Closed-Loop Insulin Delivery for Glycemic Control in Noncritical Care

The role of automated insulin delivery technology in diabetes

The role of automated insulin delivery systems in diabetes is expanding. Hybrid closed-loop systems are being used in routine clinical practice for treating people with type 1 diabetes. Encouragingly, real-world data reflects the performance and usability observed in clinical trials. We review the commercially available hybrid closed-loop systems, their distinctive features and the associated real-world data. We also consider emerging indications for closed-loop systems, including the treatment of type 2 diabetes where variability of day-to-day insulin requirements is high, and other challenging applications for this technology. We discuss issues around access and implementation of closed-loop technology, and consider the limitations of present closed-loop systems, as well as innovative approaches that are being evaluated to improve their performance.

The use of technology in type 2 diabetes and prediabetes: a narrative review

The increasing incidence of type 2 diabetes, which represents 90% of diabetes cases globally, is a major public health concern. Improved glucose management reduces the risk of vascular complications and mortality; however, only a small proportion of the type 2 diabetes population have blood glucose levels within the recommended treatment targets. In recent years, diabetes technologies have revolutionised the care of people with type 1 diabetes, and it is becoming increasingly evident that people with type 2 diabetes can also benefit from these advances. In this review, we describe the current knowledge regarding the role of technologies for people living with type 2 diabetes and the evidence supporting their use in clinical practice. We conclude that continuous glucose monitoring systems deliver glycaemic benefits for individuals with type 2 diabetes, whether treated with insulin or non-insulin therapy; further data are required to evaluate the role of these systems in those with prediabetes (defined as impaired glucose tolerance and/or impaired fasting glucose and/or HbA1c levels between 39 mmol/mol [5.7%] and 47 mmol/mol [6.4%]). The use of insulin pumps seems to be safe and effective in people with type 2 diabetes, especially in those with an HbA1c significantly above target. Initial results from studies exploring the impact of closed-loop systems in type 2 diabetes are promising. We discuss directions for future research to fully understand the potential benefits of integrating evidence-based technology into care for people living with type 2 diabetes and prediabetes.

Closed-Loop Insulin Therapy for People With Type 2 Diabetes Treated With an Insulin Pump: A 12-Week Multicenter, Open-Label Randomized, Controlled, Crossover Trial

OBJECTIVE

Continuous glucose monitoring (CGM) combined with continuous subcutaneous insulin infusion (CSII) achieves better glycemic control than multi-injection therapy in people with type 2 diabetes. The effectiveness of closed-loop therapy needs to be further evaluated in this population.

RESEARCH DESIGN AND METHODS

The study objective was to measure the impact of a hybrid closed-loop device (DBLG1) compared with CSII + CGM on glycemic control in people with type 2 diabetes previously treated with CSII. The randomized, controlled, crossover, two-period, open-label, and multicenter study was conducted from August 2022 to July 2023 in 17 individuals (9 to receive 6 weeks of CSII + CGM first and 8 to receive 6 weeks of closed-loop therapy first). The primary end point was the percentage time in range (TIR: 70-180 mg/dL). Secondary outcomes were other CGM-glucose metrics, physical activity, and sleep objectively measured using 1-week actimetry.

RESULTS

Data were analyzed using a modified intention-to-treat approach. Mean age was 63 (SD 9) years and 35% were women. Mean HbA1c at inclusion was 7.9% (SD 0.9). TIR increased to 76.0% (interquartile range 69.0-84.0) during the closed-loop condition vs. 61.0% (interquartile range 55.0-70.0) during the CSII + CGM condition; mean difference was 15.0 percentage points (interquartile range 8.0-22.0; P < 0.001). Analyses of secondary end points showed a decrease in time above range, in glucose management indicator, in glucose variability, and an increase in daily insulin dose. Actimetric sleep analysis showed an improvement in sleep fragmentation during closed-loop treatment.

CONCLUSIONS

Closed-loop therapy improved glycemic control more than did CSII + CGM in people with type 2 diabetes.

Automating insulin delivery through pump and continuous glucose monitoring connectivity: Maximizing opportunities to improve outcomes

The development of automated insulin delivery (AID) systems, which connect continuous glucose monitoring (CGM) systems with algorithmic insulin delivery from an insulin pump (continuous subcutaneous insulin infusion, [CSII]), has led to improved glycaemia and quality of life benefits in those with insulin-treated diabetes. This review summarizes the benefits gained by the connectivity between insulin pumps and CGM devices. It details the technical requirements and advances that have enabled this, and highlights the clinical and user benefits of such systems. Clinical trials and real-world outcomes from the use of AID systems in people with type 1 diabetes (T1D) will be the focus of this article; outcomes in people with type 2 diabetes (T2D) and other diabetes subtypes will also be discussed. We also detail the limitations of current technological approaches for connectivity between insulin pumps and CGM devices. While recognizing the barriers, we discuss opportunities for the future.

A Randomized Clinical Trial for Meal Bolus Decision Using Learning-based Control in Adults With Type 2 Diabetes

CONTEXT

We propose an artificial-pancreas-like algorithm (AP-A) that could automatically determine the preprandial insulin dose based on intermittently scanned continuous glucose monitoring (isCGM) data trajectories in multiple dose injection (MDI) therapy.

OBJECTIVE

We aim to determine whether preprandial insulin dose adjustments guided by the AP-A are as effective and safe as physician decisions.

METHODS

We performed a randomized, single-blind, clinical trial at a tertiary, referral hospital in Beijing, China. Type 2 diabetes participants were eligible if they were aged 18 years or older, with a glycated hemoglobin A1c of 8.0% or higher. Eligible participants were randomly assigned (1:1) to the AP-A arm supervised by physician and the conventional physician treatment arm. The primary objective was to compare percentage time spent with sensor glucose level in 3.9 to 10.0 mmol/L (TIR) between the 2 study arms. Safety was assessed by the percentage time spent with sensor glucose level below 3.0 mmol/L (TBR).

RESULTS

A total of 140 participants were screened, of whom 119 were randomly assigned to the AP-A arm (n = 59) or physician arm (n = 60). The TIR achieved by the AP-A arm was statistically noninferior compared with the control arm (72.4% [63.3%-82.1%] vs 71.2% [54.9%-81.4%]), with a median difference of 1.33% (95% CI, -6.00 to 10.94, noninferiority margin -7.5%). TBR was also statistically noninferior between the AP-A and control arms (0.0% [0.0%-0.0%] vs 0.0% [0.0%-0.0%]), respectively; median difference (95% CI, 0.00% [0.00%-0.00%], noninferiority margin 2.0%).

CONCLUSION

The AP-A-supported physician titration of preprandial insulin dosage offers noninferior glycemic control compared with optimal physician care in type 2 diabetes.

Real-Life Use of Automated Insulin Delivery in Individuals With Type 2 Diabetes

BACKGROUND

The objective of this work is to document performance of automated insulin delivery (AID) during real-life use in type 2 diabetes (T2D).

