareness at 26 weeks, although the effect size for diabetes duration was not statistically significant.

CONCLUSIONS

In older adults with type 1 diabetes, longer diabetes duration and greater daytime hypoglycemia are drivers of IAH. Dedicated research can personalize IAH management.

Glucose Targets Using Continuous Glucose Monitoring Metrics in Older Adults With Diabetes: Are We There Yet?

The older population is increasing worldwide and up to 30% of older adults have diabetes. Older adults with diabetes are at risk of glucose-related acute and chronic complications. Recently, mostly in type 1 diabetes (T1D), continuous glucose monitoring (CGM) devices have proven beneficial in improving time in range (TIR glucose, 70-180 mg/dL or glucose 3.9-10 mmol/L), glycated hemoglobin (HbA1c), and in lowering hypoglycemia (time below range [TBR] glucose <70 mg/dL or glucose <3.9 mmol/L). The international consensus group formulated CGM glycemic targets relating to older adults with diabetes based on very limited data. Their recommendations, based on expert opinion, were aimed at mitigating hypoglycemia in all older adults. However, older adults with diabetes are a heterogeneous group, ranging from healthy to very complex frail individuals based on chronological, biological, and functional aging. Recent clinical trial and real-world data, mostly from healthy older adults with T1D, demonstrated that older adults often achieve CGM targets, including TIR recommended for non-vulnerable groups, but less often meet the recommended TBR <1%. Existing data also support that hypoglycemia avoidance may be more strongly related to minimization of glucose variability (coefficient of variation [CV]) rather than lower TIR. Very limited data are available for glucose goals in older adults adjusted for the complexity of their health status. Herein, we review the bidirectional associations between glucose and health status in older adults with diabetes; use of diabetes technologies, and their impact on glucose control; discuss current guidelines; and propose a new set of CGM targets for older adults with insulin-treated diabetes that are individualized for health and living status.

A cross-sectional questionnaire study: Impaired awareness of hypoglycaemia remains prevalent in adults with type 1 diabetes and is associated with the risk of severe hypoglycaemia

OBJECTIVE

Impaired awareness of hypoglycaemia (IAH) is a risk factor for severe hypoglycaemia (SH) in type 1 diabetes (T1D). Much of the IAH prevalence data comes from older studies where participants did not have the benefit of the latest insulins and technologies. This study surveyed the prevalence of IAH and SH in a tertiary adult clinic population and investigated the associated factors.

METHODS

Adults (≥18 years) attending a tertiary T1D clinic completed a questionnaire, including a Gold and Clarke score. Background information was collected from health records.

RESULTS

189 people (56.1% female) with T1D (median [IQR] disease duration 19.3 [11.5, 29.1] years and age of 41.0 [29.0, 52.0] years) participated. 17.5% had IAH and 16.0% reported ≥1 episode of SH in the previous 12 months. Those with IAH were more likely to report SH (37.5% versus 11.7%, p = 0.001) a greater number of SH episodes per person (median [IQR] 0 [0,2] versus 0 [0,0] P<0.001) and be female (72.7% versus 52.6%, p = 0.036). Socio-economic deprivation was associated with IAH (p = 0.032) and SH (p = 0.005). Use of technology was the same between IAH vs aware groups, however, participants reporting SH were more likely to use multiple daily injections (p = 0.026). Higher detectable C-peptide concentrations were associated with a reduced risk of SH (p = 0.04).

CONCLUSION

Insulin pump and continuous glucose monitor use was comparable in IAH versus aware groups. Despite this, IAH remains a risk factor for SH and is prevalent in females and in older people. Socioeconomic deprivation was associated with IAH and SH, making this an important population to target for interventions.

Driving-Related Glucose Patterns Among Older Adults with Type 1 Diabetes

Older adults with type 1 diabetes may face challenges driving safely. Glucose "above-5-to-drive" is often recommended for insulin-treated diabetes to minimize hypoglycemia while driving. However, the effectiveness of this recommendation among older adults has not been evaluated. Older drivers with type 1 diabetes were assessed while using sensor-augmented insulin pumps during a 2-week clinical trial run-in. Twenty-three drivers (median age 69 years [interquartile range; IQR 65-72]; diabetes duration 37 years [20-45]) undertook 618 trips (duration 10 min [5-21]). Most trips (n = 535; 87%) were <30 min duration; 9 trips (1.5%) exceeded 90 min and 3 trips (0.5%) exceeded 120 min. Pre-trip continuous glucose monitoring (CGM) was >5.0 mmol/L for 577 trips (93%) and none of these had CGM <3.9 mmol/L during driving (including 8 trips >90 min and 3 trips >120 min). During 41 trips with pre-trip CGM ≤5.0 mmol/L, 11 trips had CGM <3.9 mmol/L. Seventy-one CGM alerts occurred during 60 trips (10%), of which 54 of 71 alerts (76%) were unrelated to hypoglycemia. Our findings support a glucose "above-5-to-drive" recommendation to avoid CGM-detected hypoglycemia among older drivers, including for prolonged drives, and highlight the importance of active CGM low-glucose alerts to prevent hypoglycemia during driving. Driving-related CGM usability and alert functionality warrant investigation. Clinical trial ACTRN1261900515190.

