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.

Parents' experiences of caring for a young child with type 1 diabetes: a systematic review and synthesis of qualitative evidence.

AIMS: To synthesise the qualitative evidence on parents' experiences of caring for a child aged ≤8 years with type 1 diabetes to identify: the challenges they encounter; their views about support received; ways in which support could be improved; and, directions for future research. METHODS: We searched Medline, EMBASE, CINAHL, PsycINFO and Web of Science databases to identify qualitative studies reporting parents' views and experiences of caring for a child with type 1 diabetes aged ≤8 years. Key analytical themes were identified using thematic synthesis. RESULTS: Fourteen studies were included. The synthesis resulted in the generation of two overarching themes. Monopolisation of life describes the all-encompassing impact diabetes could have on parents due to the constant worry they experienced and the perceived need for vigilance. It describes how parents' caring responsibilities could affect their wellbeing, relationships and finances, and how a lack of trusted sources of childcare and a desire to enable a 'normal' childhood constrained personal choices and activities. However, use of diabetes technologies could lessen some of these burdens. Experiences of professional and informal support describes how encounters with healthcare professionals, while generally perceived as helpful, could lead to frustration and anxiety, and how connecting with other parents caring for a child with type 1 diabetes provided valued emotional and practical support. CONCLUSIONS: This synthesis outlines the challenges parents encounter, their views about support received and ways in which support might be improved. It also highlights significant limitations in the current literature and points to important areas for future research, including how sociodemographic factors and use of newer diabetes technologies influence parents' diabetes management practices and experiences. PROSPERO: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019128710.

A qualitative study of clinician attitudes towards closed-loop systems in mainstream diabetes care in England.

AIM: Clinicians mediate access to new technologies. Consequently, their views on specific devices may influence user access to diabetes technology in mainstream care. As yet, little is known about clinicians' views about closed-loop systems. This qualitative study explored clinicians' views on the likely impacts of future closed-loop systems in mainstream diabetes care in England. METHODS: We conducted interviews with 36 clinicians from a range of professional backgrounds in five hospital outpatient clinics (two adult, two pregnancy, one paediatric) in England to explore possible consequences of closed-loop systems for users and clinicians. Data analysis utilized a framework approach. RESULTS: Clinicians reported a range of expected benefits for future users, including improved glucose control and quality of life. Expected burdens included continued need for manual input and the risk of losing basic self-care skills. In terms of future clinical workloads, three clinicians emphasized only positive impacts, seven emphasized both positive and negative impacts, and 17 mentioned only negative impacts. Our most prominent finding, expressed by 24 clinicians, was that closed-loop systems would generate initial challenges due to the need for staff training, user education and support, and new analytical capacities, alongside existing intra-clinic variations in technological experience. CONCLUSIONS: Clinicians recognize the value of closed-loop systems in terms of health benefits, but also identify a range of concerns for both users and healthcare staff, which could impact negatively on user access. Future implementation efforts should address these concerns by providing training and support for healthcare teams, taking varied technological expertise into account.

Health professionals' views about who would benefit from using a closed-loop system: a qualitative study.

AIM: To explore health professionals' views about who would benefit from using a closed-loop system and who should be prioritized for access to the technology in routine clinical care. METHODS: Health professionals (n = 22) delivering the Closed Loop from Onset in type 1 Diabetes (CLOuD) trial were interviewed after they had ≥ 6 months' experience supporting participants using a closed-loop system. Data were analysed thematically. RESULTS: Interviewees described holding strong assumptions about the types of people who would use the technology effectively prior to the trial. Interviewees described changing their views as a result of observing individuals engaging with the closed-loop system in ways they had not anticipated. This included educated, technologically competent individuals who over-interacted with the system in ways which could compromise glycaemic control. Other individuals, who health professionals assumed would struggle to understand and use the technology, were reported to have benefitted from it because they stood back and allowed the system to operate without interference. Interviewees concluded that individual, family and psychological attributes cannot be used as pre-selection criteria and, ideally, all individuals should be given the chance to try the technology. However, it was recognized that clinical guidelines will be needed to inform difficult decisions about treatment allocation (and withdrawal), with young children and infants being considered priority groups. CONCLUSIONS: To ensure fair and equitable access to closed-loop systems, prejudicial assumptions held by health professionals may need to be addressed. To support their decision-making, clinical guidelines need to be made available in a timely manner.