METHODS

A retrospective analysis was performed of continuous glucose monitoring and insulin delivery data from 796 individuals with T2D, who transitioned from 1-month predictive low-glucose suspend (PLGS) use to 3-month AID use, in real-life settings. Primary outcome was change of time in range (TIR = 70-180 mg/dL) from PLGS to AID. Secondary outcomes included time above/below range (TAR/TBR) and total daily insulin (TDI).

RESULTS

Compared with PLGS, AID increased TIR on average from 63.2% to 72.6%, decreased TAR from 36.2% to 26.8%, and increased TDI from 70.2 to 76.3 U (all P < .001), without significant change to TBR. Glycemic improvements were more pronounced in those with worse glycemic control during PLGS use (P < .001).

CONCLUSIONS

Real-life use of AID led to a rapid and sustained improvement of glycemic control in individuals with T2D.

Case series of using automated insulin delivery to improve glycaemic control in people with type 1 diabetes and end stage kidney disease on haemodialysis

Automated insulin delivery (AID) in people with type 1 diabetes (pwT1D) and end-stage kidney disease (ESKD) on haemodialysis (HD) has not been reported previously. We describe practical considerations and our findings in four pwT1D on HD for ESKD where AID was safely implemented, with significant improvements in time in range.

Patient-clinician collaboration in making care fit: A qualitative analysis of clinical consultations in diabetes care

OBJECTIVE

To confirm described dimensions of making care fit and explore how patients and clinicians collaborate to make care fit in clinical practice.

METHODS

As part of an ongoing study, we audiotaped and transcribed patient-clinician consultations in diabetes care. We purposively selected consultations based on participants' demographical, biomedical and biographical characteristics. We analysed transcripts using reflexive thematic analysis. We combined a deductive and inductive approach, using the pre-described dimensions of making care fit and adding new (sub-)dimensions when pertinent.

RESULTS

We analysed 24 clinical consultations. Our data confirmed eight previously described dimensions and provided new sub-dimensions of making care fit with examples from clinical practice (problematic situation, influence of devices, sense of options, shared agenda setting, clinician context, adapting to changing organization of care, and possibility to reconsider).

CONCLUSION

Our study confirmed, specified and enriched the conceptualization of making care fit through practice examples. We observed patient-clinician collaboration in exploration of patients' context, and by responsively changing, adapting or maintaining care plans.

PRACTICE IMPLICATIONS

Our findings support clinicians and researchers with insights in important aspects of patient-clinician collaboration. Ultimately, this would lead to optimal design of care plans that fit well in each patient life.

Review Article - Diabetes Technology in the Hospital: An Update

PURPOSE OF REVIEW

There have been many developments in diabetes technology in recent years, with continuous glucose monitoring (CGM), insulin pump therapy (CSII) and automated insulin delivery (AID) becoming progressively accepted in outpatient diabetes care. However, the use of such advanced diabetes technology in the inpatient setting is still limited for several reasons, including logistical challenges and staff training needs. On the other hand, hospital settings with altered diet and stress-induced hyperglycemia often pose challenges to tight glycemic control using conventional treatment tools. Integrating smarter glucose monitoring and insulin delivery devices into the increasingly technical hospital environment could reduce diabetes-related morbidity and mortality. This narrative review describes the most recent literature on the use of diabetes technology in the hospital and suggests avenues for further research.

RECENT FINDINGS

Advanced diabetes technology has the potential to improve glycemic control in hospitalized people with and without diabetes, and could add particular value in certain conditions, such as nutrition therapy or perioperative management. Taken together, CGM allows for more accurate and patient-friendly follow-up and ad hoc titration of therapy. AID may also provide benefits, including improved glycemic control and reduced nursing workload. Before advanced diabetes technology can be used on a large scale in the hospital, further research is needed on efficacy, accuracy and safety, while implementation factors such as cost and staff training must also be overcome.

Optogenetic therapeutic strategies for diabetes mellitus

Diabetes mellitus (DM) is a common chronic disease affecting humans globally. It is characterized by abnormally elevated blood glucose levels due to the failure of insulin production or reduction of insulin sensitivity and functionality. Insulin and glucagon-like peptide (GLP)-1 replenishment or improvement of insulin resistance are the two major strategies to treat diabetes. Recently, optogenetics that uses genetically encoded light-sensitive proteins to precisely control cell functions has been regarded as a novel therapeutic strategy for diabetes. Here, we summarize the latest development of optogenetics and its integration with synthetic biology approaches to produce light-responsive cells for insulin/GLP-1 production, amelioration of insulin resistance and neuromodulation of insulin secretion. In addition, we introduce the development of cell encapsulation and delivery methods and smart bioelectronic devices for the in vivo application of optogenetics-based cell therapy in diabetes. The remaining challenges for optogenetics-based cell therapy in the clinical translational study are also discussed.

Does fully closed-loop automated insulin delivery improve glycaemic control in patients with type 2 diabetes? A meta-analysis of randomized controlled trials

AIMS

This meta-analysis investigated the efficacy and safety of fully closed-loop automated insulin delivery (AID) in patients with type 2 diabetes.

MATERIALS AND METHODS

We systemically searched PubMed, Scopus, Web of Science, and Cochrane Central from inception until April 26, 2023. We included randomized controlled trials (RCTs) comparing fully closed-loop AID versus conventional insulin therapy. The outcomes were pooled as the mean difference (MD) and risk ratio with 95% confidence interval (CI) in the random effect model. Our primary outcome was the proportion of time in the target glucose range (5.6-10 mmol/L, 3.9-10 mmol/L, or 3.9-8 mmol/L, depending on the study). Key secondary outcomes included the proportion of time spent in hyperglycaemia or hypoglycaemia.

RESULTS

We included seven RCTs (three crossover and four parallel design), compromising 390 patients. Our analysis showed that compared to the control group, fully closed-loop AID increased the proportion of time spent within the target glucose range by additional 337 min per 24 h (MD = 23.39%, 95% CI [16.64%, 30.14%], p < 0.01), additional 108 min overnight (MD = 22.40%, 95% CI [12.88%, 31.91%], p < 0.01), and additional 258 min during the daytime period (MD = 26.85%, 95% CI [21.06%, 32.63%], p < 0.01). Compared to the control group, the overall time in hyperglycaemia was shortened by 326 min per 24 h (MD = -22.67%, 95% CI [-30.87%, -14.46%], p < 0.01). There was no significant difference between the two groups in terms of overall, overnight, and daytime periods spent in hypoglycaemia.

CONCLUSIONS

Our meta-analysis suggests that fully closed-loop AID may improve glycaemic control in patients with type 2 diabetes, particularly for those with more challenging diabetes management. Further research is required to establish the feasibility of implementing these systems in clinical practice. [Correction added on 26 August 2023 after first online publication: Under Results, the first sentence "We included seven RCTs (three crossover and one parallel designs)" has been changed to "We included seven RCTs (three crossover and four parallel designs)".].