Hypoglycemia and Hyperglycemia According to Type of Diabetes: Observations During Fully Closed-Loop Insulin Delivery in Adults With Type 1 and Type 2 Diabetes

BACKGROUND

CamAPS HX fully closed-loop (FCL) system, with no user input required at mealtimes, has been shown to be safe and effective in adults with type 1 and type 2 diabetes. We assessed whether time spent in hypoglycemia and hyperglycemia during FCL insulin delivery in adults varied by type of diabetes over the 24-hour period.

METHODS

We retrospectively analyzed eight weeks of data from 52 participants (adults with type 1 diabetes and adults with insulin-treated type 2 diabetes) recruited to two single-center randomized controlled studies using FCL insulin delivery during unrestricted-living conditions. Key outcomes were time spent in hypoglycemia <70 mg/dL and marked hyperglycemia >300 mg/dL by type of diabetes.

RESULTS

The median percentage of time spent in hypoglycemia <70 mg/dL over the 24-hour period was lower for those with type 2 diabetes than for those with type 1 diabetes (median [interquartile range (IQR)] 0.43% [0.20-0.77] vs 0.86%, [0.54-1.46]; mean difference 0.46 percentage points [95% CI 0.23-0.70]; P < .001). Median percentage time in marked hyperglycemia >300 mg/dL was lower for those with type 2 diabetes than for those with type 1 diabetes (median [IQR] 1.8% [0.6-3.5] vs 9.3% [6.9-11.8]; mean difference 7.8 percentage points [95% CI 5.5-10.0]; P < .001).

CONCLUSIONS

Using the FCL system, hypoglycemia and marked hyperglycemia exposure were lower in type 2 diabetes than in type 1 diabetes.

Real-world lived experience of older adults with type 1 diabetes after an automated insulin delivery trial

AIMS

First-generation closed-loop automated insulin delivery improves glycaemia and psychosocial outcomes among older adults with type 1 diabetes in clinical trials. However, no study has previously assessed real-world lived experience of older adults using closed-loop therapy outside a trial environment.

METHODS

Semi-structured interviews were conducted with older adults who were pre-existing insulin pump users and previously completed the OldeR Adult Closed-Loop (ORACL) randomised trial. Interviews focused on perceptions of diabetes technology use, and factors influencing decisions regarding continuation.

RESULTS

Twenty-eight participants, mean age 70 years (SD 5), were interviewed at median 650 days (IQR 608-694) after their final ORACL trial visit. At interview, 23 participants (82%) were still using a commercial closed-loop system (requiring manual input for prandial insulin bolus doses). Themes discussed in interviews relating to closed-loop system use included sustained psychosocial benefits, cost and retirement considerations and usability frustrations relating to sensor accuracy and system alarms. Of the five participants who had discontinued, reasons included cost, continuous glucose monitoring-associated difficulties and usability frustrations. Cost was the largest consideration regarding continued use; most participants considered the increased ease of diabetes management to be worth the associated costs, though cost was prohibitive for some.

CONCLUSIONS

Almost 2 years after completing a closed-loop clinical trial, closed-loop automated insulin delivery remains the preferred type 1 diabetes therapy for the majority of older adult participants. Chronological age is not a barrier to real-world successful use of diabetes technology. Identifying age-related barriers, and solutions, to diabetes technology use among older adults is warranted.

Characteristics Associated With Elevated Time Below Range in Elderly Patients With Type 1 Diabetes Using an Automated Insulin Delivery System

BACKGROUND

This study investigated the characteristics associated with an increased risk of hypoglycemia, in elderly patients with type 1 diabetes mellitus (T1D) using automated insulin delivery (AID) systems.

METHODS

Cross-sectional observational study including patients >60 years, using sensor-augmented insulin pump therapy with predictive low-glucose management (SAPT-PLGM), hybrid closed-loop (HCL), and advanced hybrid closed-loop (AHCL), for more than three months. A geriatric assessment was performed, and body composition was determined to investigate its association with achieving time below range (TBR) <70 mg/dL goals.

RESULTS

The study included 59 patients (47.5% of men, mean age of 67.6 years, glycated hemoglobin [HbA1c] of 7.5 ± 0.6%, time in range (TIR) 77.8 ± 9.9%). Time below range <70 and <54 mg/dL were 2.2 ± 2.3% and 0.4 ± 0.81%, respectively. Patients with elevated TBR <70 mg/dL (>1%) had higher HbA1c levels, lower TIR, elevated time above range (TAR), and high glycemic variability. Regarding body composition, greater muscle mass, grip strength, and visceral fat were associated with a lower TBR <70 mg/dL. These factors were independent of the type of technology used, but TIR was higher when using AHCL systems compared with SAPT-PLGM and HCL systems.

CONCLUSIONS

In elderly patients treated with AID systems with good functional status, lower lean mass, lower grip strength, and lower visceral fat percentage were associated with TBR greater than 1%, regardless of the device used. A similar finding along was found with CGM indicators such as higher HbA1c levels, lower TIR, higher TAR, and higher CV. Geriatric assessment is crucial for personalizing patient management.