Is an artificial pancreas (closed-loop system) for Type 1 diabetes effective?

The artificial pancreas is now a viable treatment option for people with Type 1 diabetes and has demonstrated improved glycaemic outcomes while also reducing the onus of self-management of Type 1 diabetes. Closed-loop glucose-responsive insulin delivery guided by real-time sensor glucose readings can accommodate highly variable day-to-day insulin requirements and reduce the hypoglycaemia risk observed with tight glycaemic control in Type 1 diabetes. In 2011, the James Lind Alliance research priorities for Type 1 diabetes were produced and priority 3 was to establish whether an artificial pancreas (closed-loop system) for Type 1 diabetes is effective. This review focuses on the progress that has been made in the evolution of closed-loop systems as an effective treatment option for Type 1 diabetes. Development of closed-loop systems has advanced from feasibility evaluations in highly supervised settings over short periods, to clinical studies in free-living, unsupervised conditions lasting several months. The approval in the USA of the first hybrid closed-loop system (MiniMed® 670G pump, Medtronic, Northridge, CA, USA) in 2016 for use in Type 1 diabetes reflects these advancements. We discuss the evidence from clinical studies that closed-loop systems are effective with improved glycaemic outcomes, reduced hypoglycaemia and had positive end-user acceptance in children, adolescents, adults and pregnant women with Type 1 diabetes. We also present the outlook for future closed-loop systems in the treatment of Type 1 diabetes and identify the challenges facing the wide-spread clinical adoption of this technology.

The impact of using a closed-loop system on food choices and eating practices among people with Type 1 diabetes: a qualitative study involving adults, teenagers and parents.

AIMS: We explored whether, how and why moving onto and using a hybrid day-and-night closed-loop system affected people's food choices and dietary practices to better understand the impact of this technology on everyday life and inform recommendations for training and support given to future users. METHODS: Twenty-four adults, adolescents and parents were interviewed before commencing use of the closed-loop system and following its 3-month use. Data were analysed thematically and longitudinally. RESULTS: While participants described preparing and/or eating similar meals to those consumed prior to using a closed-loop, many described feeling more normal and less burdened by diabetes in dietary situations. Individuals also noted how the use of this technology could lead to deskilling (less precise carbohydrate counting) and less healthy eating (increased snacking and portion sizes and consumption of fatty, energy-dense foods) because of the perceived ability of the system to deal with errors in carbohydrate counting and address small rises in blood glucose without a corrective dose needing to be administered. CONCLUSIONS: While there may be quality-of-life benefits to using a closed-loop, individuals might benefit from additional nutritional and behavioural education to help promote healthy eating. Refresher training in carbohydrate counting may also be necessary to help ensure that users are able to undertake diabetes management in situations where the technology might fail or that they take a break from using it.

Closed-loop insulin delivery in end-of-life care: a case report.

BACKGROUND: Glucose management for people with diabetes approaching the end of life can be very challenging. The aim is to balance a minimally invasive approach with avoidance of symptomatic hypo- and hyperglycaemia. CASE REPORT: We present a case of a hospitalized individual whose glucose was managed with closed-loop insulin delivery within a randomized controlled trial setting during a period of terminal illness. During the time in which closed-loop insulin delivery was used, glucose control was safe, with no glucose-related harm. The mean ± sd sensor glucose for this individual was 11.3 ± 4.3 mmol/l, percentage of time spent in target glucose range between 6 and 15 mmol/l was 70.5%, time spent in hypoglycaemia was 2.0% and time spent in significant hyperglycaemia >20 mmol/l was 2.6%. CONCLUSION: Closed-loop systems can accommodate personalized glucose targets and highly variable insulin requirements. Factory-calibrated continuous glucose sensors and insulin pump therapy are less intrusive than finger-stick glucose measurements and insulin injections, respectively. Closed-loop systems may provide a safer and less burdensome approach to glucose management towards the end of life.