A Consensus Statement for Continuous Glucose Monitoring Metrics for Inpatient Clinical Trials

Diabetes Technology Society organized an expert consensus panel to develop metrics for research in the use of continuous glucose monitors (CGMs) in a hospital setting. The experts met virtually in small groups both before and after an April 13, 2023 virtual meeting of the entire panel. The goal of the panel was to develop consensus definitions in anticipation of greater use of CGMs in hospital settings in the future. Establishment of consensus definitions of inpatient analytical metrics will be easier to compare outcomes between studies. Panelists defined terms related to 10 dimensions of measurements related to the use of CGMs including (1) hospital hypoglycemia, (2) hospital hyperglycemia, (3) hospital time in range, (4) hospital glycemic variability, (5) hospital glycemia risk index, (6) accuracy of CGM devices and reference methods for CGMs in the hospital, (7) meaningful time blocks for hospital glycemic goals, (8) hospital CGM data sufficiency, (9) using CGM data for insulin dosing, and (10) miscellaneous factors. The panelists voted on 51 proposed recommendations. Based on the panel vote, 51 recommendations were classified as either strong (43) or mild (8). Additional research is needed on CGM performance in the hospital. This consensus report is intended to support that type of research intended to improve outcomes for hospitalized people with diabetes.

Fully Closed-Loop Glucose Control Compared With Insulin Pump Therapy With Continuous Glucose Monitoring in Adults With Type 1 Diabetes and Suboptimal Glycemic Control: A Single-Center, Randomized, Crossover Study

OBJECTIVE

We evaluated the safety and efficacy of fully closed-loop with ultrarapid insulin lispro in adults with type 1 diabetes and suboptimal glycemic control compared with insulin pump therapy with continuous glucose monitoring (CGM).

RESEARCH DESIGN AND METHODS

This single-center, randomized, crossover study enrolled 26 adults with type 1 diabetes using insulin pump therapy with suboptimal glycemic control (mean ± SD, age 41 ± 12 years, HbA1c 9.2 ± 1.1% [77 ± 12 mmol/mol]). Participants underwent two 8-week periods of unrestricted living to compare fully closed-loop with ultrarapid insulin lispro (CamAPS HX system) with insulin pump therapy with CGM in random order.

RESULTS

In an intention-to-treat analysis, the proportion of time glucose was in range (primary end point 3.9-10.0 mmol/L) was higher during closed-loop than during pump with CGM (mean ± SD 50.0 ± 9.6% vs. 36.2 ± 12.2%, mean difference 13.2 percentage points [95% CI 9.5, 16.9], P < 0.001). Time with glucose >10.0 mmol/L and mean glucose were lower during closed-loop than during pump with CGM (mean ± SD time >10.0 mmol/L: 49.0 ± 9.9 vs. 62.9 ± 12.6%, mean difference -13.3 percentage points [95% CI -17.2, -9.5], P < 0.001; mean ± SD glucose 10.7 ± 1.1 vs. 12.0 ± 1.6 mmol/L, mean difference -1.2 mmol/L [95% CI -1.8, -0.7], P < 0.001). The proportion of time with glucose <3.9 mmol/L was similar between periods (median [interquartile range (IQR)] closed-loop 0.88% [0.51-1.55] vs. pump with CGM 0.64% [0.28-1.10], P = 0.102). Total daily insulin requirements did not differ (median [IQR] closed-loop 51.9 units/day [35.7-91.2] vs. pump with CGM 50.7 units/day [34.0-70.0], P = 0.704). No severe hypoglycemia or ketoacidosis occurred.

CONCLUSIONS

Fully closed-loop insulin delivery with CamAPS HX improved glucose control compared with insulin pump therapy with CGM in adults with type 1 diabetes and suboptimal glycemic control.

Key indices of glycaemic variability for application in diabetes clinical practice

Near normal glycaemic control in diabetes consists to target daily glucose fluctuations and quarterly HbA1c oscillations in addition to overall glucose exposure. Consequently, the prerequisite is to define simple, and mathematically undisputable key metrics for the short- and long-term variability in glucose homeostasis. As the standard deviations (SD) of either glucose or HbA1c are dependent on their means, the coefficient of variation (CV = SD/mean) should be applied instead as it that avoids the correlation between the SD and mean values. A CV glucose of 36% is the most appropriate threshold between those with stable versus labile glucose homeostasis. However, when near normal mean glucose concentrations are achieved a lower CV threshold of <27 % is necessary for reducing the risk for hypoglycaemia to a minimal rate. For the long-term variability in glucose homeostasis, a CVHbA1c < 5 % seems to be a relevant recommendation for preventing adverse clinical outcomes.

Glycemic control metrics in a cohort of hospitalized patients with type 1 diabetes using hybrid closed-loop and advanced hybrid closed-loop systems

AIMS

To describe Hybrid closed-loop (HCL) and advanced hybrid closed-loop (AHCL) performance in the hospital setting based on the continuous glucose monitoring (CGM) metrics description.

METHODS

This was an observational study from a cohort of patients with T1D using HCL/AHCL with history of hospitalization. CGM metrics were analyzed during the hospital stay. CGM metrics sub-analysis of the population with active Automated Mode (AM) and SmartGuard (SG) during hospitalization and/or surgical procedure was performed.

RESULTS

Twenty-four patients were included (50 % women; mean age, 49 years [inter-quartile range (IQR), 39-62 years]). During hospitalization 70.8 % patients achieved %Time in Range (TIR) between 70 and 180 mg/dL ≥ 70 %. The overall %TIR was 75.5 % (IQR, 67.3-81.5 %), % time below range (TBR) < 70 mg/dL was 2.1 % (IQR, 0.7-5.4 %) and %TBR < 54 mg/dL was 0 % (IQR, 0-5.4 %). Users of the AHCL with active SG achieved a non-significant higher %TIR during hospitalization (79 % [73.8.88 %] vs. 76 % [72.81 %], p = 0.312) and had a shorter stay (3[IQR, 2.4] vs. 6 days[IQR, 5.7], p = 0.045) compared to the users of the HCL with AM active. No device-related serious adverse events occurred for users of either system.

CONCLUSIONS

HCL/AHCL systems with active AM/SG in patients with T1D in the hospital environment leads to %TIR > 70 % in ranges of 70-180 mg/dL in patients without increasing hypoglycemia.

Automated Insulin Delivery with Remote Real-Time Continuous Glucose Monitoring for Hospitalized Patients with Diabetes: A Multicenter, Single-Arm, Feasibility Trial

Introduction: Multiple daily injection insulin therapy frequently fails to meet hospital glycemic goals and is prone to hypoglycemia. Automated insulin delivery (AID) with remote glucose monitoring offers a solution to these shortcomings. Research Design and Methods: In a single-arm multicenter pilot trial, we tested the feasibility, safety, and effectiveness of the Omnipod 5 AID System with real-time continuous glucose monitoring (CGM) for up to 10 days in hospitalized patients with insulin-requiring diabetes on nonintensive care unit medical-surgical units. Primary endpoints included the proportion of time in automated mode and percent time-in-range (TIR 70-180 mg/dL) among participants with >48 h of CGM data. Safety endpoints included incidence of severe hypoglycemia and diabetes-related ketoacidosis (DKA). Additional glycemic endpoints, CGM accuracy, and patient satisfaction were also explored. Results: Twenty-two participants were enrolled; 18 used the system for a total of 96 days (mean 5.3 ± 3.1 days per patient), and 16 had sufficient CGM data required for analysis. Median percent time in automated mode was 95% (interquartile range 92%-98%) for the 18 system users, and the 16 participants with >48 h of CGM data achieved an overall TIR of 68% ± 16%, with 0.17% ± 0.3% time <70 mg/dL and 0.06% ± 0.2% time <54 mg/dL. Sensor mean glucose was 167 ± 21 mg/dL. There were no DKA or severe hypoglycemic events. All participants reported satisfaction with the system at study end. Conclusions: The use of AID with a disposable tubeless patch-pump along with remote real-time CGM is feasible in the hospital setting. These results warrant further investigation in randomized trials.