Real-World Evidence of Automated Insulin Delivery System Use

Objective: Pivotal trials of automated insulin delivery (AID) closed-loop systems have demonstrated a consistent picture of glycemic benefit, supporting approval of multiple systems by the Food and Drug Administration or Conformité Européenne mark receipt. To assess how pivotal trial findings translate to commercial AID use, a systematic review of retrospective real-world studies was conducted. Methods: PubMed and EMBASE were searched for articles published after 2018 with more than five nonpregnant individuals with type 1 diabetes (T1D). Data were screened/extracted in duplicate for sample size, AID system, glycemic outcomes, and time in automation. Results: Of 80 studies identified, 20 met inclusion criteria representing 171,209 individuals. Time in target range 70-180 mg/dL (3.9-10.0 mmol/L) was the primary outcome in 65% of studies, with the majority of reports (71%) demonstrating a >10% change with AID use. Change in hemoglobin A1c (HbA1c) was reported in nine studies (range 0.1%-0.9%), whereas four reported changes in glucose management indicator (GMI) with a 0.1%-0.4% reduction noted. A decrease in HbA1c or GMI of >0.2% was achieved in two-thirds of the studies describing change in HbA1c and 80% of articles where GMI was described. Time below range <70 mg/dL (<3.9 mmol/L) was reported in 16 studies, with all but 1 study showing stable or reduced levels. Most systems had >90% time in automation. Conclusion: With larger and more diverse populations, and follow-up periods of longer duration (∼9 months vs. 3-6 months for pivotal trials), real-world retrospective analyses confirm pivotal trial findings. Given the glycemic benefits demonstrated, AID is rapidly becoming the standard of care for all people living with T1D. Individuals should be informed of these systems and differences between them, have access to and coverage for these technologies, and receive support as they integrate this mode of insulin delivery into their lives.

13. Older Adults: Standards of Care in Diabetes-2024

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Automated insulin delivery among adults with type 1 diabetes for up to 2 years: a real-world, multicentre study

BACKGROUND AND AIMS

Automated insulin delivery (AID) improves glycaemia among people with type 1 diabetes in clinical trials and overseas real-world studies. Whether improvements are sustained beyond 12 months in the real world, and whether they occur in the Australian context, has not yet been established. We aimed to observe, up to 2 years, the effectiveness of initiating first-generation AID for type 1 diabetes management.

METHODS

Retrospective, real-world, observational study using medical records, conducted across five sites in Australia. Adults with type 1 diabetes, who had AID initiated between February 2019 and December 2021, were observed for 6-24 months after initiation (until June 2022). Outcomes examined included glucose metrics assessed by glycated haemoglobin (HbA1c ) and continuous glucose monitoring (CGM), safety and therapy continuation.

RESULTS

Ninety-four adults were studied (median age 39 years (interquartile range, IQR: 31-51); pre-initiation HbA1c 7.8% (7.2-8.6)). After AID initiation, HbA1c decreased by mean 0.5 percentage points (95% confidence interval (CI): -0.7 to -0.2) at 3 months (P < 0.001); CGM time in range 3.9-10.0 mmol/L increased by 11 percentage points (9-14) at 1 month (P < 0.001); these improvements were maintained up to 24 months (all P < 0.02). Median CGM time below 3.9 mmol/L was <1.5% pre- and post-AID initiation. The subgroup with pre-initiation HbA1c above 8.5% had the greatest HbA1c improvement (-1.4 percentage points (-1.8 to -1.1) at 3 months). Twelve individuals (13%) discontinued AID, predominantly citing difficulties with CGM. During the 150 person-years observed, four diabetes-related emergencies were documented: three severe hypoglycaemic events and one hyperglycaemic event without ketoacidosis.

CONCLUSIONS

Early glucose improvements were observed after real-world AID initiation, sustained up to 2 years, without excess adverse events. The greatest benefits were observed among individuals with highest glycaemia before initiation. Future-generation systems with increased user-friendliness may enhance therapy continuation.

Safety Event Outcomes and Glycemic Control with a Hybrid Closed-Loop System Used by Chinese Adolescents and Adults with Type 1 Diabetes Mellitus

Background: While evidence supports glycemic control benefits for individuals with type 1 diabetes mellitus (T1DM) using hybrid closed-loop (HCL) systems, HCL automated insulin delivery therapy in China has not been assessed. This study evaluated safety events and effectiveness during HCL system use by Chinese adolescents and adults with T1DM. Methods: Sixty-two participants (n = 12 adolescents with a mean ± standard deviation [SD] of 15.5 ± 1.1 years and n = 50 adults [mean ± SD of 37.6 ± 11.1 years]) with T1DM and baseline A1C of 7.1% ± 1.0% underwent a run-in period (∼2 weeks) using open-loop Manual Mode (sensor-augmented pump) insulin delivery with the MiniMed™ 770G system with the Guardian™ Sensor (3) glucose sensor, followed by a study period (4 weeks) with HCL Auto Mode enabled. Analyses compared continuous glucose monitoring data and insulin delivered during the run-in versus study period (Wilcoxon signed-rank test or t-test). Safety events included rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Compared to baseline run-in, overall Auto Mode use increased time in range (TIR, 70-180 mg/dL) from 75.3% to 80.9% (P < 0.001) and reduced time below range (TBR, <70 mg/dL) from 4.7% to 2.2% (P < 0.001). Subgroup analysis demonstrated that participants (n = 29) with baseline A1C <7.0% had TBR that reduced from 5.6% to 2.0%, while participants (n = 21) with baseline A1C ≥7.5% had time above range (TAR, >180 mg/dL) that reduced from 31.6% to 20.8%. Auto Mode use also increased the percentage achieving combined recommendations for time at sensor glucose ranges (i.e., TIR of >70%, TBR of <4% and TAR of <25%) from 24.2% at baseline to 77.4% at study end. Total daily insulin dose reduced from 42.8 ± 19.8 to 40.7 ± 18.9 U (P = 0.013). There were no severe hypoglycemic, DKA, or serious adverse events. Conclusions: Chinese adolescents and adults, some of whom met target A1C at baseline, safely achieved significantly improved glycemia with 1 month of MiniMed 770G system use when compared to open-loop insulin delivery. ClinicalTrials.gov ID: NCT04663295.