Home Use of an Artificial Beta Cell in Type 1 Diabetes.

BACKGROUND: The feasibility, safety, and efficacy of prolonged use of an artificial beta cell (closed-loop insulin-delivery system) in the home setting have not been established. METHODS: In two multicenter, crossover, randomized, controlled studies conducted under free-living home conditions, we compared closed-loop insulin delivery with sensor-augmented pump therapy in 58 patients with type 1 diabetes. The closed-loop system was used day and night by 33 adults and overnight by 25 children and adolescents. Participants used the closed-loop system for a 12-week period and sensor-augmented pump therapy (control) for a similar period. The primary end point was the proportion of time that the glucose level was between 70 mg and 180 mg per deciliter for adults and between 70 mg and 145 mg per deciliter for children and adolescents. RESULTS: Among adults, the proportion of time that the glucose level was in the target range was 11.0 percentage points (95% confidence interval [CI], 8.1 to 13.8) greater with the use of the closed-loop system day and night than with control therapy (P<0.001). The mean glucose level was lower during the closed-loop phase than during the control phase (difference, -11 mg per deciliter; 95% CI, -17 to -6; P<0.001), as were the area under the curve for the period when the glucose level was less than 63 mg per deciliter (39% lower; 95% CI, 24 to 51; P<0.001) and the mean glycated hemoglobin level (difference, -0.3%; 95% CI, -0.5 to -0.1; P=0.002). Among children and adolescents, the proportion of time with the nighttime glucose level in the target range was higher during the closed-loop phase than during the control phase (by 24.7 percentage points; 95% CI, 20.6 to 28.7; P<0.001), and the mean nighttime glucose level was lower (difference, -29 mg per deciliter; 95% CI, -39 to -20; P<0.001). The area under the curve for the period in which the day-and-night glucose levels were less than 63 mg per deciliter was lower by 42% (95% CI, 4 to 65; P=0.03). Three severe hypoglycemic episodes occurred during the closed-loop phase when the closed-loop system was not in use. CONCLUSIONS: Among patients with type 1 diabetes, 12-week use of a closed-loop system, as compared with sensor-augmented pump therapy, improved glucose control, reduced hypoglycemia, and, in adults, resulted in a lower glycated hemoglobin level. (Funded by the JDRF and others; AP@home04 and APCam08 ClinicalTrials.gov numbers, NCT01961622 and NCT01778348.).

Bridging technology and clinical practice: innovating inpatient hyperglycaemia management in non-critical care settings.

Emerging evidence shows that suboptimal glycaemic control is associated with increased morbidity and length of stay in hospital. Various guidelines for safe and effective inpatient glycaemic control in the non-critical care setting have been published. In spite of this, implementation in practice remains limited because of the increasing number of people with diabetes admitted to hospital and staff work burden. The use of technology in the outpatient setting has led to improved glycaemic outcomes and quality of life for people with diabetes. There remains an unmet need for technology utilisation in inpatient hyperglycaemia management in the non-critical care setting. Novel technologies have the potential to provide benefits in diabetes care in hospital by improving efficacy, safety and efficiency. Rapid analysis of glucose measurements by point-of-care devices help facilitate clinical decision-making and therapy adjustment in the hospital setting. Glucose treatment data integration with computerized glucose management systems underpins the effective use of decision support systems and may streamline clinical staff workflow. Continuous glucose monitoring and automation of insulin delivery through closed-loop systems may provide a safe and efficacious tool for hospital staff to manage inpatient hyperglycaemia whilst reducing staff workload. This review summarizes the evidence with regard to technological methods to manage inpatient glycaemic control, their limitations and the future outlook, as well as potential strategies by healthcare organizations such as the National Health Service to mediate the adoption, procurement and use of diabetes technologies in the hospital setting.

Bolusing frequency and amount impacts glucose control during hybrid closed-loop.