Time requirements for perioperative glucose management using fully closed-loop versus standard insulin therapy: A proof-of-concept time-motion study

AIMS

To compare the time required for perioperative glucose management using fully automated closed-loop versus standard insulin therapy.

METHODS

We performed a time-motion study to quantify the time requirements for perioperative glucose management with fully closed-loop (FCL) and standard insulin therapy applied to theoretical scenarios. Following an analysis of workflows in different periods of perioperative care in elective surgery patients receiving FCL or standard insulin therapy upon hospital admission (pre- and intra-operatively, at the intermediate care unit and general wards), the time of process-specific tasks was measured by shadowing hospital staff. Each task was measured 20 times and its average duration in combination with its frequency according to guidelines was used to calculate the cumulative staff time required for blood glucose management. Cumulative time was calculated for theoretical scenarios consisting of elective minor and major abdominal surgeries (pancreatic surgery and sleeve gastrectomy, respectively) to account for the different care settings and lengths of stay.

RESULTS

The FCL insulin therapy reduced the time required for perioperative glucose management compared to standard insulin therapy, across all assessed care periods and for both perioperative pathways (range 2.1-4.5). For a major abdominal surgery, total time required was 248.5 min using FCL versus 753.9 min using standard insulin therapy. For a minor abdominal surgery, total time required was 68.6 min and 133.2 min for FCL and standard insulin therapy, respectively.

CONCLUSIONS

The use of fully automated closed-loop insulin delivery for inpatient glucose management has the potential to alleviate the workload of diabetes management in an environment with adequately trained staff.

Assessment of US Food and Drug Administration-Approved Digital Medical Devices for Just-in-Time Interventions: A Systematic Review

Importance

Just-in-time interventions (JITIs) are a type of digital therapeutic intervention that combines remote monitoring tools and algorithms to personalize the delivery of specific interventions at the right time. The US Food and Drug Administration (FDA) regulatory approval documents are often the only available source of information on the effectiveness of therapeutic interventions based on these devices.

Objective

To systematically review the publicly available information from the FDA on all recently approved medical devices used in JITIs to (1) assess how they operate to deliver JITIs and (2) appraise the evidence supporting their performance and clinical effectiveness.

Evidence Review

Two reviewers systematically searched the Premarket Notifications (510(k)), Premarket Approvals, De Novo, and Humanitarian Device Exemption databases from January 2019 to December 2021 for all entries associated with devices that monitored patients' data over time to personalize the delivery of interventions to treat, prevent, or mitigate health conditions or events. They assessed whether the product summaries (1) enabled an understanding of how the device operated to deliver a JITI (eg, the nature, type, and frequency of the monitoring, the nature of the decision algorithm, and the nature and intended receiver of the intervention); (2) informed about the performance and effectiveness of the JITI; and (3) included information on data security and ownership.

Findings

In total, 38 devices were included in this review. These were mainly intended for cardiac conditions (12 [31.6%]), diabetes (10 [26.3%]), and neurological diseases (4 [10.5%]). Monitoring devices ranged from wearable (18 of 28 [64.4%]; eg, smartwatches) to implanted sensors (6 of 28 [21.4%]; eg, inserted electrocardiographic sensors). Only 10 of 38 product summaries (26.3%) allowed a full understanding of how the device operated to deliver a JITI. Similarly, only 12 of 28 (42.9%), 12 of 36 (33.3%), and 5 of 38 (13.2%) reported the assessment of the performance of the monitoring device, assessment of the decision algorithm, and results of clinical studies assessing the effectiveness of the JITI, respectively. Finally, 14 of 36 product summaries (38.9%) included some information on data security, but none included information on data ownership.

Conclusion and Relevance

The results of this systematic review suggest that the information publicly available in the FDA databases on the performance and effectiveness of digital medical devices used in JITIs is heterogeneous.

Implementation of fully closed-loop insulin delivery for inpatients with diabetes: Real-world outcomes

AIMS

Fully closed-loop insulin delivery has been shown in clinical trials to be safe and improve glucose control compared with standard insulin therapy in the inpatient setting. We investigated the feasibility of implementing the approved CamAPS HX fully closed-loop system in a hospital setting.

METHODS

This implementation project was conducted in a large teaching hospital in Cambridge, UK. Healthcare professional training was multimodal including face-to-face workshops, online learning modules and supported by standard operating procedures. Set-up and maintenance of closed-loop devices were undertaken by the inpatient diabetes team. Selection of suitable patients was multidisciplinary and prioritised those with more challenging diabetes management. Demographic and clinical data were collected from electronic health records and diabetes data management platforms.

RESULTS

In the 12 months since the closed-loop system was implemented, 32 inpatients (mean ± SD age 61 ± 16 years, 8 females, 24 males) used closed-loop insulin delivery during their admission, across medical and surgical wards in the hospital with a total of 555 days of closed-loop glucose control (median [IQR]: 14 [6, 22] days per inpatient). The time spent in target glucose range 3.9-10.0 mmol/L was 53.3 ± 18.3%. Mean glucose was 10.7 ± 1.9 mmol/L with 46.0 ± 18.2% of time spent with glucose >10.0 mmol/L. Time spent with sensor glucose below 3.9 mmol/L was low (median [IQR]: 0.38 [0.00, 0.85]). There were no episodes of severe hypoglycaemia or diabetic ketoacidosis during closed-loop use.

CONCLUSIONS

We have demonstrated that the fully closed-loop system can be safely and effectively implemented by a diabetes outreach team in complex medical and surgical inpatients with challenging glycaemic control.

Automated Insulin Delivery (AID) Systems: Use and Efficacy in Children and Adults with Type 1 Diabetes and Other Forms of Diabetes in Europe in Early 2023

Type 1 diabetes (T1D) patients' lifestyle and prognosis has remarkably changed over the years, especially after the introduction of insulin pumps, in particular advanced hybrid closed loop systems (AHCL). Emerging data in literature continuously confirm the improvement of glycemic control thanks to the technological evolution taking place in this disease. As stated in previous literature, T1D patients are seen to be more satisfied thanks to the use of these devices that ameliorate not only their health but their daily life routine as well. Limited findings regarding the use of new devices in different age groups and types of patients is their major limit. This review aims to highlight the main characteristics of each Automated Insulin Delivery (AID) system available for patients affected by Type 1 Diabetes Mellitus. Our main goal was to particularly focus on these systems' efficacy and use in different age groups and populations (i.e., children, pregnant women). Recent studies are emerging that demonstrate their efficacy and safety in younger patients and other forms of diabetes.