Glucose control and psychosocial outcomes with use of automated insulin delivery for 12 to 96 weeks in type 1 diabetes: a meta-analysis of randomised controlled trials

BACKGROUND

Glycaemic control of Type 1 Diabetes Mellitus (T1DM) remains a challenge due to hypoglycaemic episodes and the burden of insulin self-management. Advancements have been made with the development of automated insulin delivery (AID) devices, yet, previous reviews have only assessed the use of AID over days or weeks, and potential benefits with longer time of AID use in this population remain unclear.

METHODS

 We performed a systematic review and meta-analysis of randomised controlled trials comparing AID (hybrid and fully closed-loop systems) to usual care (sensor augmented pumps, multiple daily insulin injections, continuous glucose monitoring and predictive low-glucose suspend) for adults and children with T1DM with a minimum duration of 3 months. We searched PubMed, Embase, Cochrane Central, and Clinicaltrials.gov for studies published up until April 4, 2023. Main outcomes included time in range 70-180 mg/dL as the primary outcome, and change in HbA1c (%, mmol/mol), glucose variability, and psychosocial impact (diabetes distress, treatment satisfaction and fear of hypoglycaemia) as secondary outcomes. Adverse events included diabetic ketoacidosis (DKA) and severe hypoglycaemia. Statistical analyses were conducted using mean differences and odds ratios. Sensitivity analyses were performed according to age, study duration and type of AID device. The protocol was registered in PROSPERO, CRD42022366710.

RESULTS

We identified 25 comparisons from 22 studies (six crossover and 16 parallel designs) including a total of 2376 participants (721 in adult studies, 621 in paediatric studies, and 1034 in combined studies) which were eligible for analysis. Use of AID devices ranged from 12 to 96 weeks. Patients using AID had 10.87% higher time in range [95% CI 9.38 to 12.37; p < 0.0001, I2 = 87%) and 0.37% (4.77 mmol/mol) lower HbA1c (95% CI - 0.49% (- 6.39 mmol/mol) to - 0.26 (- 3.14 mmol/mol); p < 0·0001, I2 = 77%]. AID systems decreased night hypoglycaemia, time in hypoglycaemia and hyperglycaemia and improved patient distress, with no increase in the risk of DKA or severe hypoglycaemia. No difference was found regarding treatment satisfaction or fear of hypoglycaemia. Among children, there was no difference in glucose variability or time spent in hypoglycaemia between the use of AID systems or usual care. In sensitivity analyses, results remained consistent with the overall analysis favouring AID.

CONCLUSION

The use of AID systems over 12 weeks, regardless of technical or clinical differences, improved glycaemic outcomes and diabetes distress without increasing the risk of adverse events in adults and children with T1DM.

Patient-reported outcomes for older adults on CamAPS FX closed loop system

AIMS

Use of the CamAPS FX hybrid closed loop (CL) system is associated with improved time in range and glycated haemoglobin A1c across the age span, but little is known about its effects on patient-reported outcomes (PROs).

METHODS

This open-label, randomized, multi-site study compared CamAPS FX to sensor-augmented pump (SAP) in a sample of older adults (≥60 years) with type 1 diabetes (T1D). Thirty-five older adults completed PROs surveys at the start of the study and after each period of 16 weeks using either CL or SAP. At the end of the study, 19 participated in interviews about their experiences with CL.

RESULTS

Results examining the 16 weeks of CL use showed that the overall Diabetes Distress Scale score and two subscales (powerlessness and physician distress) improved significantly along with trust on the Glucose Monitoring Satisfaction Survey. User experience interview responses were consistent in noting benefits of 'improved glycaemic control' and 'worrying less about diabetes'.

CONCLUSION

In this sample of older adults with T1D who have previously shown glycaemic benefit, there are indicators of improved PROs and subjective user experience benefits.

Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial

INTRODUCTION

Do-it-yourself artificial pancreas system (DIY APS) is built using commercially available insulin pump, continuous glucose monitoring (CGM) and an open-source algorithm. Compared with commercial products, DIY systems are affordable, allow personalised settings and provide updated algorithms, making them a more promising therapy for most patients with type 1 diabetes mellitus (T1DM). Many small and self-reported observational studies have found that their real-world use was associated with potential metabolic and psychological benefits. However, rigorous-designed studies are urgently needed to confirm its efficacy and safety.