AIM: To compare bolus insulin delivery patterns during closed-loop home studies in adults with suboptimally [HbA1c 58-86 mmol/mol (7.5%-10%)] and well-controlled [58 mmol/mol (< 7.5%)] Type 1 diabetes. METHODS: Retrospective analysis of daytime and night-time insulin delivery during home use of closed-loop over 4 weeks. Daytime and night-time controller effort, defined as amount of insulin delivered by closed-loop relative to usual basal insulin delivery, and daytime bolus effort, defined as total bolus insulin delivery relative to total daytime insulin delivery were compared between both cohorts. Correlation analysis was performed between individual bolus behaviour (bolus effort and frequency) and daytime controller efforts, and proportion of time spent within and below sensor glucose target range. RESULTS: Individuals with suboptimally controlled Type 1 diabetes had significantly lower bolus effort (P = 0.038) and daily bolus frequency (P < 0.001) compared with those with well-controlled diabetes. Controller effort during both daytime (P = 0.007) and night-time (P = 0.005) were significantly higher for those with suboptimally controlled Type 1 diabetes. Time when glucose was within the target range (3.9-10.0 mmol/L) during daytime correlated positively with bolus effort (r = 0.37, P = 0.016) and bolus frequency (r = 0.33, P = 0.037). Time when glucose was below the target range during daytime was comparable in both groups (P = 0.36), and did not correlate significantly with bolus effort (r = 0.28, P = 0.066) or bolus frequency (r = -0.21, P = 0.19). CONCLUSION: More frequent bolusing and higher proportion of insulin delivered as bolus during hybrid closed-loop use correlated positively with time glucose was in target range. This emphasises the need for user input and educational support to benefit from this novel therapeutic modality.

Patients' and caregivers' experiences of using continuous glucose monitoring to support diabetes self-management: qualitative study.

BACKGROUND: Continuous glucose monitoring (CGM) enables users to view real-time interstitial glucose readings and provides information on the direction and rate of change of blood glucose levels. Users can also access historical data to inform treatment decisions. While the clinical and psychological benefits of CGM are well established, little is known about how individuals use CGM to inform diabetes self-management. We explored participants' experiences of using CGM in order to provide recommendations for supporting individuals to make optimal use of this technology. METHODS: In-depth interviews (n = 24) with adults, adolescents and parents who had used CGM for ≥4 weeks; data were analysed thematically. RESULTS: Participants found CGM an empowering tool because they could access blood glucose data effortlessly, and trend arrows enabled them to see whether blood glucose was rising or dropping and at what speed. This predicative information aided short-term lifestyle planning and enabled individuals to take action to prevent hypoglycaemia and hyperglycaemia. Having easy access to blood glucose data on a continuous basis also allowed participants to develop a better understanding of how insulin, activity and food impacted on blood glucose. This understanding was described as motivating individuals to make dietary changes and break cycles of over-treating hypoglycaemia and hyperglycaemia. Participants also described how historical CGM data provided a more nuanced picture of blood glucose control than was possible with blood glucose self-monitoring and, hence, better information to inform changes to background insulin doses and mealtime ratios. However, while participants expressed confidence making immediate adjustments to insulin and lifestyle to address impending hypoglycaemia and hypoglycaemia, most described needing and expecting health professionals to interpret historical CGM data and determine changes to background insulin doses and mealtime ratios. While alarms could reinforce a sense of hypoglycaemic safety, some individuals expressed ambivalent views, especially those who perceived alarms as signalling personal failure to achieve optimal glycaemic control. CONCLUSIONS: CGM can be an empowering and motivational tool which enables participants to fine-tune and optimize their blood glucose control. However, individuals may benefit from psycho-social education, training and/or technological support to make optimal use of CGM data and use alarms appropriately.

Experiences of closed-loop insulin delivery among pregnant women with Type 1 diabetes.