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.

Automated Insulin Delivery Systems as a Treatment for Type 2 Diabetes Mellitus: A Review

OBJECTIVE

Approximately 6.3% of the worldwide population has type 2 diabetes mellitus (T2DM), and the number of people requiring insulin is increasing. Automated insulin delivery (AID) systems integrate continuous subcutaneous insulin infusion and continuous glucose monitoring with a predictive control algorithm to provide more physiologic glycemic control. Personalized glycemic targets are recommended in T2DM owing to the heterogeneity of the disease. Based on the success of hybrid closed-loop systems in improving glycemic control and safety in type 1 diabetes mellitus, there has been further interest in the use of these systems in people with T2DM.

METHODS

We performed a review of AID systems with a focus on the T2DM population.

RESULTS

In 5 randomized controlled trials, AID systems improve time in range and reduce glycemic variability, without increasing insulin requirements or the risk of hypoglycemia.

CONCLUSION

AID systems in T2DM are safe and effective in hospitalized and closely monitored settings. Home studies of longer duration are required to assess for long-term benefit and identify target populations of benefit.

Glycaemic control in critical care: Can flash glucose monitoring help?

Good glycaemic control confers an outcome benefit in both diabetic and non-diabetic critically unwell patients. Critically unwell patients receiving intravenous insulin in the intensive care unit (ICU) require hourly glucose monitoring. This brief communication highlights the impact of the introduction of the FreeStyle Libre glucose monitor, a form of continuous glucose monitoring, on the frequency of glucose recordings in patients receiving intravenous insulin in the ICU at York Teaching Hospital NHS Foundation Trust.

[Hospital diabetes management (Update 2023)]

This position statement presents the recommendations of the Austrian Diabetes Association for diabetes management of adult patients during inpatient stay. It is based on the current evidence with respect to blood glucose targets, insulin therapy and treatment with oral/injectable antidiabetic drugs during inpatient hospitalization. Additionally, special circumstances such as intravenous insulin therapy, concomitant therapy with glucocorticoids and use of diabetes technology during hospitalization are discussed.

Fully automated closed-loop insulin delivery in adults with type 2 diabetes: an open-label, single-center, randomized crossover trial

In adults with type 2 diabetes, the benefits of fully closed-loop insulin delivery, which does not require meal bolusing, are unclear. In an open-label, single-center, randomized crossover study, 26 adults with type 2 diabetes (7 women and 19 men; (mean ± s.d.) age, 59 ± 11 years; baseline glycated hemoglobin (HbA1c), 75 ± 15 mmol mol^-1 (9.0% ± 1.4%)) underwent two 8-week periods to compare the CamAPS HX fully closed-loop app with standard insulin therapy and a masked glucose sensor (control) in random order, with a 2-week to 4-week washout between periods. The primary endpoint was proportion of time in target glucose range (3.9-10.0 mmol l^-1). Analysis was by intention to treat. Thirty participants were recruited between 16 December 2020 and 24 November 2021, of whom 28 were randomized to two groups (14 to closed-loop therapy first and 14 to control therapy first). Proportion of time in target glucose range (mean ± s.d.) was 66.3% ± 14.9% with closed-loop therapy versus 32.3% ± 24.7% with control therapy (mean difference, 35.3 percentage points; 95% confidence interval (CI), 28.0-42.6 percentage points; P < 0.001). Time > 10.0 mmol l^-1 was 33.2% ± 14.8% with closed-loop therapy versus 67.0% ± 25.2% with control therapy (mean difference, -35.2 percentage points; 95% CI, -42.8 to -27.5 percentage points; P < 0.001). Mean glucose was lower during the closed-loop therapy period than during the control therapy period (9.2 ± 1.2 mmol l^-1 versus 12.6 ± 3.0 mmol l^-1, respectively; mean difference, -3.6 mmol l^-1; 95% CI, -4.6 to -2.5 mmol l^-1; P < 0.001). HbA1c was lower following closed-loop therapy (57 ± 9 mmol mol^-1 (7.3% ± 0.8%)) than following control therapy (72 ± 13 mmol mol^-1 (8.7% ± 1.2%); mean difference, -15 mmol mol^-1; 95% CI, -11 to -20 mmol l^-1 (mean difference, -1.4%; 95% CI, -1.0 to -1.8%); P < 0.001). Time < 3.9 mmol l^-1 was similar between treatments (a median of 0.44% (interquartile range, 0.19-0.81%) during the closed-loop therapy period versus a median of 0.08% (interquartile range, 0.00-1.05%) during the control therapy period; P = 0.43). No severe hypoglycemia events occurred in either period. One treatment-related serious adverse event occurred during the closed-loop therapy period. Fully closed-loop insulin delivery improved glucose control without increasing hypoglycemia compared with standard insulin therapy and may represent a safe and efficacious method to improve outcomes in adults with type 2 diabetes. This study is registered with ClinicalTrials.gov (NCT04701424).

[Position statement: surgery and diabetes mellitus (Update 2023)]

This position statement reflects the perspective of the Austrian Diabetes Association concerning the perioperative management of people with diabetes mellitus based on the available scientific evidence. The paper covers necessary preoperative examinations from an internal/diabetological point of view as well as the perioperative metabolic control by means of oral antihyperglycemic and/or insulin therapy.

Insulin Pumps and Hybrid Close Loop Systems Within Hospital: A Scoping Review and Practical Guidance From the Joint British Diabetes Societies for Inpatient Care

This article is the second of a two-part series providing a scoping review and summary of the Joint British Diabetes Societies for Inpatient Care (JBDS-IP) guidelines on the use of diabetes technology in people with diabetes admitted to hospital. The first part reviewed the use of continuous glucose monitoring (CGM) in hospital. In this article, we focus on the use of continuous subcutaneous insulin infusion (CSII; insulin pumps) and hybrid closed-loop systems in hospital. JBDS-IP advocates enabling people who can self-manage and are willing and capable of using CSII to continue doing so as they would do out of hospital. CSII should be discontinued if the individual is critically ill or hemodynamically unstable. For individuals on hybrid closed-loop systems, the system should be discontinued from auto-mode, and may be used individually (as CGM only or CSII only, if criteria are met). Continuing in closed-loop mode may only be done so under specialist guidance from the Diabetes Team, where the diabetes teams are comfortable and knowledgeable about the specific devices used. Health care organizations need to have clear local policies and guidance to support individuals using these wearable technologies, and ensure the relevant workforce is capable and skilled enough to ensure their safe use within the hospital setting.

Perioperative Fully Closed-Loop Insulin Delivery in Patients Undergoing Elective Surgery: An Open-Label, Randomized Controlled Trial

OBJECTIVE

Perioperative management of glucose levels remains challenging. We aimed to assess whether fully closed-loop subcutaneous insulin delivery would improve glycemic control compared with standard insulin therapy in insulin-requiring patients undergoing elective surgery.