METHODS AND ANALYSIS

In this 26-week randomised, open-label, two-arm, two-phase, crossover trial, participants aged 18-75 years, with T1DM and glycated haemoglobin (HbA1c) 7-11%, will use AndroidAPS during one 12-week period and sensor-augmented pump during another 12-week period. This study will recruit at least 24 randomised participants. AndroidAPS consists of three components: (1) real-time CGM; (2) insulin pump; (3) AndroidAPS algorithm implemented in Android smartphone. The primary endpoint is time in range (3.9-10.0 mmol/L) derived from CGM. The main secondary endpoints include percentage of sensor glucose values below, within and above target range; mean sensor glucose value; measures of glycaemic variability and centralised HbA1c. Safety endpoints mainly include the frequency of hypoglycaemia events, diabetic ketoacidosis and other serious adverse events.

ETHICS AND DISSEMINATION

This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University. There will be verbal and written information regarding the trial given to each participant. The study will be disseminated through peer-reviewed publications and conference presentations.

OVERALL STATUS

Recruiting.

STUDY START

11 February 2023.

PRIMARY COMPLETION

31 July 2024.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Registry (NCT05726461).

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.

The Growing Role of Technology in the Care of Older Adults With Diabetes

The integration of technologies such as continuous glucose monitors, insulin pumps, and smart pens into diabetes management has the potential to support the transformation of health care services that provide a higher quality of diabetes care, lower costs and administrative burdens, and greater empowerment for people with diabetes and their caregivers. Among people with diabetes, older adults are a distinct subpopulation in terms of their clinical heterogeneity, care priorities, and technology integration. The scientific evidence and clinical experience with these technologies among older adults are growing but are still modest. In this review, we describe the current knowledge regarding the impact of technology in older adults with diabetes, identify major barriers to the use of existing and emerging technologies, describe areas of care that could be optimized by technology, and identify areas for future research to fulfill the potential promise of evidence-based technology integrated into care for this important population.

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.

Type 1 Diabetes and Aging

The number of older adults with type 1 diabetes (T1D) is increasing due to an overall increase in life expectancy and improvement in diabetes management and treatment of complications. They are a heterogeneous cohort due to the dynamic process of aging and the presence of comorbidities and diabetes-related complications. A high risk for hypoglycemia unawareness and severe hypoglycemia has been described. Periodic assessment of health status and adjustment of glycemic goals to mitigate hypoglycemia is imperative. Continuous glucose monitoring, insulin pump, and hybrid closed-loop systems are promising tools to improve glycemic control and mitigate hypoglycemia in this age group.

Time spent in hypoglycemia according to age and time-of-day: Observations during closed-loop insulin delivery

OBJECTIVE

We aimed to assess whether percentage of time spent in hypoglycemia during closed-loop insulin delivery differs by age-group and time-of-day.

METHODS

We retrospectively analyzed data from hybrid closed-loop studies involving young children (2-7 years), children and adolescents (8-18 years), adults (19-59 years), and older adults (≥60 years) with type 1 diabetes. Main outcome was time spent in hypoglycemia <3.9mmol/l. Eight weeks of data for 88 participants were analyzed.

RESULTS

Median time spent in hypoglycemia over the 24-hour period was highest in children and adolescents (4.4%; [IQR 2.4-5.0]) and very young children (4.0% [3.4-5.2]), followed by adults (2.7% [1.7-4.0]), and older adults (1.8% [1.2-2.2]); p<0.001 for difference between age-groups. Time spent in hypoglycemia during nighttime (midnight-05:59) was lower than during daytime (06:00-23:59) across all age-groups.

CONCLUSION

Time in hypoglycemia was highest in the pediatric age-group during closed-loop insulin delivery. Hypoglycemia burden was lowest overnight across all age-groups.

Switching from treatment with sensor augmented pump to hybrid closed loop system in type 1 diabetes: impact on glycemic control and neuropsychological tests in the real world

AIMS

The aim of this study is to assess in the real world the impact of initiating hybrid closed loop (HCL) on glycemic control and quality of life in patients using sensor-augmented pump (SAP).

METHODS

In this prospective study, patients using SAP changed to an HCL system in a specialized hospital. HCL devices used were Medtronic 780G®, Tandem Control-IQ® and Diabeloop® system. Glucometric data and hypoglycemia and neuropsychological tests were assessed at baseline and 3 months after initiating HCL.

RESULTS

A total of 66 consecutive patients were included (74% women, mean age 44±11 years, diabetes duration 27.2 ±11 years). Significant improvements were observed in coefficient of variation (from 35.6% to 33.1%), time in range (from 62.2 % to 73.8%), time above 180 mg/dl (from 26.9% to 18%), time below 70 mg/dl (from 3.3% to 2.1%) and time below 55 mg/dl (from 0.7% to 0.3%). In addition, significant improvements were observed in fear of hypoglycemia and grade of distress associated to treatment and to interpersonal sphere.

CONCLUSIONS

Switching from SAP to HCL system improves time in range and reduces time in hypoglycemia and glycemic variability at 3 months. These changes are accompanied by significant reduction of neuropsychological burden related to diabetes.

Continuous glucose monitoring-based composite metrics: a review and assessment of performance in recent-onset and long-duration type 1 diabetes

This study examined correlations between continuous glucose monitoring (CGM)-based composite metrics and standard glucose metrics within CGM data sets from individuals with recent-onset and long-duration type 1 diabetes. First, a literature review and critique of published CGM-based composite metrics was undertaken. Second, composite metric results were calculated for the two CGM data sets and correlations with six standard glucose metrics were examined. Fourteen composite metrics met selection criteria; these metrics focused on overall glycemia (n = 8), glycemic variability (n = 4), and hypoglycemia (n = 2), respectively. Results for the two diabetes cohorts were similar. All eight metrics focusing on overall glycemia strongly correlated with glucose time in range; none strongly correlated with time below range. The eight overall glycemia-focused and two hypoglycemia-focused composite metrics were all sensitive to automated insulin delivery therapeutic intervention. Until a composite metric can adequately capture both achieved target glycemia and hypoglycemia burden, the current two-dimensional CGM assessment approach may offer greatest clinical utility.