AIMS: To explore the experiences of pregnant women with Type 1 diabetes, and the relationships between perceptions of glucose control, attitudes to technology and glycaemic responses with regard to closed-loop insulin delivery. METHODS: We recruited 16 pregnant women with Type 1 diabetes [mean ± sd age 34.1 ± 4.6 years, duration of diabetes 23.6 ± 7.2 years, baseline HbA1c 51±5 mmol/mol (6.8 ± 0.6%)] to a randomized crossover trial of sensor-augmented pump therapy vs automated closed-loop therapy. Questionnaires (Diabetes Technology Questionnaire, Hypoglycaemia Fear Survey) were completed before and after each intervention, with qualitative interviews at baseline and follow-up. RESULTS: Women described the benefits and burdens of closed-loop systems during pregnancy. Feelings of improved glucose control, excitement and empowerment were counterbalanced by concerns about device visibility, obsessive data checking and diminished attentiveness to hyper- and hypoglycaemia symptoms. Responding to questionnaires, eight participants felt less worry about overnight hypoglycaemia and that diabetes 'did not run their lives'; however, five reported that closed-loop increased time thinking about diabetes, and three felt it made sleep and preventing hyperglycaemia more problematic. Women slightly overestimated their glycaemic response to closed-loop therapy. Most became more positive in their technology attitudes throughout pregnancy. Women with more positive technology attitudes had higher degrees of overestimation, and poorer levels of glycaemic control. CONCLUSIONS: Women displayed complex psychosocial responses to closed-loop therapy in pregnancy. Perceptions of glycaemic response may diverge from biomedical data.

Artificial Pancreas Project at Cambridge 2013.

The development and clinical testing of closed-loop systems (the artificial pancreas) is underpinned by advances in continuous glucose monitoring and benefits from concerted academic and industry collaborative efforts. This review describes the progress of the Artificial Pancreas Project at the University of Cambridge from 2006 to 2014. Initial studies under controlled laboratory conditions, designed to collect representative safety and performance data, were followed by short to medium free-living unsupervised outpatient studies demonstrating the safety and efficacy of closed-loop insulin delivery using a model predictive control algorithm. Accompanying investigations included assessment of the psychosocial impact and key factors affecting glucose control such as insulin kinetics and glucose absorption. Translation to other disease conditions such as critical illness and Type 2 diabetes took place. It is concluded that innovation of iteratively enhanced closed-loop systems will provide tangible means to improve outcomes and quality of life in people with Type 1 diabetes and their families in the next decade.

Psychosocial aspects of closed- and open-loop insulin delivery: closing the loop in adults with Type 1 diabetes in the home setting.

AIMS: To explore the psychosocial experiences of closed-loop technology and to compare ratings of closed- and open-loop technology for adults with Type 1 diabetes taking part in a randomized crossover study. METHODS: Adults (aged > 18 years) on insulin pump therapy were recruited to receive a first phase of either real-time continuous glucose monitoring with overnight closed-loop or real-time continuous glucose monitoring alone (open-loop) followed by a second phase of the alternative treatment in random order, at home for 4 weeks, unsupervised. Participants were invited to share their views in semi-structured interviews. The impact of the closed-loop technology, positive and negative aspects of living with the device overnight, along with the hopes and anxieties of the participants, were explored. RESULTS: The participants in the trial were 24 adults with a mean (sd) age of 43 (12) years, of whom 54% were men. The mean (range) interview duration was 26 (12-46) min. Content and thematic analysis showed the following key positive themes: improved blood glucose control (n = 16); reassurance/reduced worry (n = 16); improved overnight control leading to improved daily functioning and diabetes control (n = 16); and improved sleep (n = 8). The key negative themes were: technical difficulties (n = 24); intrusiveness of alarms (n = 13); and size of equipment (n = 7). Of the 24 participant, 20 would recommend the closed-loop technology. CONCLUSIONS: Closed-loop therapy has positive effects when it works in freeing participants from the demands of self-management. The downside was technical difficulties, particularly concerning the pump and 'connectivity', which it is hoped will improve. Future research should continue to explore the acceptability of the closed-loop system as a realistic therapy option, taking account of user concerns as new systems are designed. Failure to do this may reduce the eventual utility of new systems.

Unsupervised home use of an overnight closed-loop system over 3-4 weeks: a pooled analysis of randomized controlled studies in adults and adolescents with type 1 diabetes.