RESEARCH DESIGN AND METHODS

We performed a single-center, open-label, randomized controlled trial. Patients with diabetes (other than type 1) undergoing elective surgery were recruited from various surgical units and randomly assigned using a minimization schedule (stratified by HbA1c and daily insulin dose) to fully closed-loop insulin delivery with fast-acting insulin aspart (closed-loop group) or standard insulin therapy according to local clinical practice (control group). Study treatment was administered from hospital admission to discharge (for a maximum of 20 days). The primary end point was the proportion of time with sensor glucose in the target range (5.6-10.0 mmol/L).

RESULTS

Forty-five patients were enrolled and assigned to the closed-loop (n = 23) or the control (n = 22) group. One patient (closed-loop group) withdrew from the study before surgery and was not analyzed. Participants underwent abdominal (57%), vascular (23%), orthopedic (9%), neuro (9%), or thoracic (2%) surgery. The mean proportion of time that sensor glucose was in the target range was 76.7 ± 10.1% in the closed-loop and 54.7 ± 20.8% in the control group (mean difference 22.0 percentage points [95% CI 11.9; 32.0%]; P < 0.001). No episodes of severe hypoglycemia (<3.0 mmol/L) or hyperglycemia with ketonemia or any study-related adverse events occurred in either group.

CONCLUSIONS

In the context of mixed elective surgery, the use of fully closed-loop subcutaneous insulin delivery improves glucose control without a higher risk of hypoglycemia.

A Systematic Review Supporting the Endocrine Society Clinical Practice Guideline for the Management of Hyperglycemia in Adults Hospitalized for Noncritical Illness or Undergoing Elective Surgical Procedures

CONTEXT

Individuals with diabetes or newly recognized hyperglycemia account for over 30% of noncritically ill hospitalized patients. Management of hyperglycemia in these patients is challenging.

OBJECTIVE

To support development of the Endocrine Society Clinical Practice Guideline for management of hyperglycemia in adults hospitalized for noncritical illness or undergoing elective surgical procedures.

METHODS

We searched several databases for studies addressing 10 questions provided by a guideline panel from the Endocrine Society. Meta-analysis was conducted when feasible. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess certainty of evidence.

RESULTS

We included 94 studies reporting on 135 553 patients. Compared with capillary blood glucose, continuous glucose monitoring increased the number of patients identified with hypoglycemia and decreased mean daily blood glucose (BG) (very low certainty). Data on continuation of insulin pump therapy in hospitalized adults were sparse. In hospitalized patients receiving glucocorticoids, combination neutral protamine hagedorn (NPH) and basal-bolus insulin was associated with lower mean BG compared to basal-bolus insulin alone (very low certainty). Data on NPH insulin vs basal-bolus insulin in hospitalized adults receiving enteral nutrition were inconclusive. Inpatient diabetes education was associated with lower HbA1c at 3 and 6 months after discharge (moderate certainty) and reduced hospital readmissions (very low certainty). Preoperative HbA1c level < 7% was associated with shorter length of stay, lower postoperative BG and a lower number of neurological complications and infections, but a higher number of reoperations (very low certainty). Treatment with glucagon-like peptide-1 agonists or dipeptidyl peptidase-4 inhibitors in hospitalized patients with type 2 diabetes and mild hyperglycemia was associated with lower frequency of hypoglycemic events than insulin therapy (low certainty). Caloric oral fluids before surgery in adults with diabetes undergoing surgical procedures did not affect outcomes (very low certainty). Counting carbohydrates for prandial insulin dosing did not affect outcomes (very low certainty). Compared with scheduled insulin (basal-bolus or basal insulin + correctional insulin), correctional insulin was associated with higher mean daily BG and fewer hypoglycemic events (low certainty).

CONCLUSION

The certainty of evidence supporting many hyperglycemia management decisions is low, emphasizing importance of shared decision-making and consideration of other decisional factors.

Closed-Loop Artificial Pancreas Therapy for Type 1 Diabetes

PURPOSE OF REVIEW

Closed-loop insulin pump systems (artificial pancreas) represent the cutting edge of insulin delivery technology. There are only a few systems currently approved for use in the USA: the MiniMed 670G/770G (which share an algorithm), t:slim X2 Control IQ, and the Omnipod 5. We review these systems and look into the future of the technology.

RECENT FINDINGS

All of the approved closed-loop insulin pump systems have demonstrated in multicenter prospective trials improvements in time in range, hemoglobin A1c, and time spent in hypoglycemia. The newer systems have also improved time spent in automation. Comparisons between the systems with regard to glycemic control are difficult to make due to differences in clinical trial design, but there are notable differences in the user experience between systems. The past few years have been a time of exponential development in the field of closed-loop insulin pump systems. However, more research is needed to provide full automation of these systems without any need for information from the user.

The Need for Diabetes Advance Directives to Support the Care of People With Diabetes

It is time to adopt an advance directive specific to diabetes management. Research shows that people with diabetes in the hospital are often removed from existing diabetes self-management, resulting in poorer outcomes. Diabetes advance directives, which outline preferred diabetes self-management in scenarios such as hospitalization or outpatient procedures, are key for enabling patients with diabetes to continue successful diabetes management including use of existing diabetes technology. A diabetes advance directive is a new concept for both patients and providers that can improve clinical outcomes and patient-reported outcomes. Given the risk of harm in the absence of such a document, diabetes advance directives can be a useful new tool for patients and providers and to aid in the discussion, care planning, and self-management with diabetes technology.

Closed-Loop Insulin Delivery Systems: Past, Present, and Future Directions

Closed-loop (artificial pancreas) systems for automated insulin delivery have been likened to the holy grail of diabetes management. The first iterations of glucose-responsive insulin delivery were pioneered in the 1960s and 1970s, with the development of systems that used venous glucose measurements to dictate intravenous infusions of insulin and dextrose in order to maintain normoglycemia. Only recently have these bulky, bedside technologies progressed to miniaturized, wearable devices. These modern closed-loop systems use interstitial glucose sensing, subcutaneous insulin pumps, and increasingly sophisticated algorithms. As the number of commercially available hybrid closed-loop systems has grown, so too has the evidence supporting their efficacy. Future challenges in closed-loop technology include the development of fully closed-loop systems that do not require user input for meal announcements or carbohydrate counting. Another evolving avenue in research is the addition of glucagon to mitigate the risk of hypoglycemia and allow more aggressive insulin dosing.

Hypoglycemia in diabetes: An update on pathophysiology, treatment, and prevention

Hypoglycemia is a common complication in patients with diabetes, mainly in those treated with insulin, sulfonylurea, or glinide. Impairments in counterregulatory responses and hypoglycemia unawareness constitute the main risk factors for severe hypoglycemia. Episodes of hypoglycemia are associated with physical and psychological morbidity. The fear of hypoglycemia constitutes a barrier that impairs the patient's ability to reach good glycemic control. To prevent hypoglycemia, much effort must be invested in patient education regarding risk factors, warning signs, and treatment of hypoglycemia at an early stage, together with setting personalized goals for glycemic control. In this review, we present a comprehensive update on the treatment and prevention of hypoglycemia in type 1 and type 2 diabetic patients.