Lived experience of older adults with type 1 diabetes using closed-loop automated insulin delivery in a randomised trial

AIM

To explore the lived experience of older adults with type 1 diabetes using closed-loop automated insulin delivery, an area previously receiving minimal attention.

METHODS

Semi-structured interviews were conducted with adults aged 60 years or older with long-duration type 1 diabetes who participated in a randomised, open-label, two-stage crossover trial comparing first-generation closed-loop therapy (MiniMed 670G) versus sensor-augmented pump therapy. Interview recordings were transcribed, thematically analysed and assessed.

RESULTS

Twenty-one older adults participated in interviews after using closed-loop therapy. Twenty were functionally independent, without frailty or major cognitive impairment; one was dependent on caregiver assistance, including for diabetes management. Quality of life benefits were identified, including improved sleep and reduced diabetes-related psychological burden, in the context of experiencing improved glucose levels. Gaps between expectations and reality of closed-loop therapy were also experienced, encountering disappointment amongst some participants. The cost was perceived as a barrier to continued closed-loop access post-trial. Usability issues were identified, such as disruptive overnight alarms and sensor inaccuracy.

CONCLUSIONS

The lived experience of older adults without frailty or major cognitive impairment using first-generation closed-loop therapy was mainly positive and concordant with glycaemic benefits found in the trial. Older adults' lived experience using automated insulin delivery beyond trial environments requires exploration; moreover, the usability needs of older adults should be considered during future device development.

Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice

The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.

An Assessment of Clinical Continuous Glucose Monitoring Targets for Older and High-Risk People Living with Type 1 Diabetes

Aim: To assess relationships between continuous glucose monitoring (CGM) time in range (TIR), 70-180 mg/dL, time below range (TBR), <70 mg/dL, time above range (TAR), >180 mg/dL, and glucose coefficient of variation (CV) in relation to currently recommended clinical CGM targets for older people, which recommend reduced TIR and TBR targets relative to the general type 1 diabetes population. Methods: We conducted a post hoc analysis using the JDRF Australia Adult Hybrid Closed Loop trial database examining correlations in 120 adults with type 1 diabetes of 3 weeks masked CGM (Guardian Sensor 3; Medtronic) metrics (n = 61 on multiple daily injections, 59 on non-CGM augmented pumps) using manual insulin dosing at baseline and at 26-weeks, with 50% randomized to automated insulin dosing (AID). Results: Correlations between baseline TIR and TAR were strong (r = -0.966; P < 0.0001), weak for TBR (r = 0.363; P < 0.0001), and glucose CV (r = 0.037; P = 0.687) while moderate between CV and TBR (r = 0.726; P < 0.0001). Associations were similar for participants aged >60 years (n = 15) versus younger subjects. Correlations of changes in (Δ) TIR with ΔTAR over 26 weeks were strong (r = -0.945; P < 0.001) and correlations for ΔTBR were weak (r = 0.025; P = 0.802). ΔCV did not significantly correlate with ΔTAR (r = -0.064; P = 0.526) but did with ΔTBR (r = 0.770; P = <0.001). Conclusions: Changes in TIR are not associated with changes in TBR. Thus, we recommend that for older AID users whilst TBR targets should be prioritized to reduce hypoglycemia-related risk, TBR should be addressed independently of TIR. Clinical Trial Registratrion number: (ACTRN12617000520336).

13. Older Adults: Standards of Care in Diabetes-2023

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Continuous glucose monitoring and metrics for clinical trials: an international consensus statement

Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.

Glucose profiles of older adults with type 1 diabetes using sensor-augmented pump therapy in Australia: pre-randomisation results from the ORACL study

BACKGROUND

Older adults with type 1 diabetes are recommended modified glucose targets. However, data on the effects of diabetes technology in older age are scarce. We assessed older adults established on sensor-augmented insulin pump therapy during clinical trial run-in and compared their continuous glucose monitoring (CGM) profiles with consensus recommendations. We aimed to provide insight into the applicability of currently recommended CGM-based targets while accounting for current Diabetes UK guidelines.

METHODS

In this analysis, adults aged 60 years or older with type 1 diabetes with a duration of at least 10 years and entering the Older Adult Closed Loop (ORACL) trial were studied. The trial was done at two tertiary hospitals in Australia. Individuals who were independent with diabetes self-management, as well as those receiving caregiver assistance for their diabetes management, were eligible for inclusion. Participants underwent baseline clinical assessment, which included medical history and examination, testing for frailty, functional ability, cognitive functioning, psychosocial wellbeing, and subjective sleep quality; fasting venous blood samples were collected for C-peptide, glucose, and glycated haemoglobin A_1c measurement. Sensor-augmented pumps, carbohydrate-counting education, and diabetes education were provided to participants by diabetes nurse educators, dietitians, and endocrinologists experienced in type 1 diabetes clinical care. CGM data were subsequently collected for 2 weeks during sensor-augmented pump therapy. The ORACL trial is registered with the Australian New Zealand Clinical Trial Registry, ACTRN12619000515190.