Empfehlungen zur Diabetes-Behandlung mit automatischen Insulin-Dosierungssystemen

Das Prinzip der automatischen Insulindosierung, kurz „AID“ genannt, zeigt in Zulassungsstudien und Real-World-Erfahrungen ausgezeichnete Behandlungsergebnisse. Beim AID wird eine Insulinpumpe mit einem System zur kontinuierlichen Glukosemessung zusammengeschaltet, während ein Rechenprogramm, der sogenannte Algorithmus, die Steuerung der Insulingabe nach Bedarf übernimmt. Idealerweise wäre das System ein geschlossener Kreis, bei dem die Menschen mit Diabetes keine Eingabe mehr machen müssten. Jedoch sind bei den heute verfügbaren Systemen verschiedene Grundeinstellungen und Eingaben erforderlich (insbesondere von Kohlenhydratmengen der Mahlzeiten oder körperlicher Aktivität), die sich von den bisherigen Empfehlungen der sensorunterstützten Pumpentherapie in einzelnen Aspekten unterscheiden. So werden die traditionellen Konzepte von „Basal“ und „Bolus“ mit AID weniger nützlich, da der Algorithmus beide Arten der Insulinabgabe verwendet, um die Glukosewerte dem eingestellten Zielwert zu nähern. Daher sollte bei diesen Systemen statt der Erfassung von „Basal“ und „Bolus“, zwischen einer „nutzerinitiierten“ und einer „automatischen“ Insulindosis unterschieden werden. Gemeinsame Therapieprinzipien der verschiedenen AID-Systeme umfassen die passgenaue Einstellung des Kohlenhydratverhältnisses, die Bedeutung des Timings der vom Anwender initiierten Insulinbolusgaben vor der Mahlzeit, den korrekten Umgang mit einem verzögerten oder versäumten Mahlzeitenbolus, neue Prinzipien im Umgang mit Sport oder Alkoholgenuss sowie den rechtzeitigen Umstieg von AID zu manuellem Modus bei Auftreten erhöhter Ketonwerte. Das Team vom Diabetes-Zentrum AUF DER BULT in Hannover hat aus eigenen Studienerfahrungen und der zugrunde liegenden internationalen Literatur praktische Empfehlungen zur Anwendung und Schulung der gegenwärtig und demnächst in Deutschland kommerziell erhältlichen Systeme zusammengestellt. Für den Erfolg der AID-Behandlung scheint das richtige Erwartungsmanagement sowohl beim Behandlungsteam und als auch beim Anwender von großer Bedeutung zu sein.

Low glycaemic state increases risk of frailty and functional decline in older people with type 2 diabetes mellitus - Evidence from a systematic review

AIMS

To explore risk of frailty and functional decline associated with low glycaemia in older people with type 2 diabetes.

METHODS

Systematic review.

RESULTS

11 studies included. Six studies investigated risk of frailty or physical decline with hypoglycaemia. Hypoglycaemia increased risk of incident frailty (HR 1.60, 95% CI 1.14 to 2.42) in one study and risk of fractures in four studies (2.24, 1.56 to 3.21, 1.24, 1.13 to 1.37, 1.94, 1.67 to 2.24 and 1.71, 1.35 to 2.16 respectively). In sixth study, hypoglycaemia associated with dependency (P < 0.001). Five studies explored association of low blood glucose/HbA1c with frailty. One study showed that mean blood glucose decreased with increasing frailty (p = 0.003). Two studies reported that HbA1c inversely correlated with clinical frailty scale (r = -0.31, p < 0.01) and HbA1c < 6.9% increased risk of frailty (HR, 1.41 95% CI 1.12 to 1.78) respectively. Last two studies showed that HbA1c < 6.5% associated with risk of any fracture (HR 1.08, 95% CI 1.06 to 1.11) and HbA1c < 6.0% associated with increased risk of care need (3.45, 1.02 to 11.6) respectively.

CONCLUSIONS

Low glycaemia increases risk of frailty and functional decline in older people with type 2 diabetes. Management should minimise incidence of low glycaemia in these patients.

Optimizing the use of technology to support people with diabetes: research recommendations from Diabetes UK's 2019 diabetes and technology workshop

AIMS

To identify key gaps in the research evidence base that could help improve how technology supports people with diabetes, and provide recommendations to researchers and research funders on how best to address them.

METHODS

A research workshop was conducted, bringing together research experts in diabetes, research experts in technology, people living with diabetes and healthcare professionals.

RESULTS

The following key areas within this field were identified, and research recommendations for each were developed: Matching the pace of research with that of technology development Time in range as a measure Health inequalities and high-risk groups How to train people to use technology most effectively Impact of technology usage on mental health CONCLUSIONS: This position statement outlines recommendations through which research could improve how technology is employed to care for and support people living with diabetes, and calls on the research community and funders to address them in future research programmes and strategies.

Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence

Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.

Glycaemic variabilities: Key questions in pursuit of clarity

After years of intensive investigation, the definition of glycaemic variability remains unclear and the term variability in glucose homoeostasis might be more appropriate covering both short and long-term glycaemic variability. For the latter, we remain in the search of an accurate definition and related targets. Recent work leads us to consider that the within-subject variability of HbA1c calculated from consecutive determinations of HbA1c at regular time-intervals could be the most relevant index for assessing the long-term variability with a threshold value of 5% (%CV = SD of HbA1c/mean HbA1c) to separate stability from lability of HbA1c. Presently, no one can deny that short- and long-term glucose variability should be maintained within their lower ranges to limit the incidence of hypoglycaemia. Usually, therapeutic strategies aimed at reducing post-meal glucose excursions, i.e. the major contributor to daily glucose fluctuations, exert a beneficial effect on the short-term glucose variability. This explains the effectiveness of adjunct therapies with either GLP- receptor agonists or SGLT inhibitors in type 2 diabetes. In type 1 diabetes, the application of a CGM device alone reduces the short-term glycaemic variability. In contrast, sophisticated insulin delivery does not necessarily lead to such reductions despite marked downward shifts of 24-hour glycaemic profiles. Such contrasting observations raise the question as to whether the prolonged wear of CGM devices is or not the major causative factor for improvement in glucose variability among intensively insulin-treated persons with type 1 diabetes.