FINDINGS

Our analysis included all 30 participants who completed the ORACL trial run-in-19 (63%) women and 11 (37%) men (mean age 67 years [SD 5], median diabetes duration 38 years [IQR 20-47], and insulin total daily dose 0·55 units [0·41-0·66] per kg bodyweight). Ten (33%) of 30 participants had impaired hypoglycaemia awareness and six (20%) were pre-frail; none were frail. The median CGM time in range 3·9-10·0 mmol/L was 71% (IQR 64-79). The time spent with glucose above 10·0 mmol/L was 27% (18-35) and above 13·9 mmol/L was 3·9% (2·4-10·2). The time with glucose below 3·9 mmol/L was 2·0% (1·2-3·1) and the time below 3·0 mmol/L was 0·2% (0·1-0·4). Only two (7%) of 30 participants met all CGM-based consensus recommendations modified for older adults. Time in hypoglycaemia was lower among the 16 participants with predictive low-glucose alerts enabled than among the 14 participants not using predictive low-glucose alerts (median difference -1·1 percentage points [95% CI -2·0 to -0·1]; p=0·038). This difference was even greater overnight (-2·3 percentage points [-3·2 to -1·0]; p=0·0018). One serious adverse event occurred (elective cardiac stent).

INTERPRETATION

Using sensor-augmented pumps after multidisciplinary education, this group of older adults without frailty achieved a time in range far exceeding minimum consensus recommendations. However, the current stringent hypoglycaemia recommendations for all older adults were not met. Predictive low alerts could reduce hypoglycaemia, particularly overnight. Investigation into the effectiveness of CGM-based targets that consider frailty, functional status, and diabetes therapies for older adults is warranted.

FUNDING

JDRF and Diabetes Australia.

Biobehavioral Changes Following Transition to Automated Insulin Delivery: A Large Real-life Database Analysis

OBJECTIVE

To document glycemic and user-initiated bolus changes following transition from predictive low glucose suspend (PLGS) system to automated insulin delivery (AID) system during real-life use.

RESEARCH DESIGN AND METHODS

We conducted analysis of 2,329,166 days (6,381 patient-years) of continuous glucose monitoring (CGM) and insulin therapy data for 19,354 individuals with type 1 Diabetes, during 1-month PLGS use (Basal-IQ technology) followed by 3-month AID use (Control-IQ technology). Baseline characteristics are as follows: 55.4% female, age (median/quartiles/range) 39/19-58/1-92 years, mean ± SD glucose management indicator (GMI) 7.5 ± 0.8. Primary outcome was time in target range (TIR) (70-180 mg/dL). Secondary outcomes included CGM-based glycemic control metrics and frequency of user-initiated boluses.

RESULTS

Compared with PLGS, AID increased TIR on average from 58.4 to 70.5%. GMI and percent time above and below target range improved as well: from 7.5 to 7.1, 39.9 to 28.1%, and 1.66 to 1.46%, respectively; all P values <0.0001. Stratification of outcomes by age and baseline GMI revealed clinically significant differences. Glycemic improvements were most pronounced in those <18 years old (TIR improvement 14.0 percentage points) and those with baseline GMI >8.0 (TIR improvement 13.2 percentage points). User-initiated correction boluses decreased from 2.7 to 1.8 per day, while user-initiated meal boluses remained stable at 3.6 to 3.8 per day.

CONCLUSIONS

Observed in real life of >19,000 individuals with type 1 diabetes, transitions from PLGS to AID resulted in improvement of all glycemic parameters, equivalent to improvements observed in randomized clinical trials, and reduced user-initiated boluses. However, glycemic and behavioral changes with AID use may differ greatly across different demographic and clinical groups.

Closed-loop insulin delivery: update on the state of the field and emerging technologies

INTRODUCTION

Over the last five years, closed-loop insulin delivery systems have transitioned from research-only to real-life use. A number of systems have been commercialized and are increasingly used in clinical practice. Given the rapidity of new developments in the field, understanding the capabilities and key similarities and differences of current systems can be challenging. This review aims to provide an update on the state of the field of closed-loop insulin delivery systems, including emerging technologies.

AREAS COVERED

We summarize key clinical safety and efficacy evidence of commercial and emerging insulin-only hybrid closed-loop systems for type 1 diabetes. A literature search was conducted and clinical trials using closed-loop systems during free-living conditions were identified to report on safety and efficacy data. We comment on emerging technologies and adjuncts for closed-loop systems, as well as non-technological priorities in closed-loop insulin delivery.

EXPERT OPINION

Commercial hybrid closed-loop insulin delivery systems are efficacious, consistently improving glycemic control when compared to standard therapy. Challenges remain in widespread adoption due to clinical inertia and the lack of resources to embrace technological developments by health care professionals.

Fluidic enabled bioelectronic implants: opportunities and challenges

Bioelectronic implants are increasingly facilitating novel strategies for clinical diagnosis and treatment. The integration of fluidic technologies into such implants enables new complementary routes for sensing and therapy alongside electrical interaction. Indeed, these two technologies, electrical and fluidic, can work synergistically in a bioelectronics implant towards the fabrication of a complete therapeutic platform. In this perspective article, the leading applications of fluidic enabled bioelectronic implants are highlighted and methods of operation and material choices are discussed. Furthermore, a forward-looking perspective is offered on emerging opportunities as well as critical materials and technological challenges.

Closed-Loop Insulin Delivery Effects on Glycemia During Sleep and Sleep Quality in Older Adults with Type 1 Diabetes: Results from the ORACL Trial

Sleep-related effects of closed-loop therapy among older adults with type 1 diabetes have not been well established. In the OldeR Adult Closed-Loop (ORACL) randomized, crossover trial of first-generation closed-loop therapy (MiniMed 670G), participants wore actigraphy and completed sleep diaries for 14-day periods at stage end. During objectively measured sleep (actigraphy) with closed-loop versus sensor-augmented pump therapy, glucose time-in-range 70-180 mg/dL (3.9-10.0 mmol/L) was greater (90.3% vs. 78.7%, respectively; difference 8.2 percentage points [95% confidence interval {CI} 1.5 to 13.0]; P = 0.008), and there were fewer sensor hypoglycemia episodes (18 vs. 43, respectively; incident rate ratio 0.40 [95% CI 0.20 to 0.55]; P = 0.007). Sleep quality recorded daily was worse with closed-loop therapy (P = 0.006); Pittsburgh Sleep Quality Index did not differ. There were 30% more system alarms during monitored sleep with closed-loop therapy (P < 0.001). First-generation closed-loop therapy has important glycemic benefits during sleep for older adults, with deterioration in some sleep quality measures. Sleep quality warrants prioritization and investigation during advancement of closed-loop technology.

Practical Guidance on Open Source and Commercial Automated Insulin Delivery Systems: A Guide for Healthcare Professionals Supporting People with Insulin-Requiring Diabetes

As increasing numbers of people with insulin-managed diabetes use automated insulin delivery (AID) systems or seek such technologies, healthcare providers are faced with a steep learning curve. Healthcare providers need to understand how to support these technologies to help inform shared decision making, discussing available options, implementing them in the clinical setting, and guiding users in special situations. At the same time, there is a growing diversity of commercial and open source automated insulin delivery systems that are evolving at a rapid pace. This practical guide seeks to provide a conversational framework for healthcare providers to first understand and then jointly assess AID system options with users and caregivers. Using this framework will help HCPs in learning how to evaluate potential new commercial or open source AID systems, while also providing a guide for conversations to help HCPs to assess the readiness and understanding of users for AID systems. The choice of an AID system is not as simple as whether the system is open source or commercially developed, and indeed there are multiple criteria to assess when choosing an AID system. Most importantly, the choices and preferences of the person living with diabetes should be at the center of any decision around the ideal automated insulin delivery system or any other diabetes technology. This framework highlights issues with AID use that may lead to burnout or perceived failures or may otherwise cause users to abandon the use of AID. It discusses the troubleshooting of basic AID system operation and discusses more advanced topics regarding how to maximize the time spent on AID systems, including how to optimize settings and behaviors for the best possible outcomes with AID technology for people with insulin-requiring diabetes. This practical approach article demonstrates how healthcare providers will benefit from assessing and better understanding all available AID system options to enable them to best support each individual.

Benefit of Continuous Glucose Monitoring in Reducing Hypoglycemia Is Sustained Through 12 Months of Use Among Older Adults with Type 1 Diabetes

Objective: To evaluate glycemic outcomes in the Wireless Innovation for Seniors with Diabetes Mellitus (WISDM) randomized clinical trial (RCT) participants during an observational extension phase. Research Design and Methods: WISDM RCT was a 26-week RCT comparing continuous glucose monitoring (CGM) with blood glucose monitoring (BGM) in 203 adults aged ≥60 years with type 1 diabetes. Of the 198 participants who completed the RCT, 100 (98%) CGM group participants continued CGM (CGM-CGM cohort) and 94 (98%) BGM group participants initiated CGM (BGM-CGM cohort) for an additional 26 weeks. Results: CGM was used a median of >90% of the time at 52 weeks in both cohorts. In the CGM-CGM cohort, median time <70 mg/dL decreased from 5.0% at baseline to 2.6% at 26 weeks and remained stable with a median of 2.8% at 52 weeks (P < 0.001 baseline to 52 weeks). Participants spent more time in range 70-180 mg/dL (TIR) (mean 56% vs. 64%; P < 0.001) and had lower hemoglobin A1c (HbA1c) (mean 7.6% [59 mmol/mol] vs. 7.4% [57 mmol/mol]; P = 0.01) from baseline to 52 weeks. In BGM-CGM, from 26 to 52 weeks median time <70 mg/dL decreased from 3.9% to 1.9% (P < 0.001), TIR increased from 56% to 60% (P = 0.006) and HbA1c decreased from 7.5% (58 mmol/mol) to 7.3% (57 mmol/mol) (P = 0.025). In BGM-CGM, a severe hypoglycemic event was reported for nine participants while using BGM during the RCT and for two participants during the extension phase with CGM (P = 0.02). Conclusions: CGM use reduced hypoglycemia without increasing hyperglycemia in older adults with type 1 diabetes. These data provide further evidence for fully integrating CGM into clinical practice. Clinicaltrials.gov (NCT03240432).