Patient and general public attitudes towards clinical artificial intelligence: a mixed methods systematic review

Artificial intelligence (AI) promises to change health care, with some studies showing proof of concept of a provider-level performance in various medical specialties. However, there are many barriers to implementing AI, including patient acceptance and understanding of AI. Patients' attitudes toward AI are not well understood. We systematically reviewed the literature on patient and general public attitudes toward clinical AI (either hypothetical or realised), including quantitative, qualitative, and mixed methods original research articles. We searched biomedical and computational databases from Jan 1, 2000, to Sept 28, 2020, and screened 2590 articles, 23 of which met our inclusion criteria. Studies were heterogeneous regarding the study population, study design, and the field and type of AI under study. Six (26%) studies assessed currently available or soon-to-be available AI tools, whereas 17 (74%) assessed hypothetical or broadly defined AI. The quality of the methods of these studies was mixed, with a frequent issue of selection bias. Overall, patients and the general public conveyed positive attitudes toward AI but had many reservations and preferred human supervision. We summarise our findings in six themes: AI concept, AI acceptability, AI relationship with humans, AI development and implementation, AI strengths and benefits, and AI weaknesses and risks. We suggest guidance for future studies, with the goal of supporting the safe, equitable, and patient-centred implementation of clinical AI.

Fully automated closed-loop glucose control compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis: an open-label, randomized crossover trial

We evaluated the safety and efficacy of fully closed-loop insulin therapy compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis. In an open-label, multinational, two-center, randomized crossover trial, 26 adults with type 2 diabetes requiring dialysis (17 men, 9 women, average age 68 ± 11 years (mean ± s.d.), diabetes duration of 20 ± 10 years) underwent two 20-day periods of unrestricted living, comparing the Cambridge fully closed-loop system using faster insulin aspart (‘closed-loop’) with standard insulin therapy and a masked continuous glucose monitor (‘control’) in random order. The primary endpoint was time in target glucose range (5.6–10.0 mmol l⁻¹). Thirteen participants received closed-loop first and thirteen received control therapy first. The proportion of time in target glucose range (5.6–10.0 mmol l⁻¹; primary endpoint) was 52.8 ± 12.5% with closed-loop versus 37.7 ± 20.5% with control; mean difference, 15.1 percentage points (95% CI 8.0–22.2; P < 0.001). Mean glucose was lower with closed-loop than control (10.1 ± 1.3 versus 11.6 ± 2.8 mmol l⁻¹; P = 0.003). Time in hypoglycemia (<3.9 mmol l⁻¹) was reduced with closed-loop versus control (median (IQR) 0.1 (0.0–0.4%) versus 0.2 (0.0–0.9%); P = 0.040). No severe hypoglycemia events occurred during the control period, whereas one severe hypoglycemic event occurred during the closed-loop period, but not during closed-loop operation. Fully closed-loop improved glucose control and reduced hypoglycemia compared with standard insulin therapy in adult outpatients with type 2 diabetes requiring dialysis. The trial registration number is NCT04025775.

A new randomized, crossover clinical trial testing rapid-acting insulin aspart delivered in a closed-loop system compared with standard care demonstrates increased time in range in patients with type 2 diabetes who require dialysis in the outpatient setting.

Day-to-day variability of insulin requirements in the inpatient setting: Observations during fully closed-loop insulin delivery

The aim of this study was to characterize the variability of exogenous insulin requirements during fully closed-loop insulin delivery in hospitalized patients with type 2 diabetes or new-onset hyperglycaemia, and to determine patient-related characteristics associated with higher variability of insulin requirements. We retrospectively analysed data from two fully closed-loop inpatient studies involving adults with type 2 diabetes or new-onset hyperglycaemia requiring insulin therapy. The coefficient of variation quantified day-to-day variability of exogenous insulin requirements during up to 15 days using fully automated closed-loop insulin delivery. Data from 535 days in 67 participants were analysed. The coefficient of variation of day-to-day exogenous insulin requirements was 30% ± 16%, and was higher between nights than between any daytime period (56% ± 29% overnight [11:00 pm to 4:59 am] compared with 41% ± 21% in the morning [5:00 am to 10:59 am], 39% ± 15% in the afternoon [11:00 am to 4:59 pm] and 45% ± 19% during the evening [5:00 pm to 10:59 pm]; all P < 0.01). There is high day-to-day variability of exogenous insulin requirements in inpatients, particularly overnight, and diabetes management approaches should account for this variability.

Technology in the management of type 2 diabetes: Present status and future prospects

The growing incidence of type 2 diabetes (T2D) is a significant health concern, representing 90% of diabetes cases worldwide. As the disease progresses, resultant insulin deficiency and hyperglycaemia necessitates insulin therapy in many cases. It has been recognized that a significant number of people who have a clinical requirement for insulin therapy, as well as their healthcare professionals, are reluctant to intensify treatment with insulin due to fear of hypoglycaemia, poor understanding of treatment regimens or lack of engagement, and are therefore at higher risk of developing complications from poor glycaemic control. Over the past decade, the rise of diabetes technologies, including dosing advisors, continuous glucose monitoring systems, insulin pumps and automated insulin delivery systems, has led to great improvements in the therapies available, particularly to those requiring insulin. Although the focus has largely been on delivering these therapies to the type 1 diabetes population, it is becoming increasingly recognized that people with T2D face similar challenges to achieve recommended glycaemic standards and also have the potential to benefit from these advances. In this review, we discuss diabetes technologies that are currently available for people with T2D and the evidence supporting their use, as well as future prospects. We conclude that there is a clinical need to extend the use of these technologies to the T2D population to curb the consequences of suboptimal disease management in this group.

Voucher Reinforcement Decreases Psychiatric Symptoms in Young People in Treatment for Drug Use Disorders - A Post Hoc Secondary Analysis of a Randomized Controlled Trial

OBJECTIVE

This multicenter, parallel randomized, open study examined the effect of using vouchers and session reminders as an added element to outpatient treatment for drug use disorders in youth. It was hypothesized that being randomly assigned to a contingency management condition would lead to a reduction of psychiatric symptoms, and that this reduction would be mediated through abstinence and treatment completion.

METHODS

A total of 460 participants aged 15 to 25 years from nine outpatient sites were randomized to one of four treatment conditions (standard treatment alone [STD], i.e., 12 sessions using motivational interviewing and cognitive behavioral therapy, STD plus vouchers for attendance [VOU], STD plus text reminders [REM], or STD plus vouchers and text reminders [REM + VOU]). Participants' symptoms of psychological distress were assessed using the YouthMap 12 instrument at intake, and at 3, 6, and 9 months post-treatment initiation. Interviewers were blinded to interventions.

RESULTS

114 participants were randomized to STD, 112 to REM, 113 to VOU, and 121 to VOU + REM. 69 clients were never interviewed for follow-up, leaving 391 for analysis (n = 90, n = 94, n = 99, n = 108). The mean age was 20.5 years (SD = 2.6), 23% were female, and 34% reported having a psychiatric diagnosis. Random effects regression showed that participants randomized to one of the two voucher-based conditions experienced significantly steeper declines in symptoms compared with STD (p < .01). Structural equation modeling results indicated that the effects of contingency management on symptoms were mediated through abstinence, but not sessions attended.

CONCLUSIONS

Adding contingency management to interventions for drug use disorders can reduce symptoms of psychological and emotional distress among populations of treatment-seeking youth, in part due to indirect effects through abstinence at follow-up. The data is collected from a clinical trial registered as ISRCTN27473213, at https://www.isrctn.com/.