AIMS: To compare overnight closed-loop and sensor-augmented pump therapy in patients with type 1 diabetes by combining data collected during free-living unsupervised randomized crossover home studies. METHODS: A total of 40 participants with type 1 diabetes, of whom 24 were adults [mean ± standard deviation (s.d.) age 43 ± 12 years and glycated haemoglobin (HbA1c) 8.0 ± 0.9%] and 16 were adolescents (mean ± s.d. age 15.6 ± 3.6 years and HbA1c 8.1 ± 0.8%), underwent two periods of sensor-augmented pump therapy in the home setting, in combination with or without an overnight closed-loop insulin delivery system that uses a model predictive control algorithm to direct insulin delivery. The order of the two interventions was random; each period lasted 4 weeks in adults and 3 weeks in adolescents. The primary outcome was time during which sensor glucose readings were in the target range of 3.9-8.0 mmol/l. RESULTS: The proportion of time when sensor glucose was in the target range (3.9-8.0 mmol/l) overnight (between 24:00 and 08:00 hours) was 18.5% greater during closed-loop insulin delivery than during sensor-augmented therapy (p < 0.001). Closed-loop therapy significantly reduced mean overnight glucose levels by 0.9 mmol/l (p < 0.001), with no difference in glycaemic variability, as measured by the standard deviation of sensor glucose. Time spent above the target range was reduced (p = 0.001), as was time spent in hypoglycaemia (<3.9 mmol/l; p = 0.014) during closed-loop therapy. Lower mean overnight glucose levels during closed-loop therapy were brought about by increased overnight insulin delivery (p < 0.001) without changes to the total daily delivery (p = 0.84). CONCLUSION: Overnight closed-loop insulin therapy at home in adults and adolescents with type 1 diabetes is feasible, showing improvements in glucose control and reducing the risk of nocturnal hypoglycaemia.

Safety, efficacy and glucose turnover of reduced prandial boluses during closed-loop therapy in adolescents with type 1 diabetes: a randomized clinical trial.

AIMS: To evaluate safety, efficacy and glucose turnover during closed-loop with meal announcement using reduced prandial insulin boluses in adolescents with type 1 diabetes (T1D). METHODS: We conducted a randomized crossover study comparing closed-loop therapy with standard prandial insulin boluses versus closed-loop therapy with prandial boluses reduced by 25%. Eight adolescents with T1D [3 males; mean (standard deviation) age 15.9 (1.5) years, glycated haemoglobin 74 (17) mmol/mol; median (interquartile range) total daily dose 0.9 (0.7, 1.1) IU/kg/day] were studied on two 36-h-long visits. In random order, subjects received closed-loop therapy with either standard or reduced insulin boluses administered with main meals (50-80 g carbohydrates) but not with snacks (15-30 g carbohydrates). Stable-label tracer dilution methodology measured total glucose appearance (Ra_total) and glucose disposal (Rd). RESULTS: The median (interquartile range) time spent in target (3.9-10 mmol/l) was similar between the two interventions [74 (66, 84)% vs 80 (65, 96)%; p = 0.87] as was time spent above 10 mmol/l [21.8 (16.3, 33.5)% vs 18.0 (4.1, 34.2)%; p = 0.87] and below 3.9 mmol/l [0 (0, 1.5)% vs 0 (0, 1.8)%; p = 0.88]. Mean plasma glucose was identical during the two interventions [8.4 (0.9) mmol/l; p = 0.98]. Hypoglycaemia occurred once 1.5 h post-meal during closed-loop therapy with standard bolus. Overall insulin delivery was lower with reduced prandial boluses [61.9 (55.2, 75.0) vs 72.5 (63.6, 80.3) IU; p = 0.01] and resulted in lower mean plasma insulin concentration [186 (171, 260) vs 252 (198, 336) pmol/l; p = 0.002]. Lower plasma insulin was also documented overnight [160 (136, 192) vs 191 (133, 252) pmol/l; p = 0.01, pooled nights]. Ra_total was similar [26.3 (21.9, 28.0) vs 25.4 (21.0, 29.2) µmol/kg/min; p = 0.19] during the two interventions as was Rd [25.8 (21.0, 26.9) vs 25.2 (21.2, 28.8) µmol/kg/min; p = 0.46]. CONCLUSIONS: A 25% reduction in prandial boluses during closed-loop therapy maintains similar glucose control in adolescents with T1D whilst lowering overall plasma insulin levels. It remains unclear whether closed-loop therapy with a 25% reduction in prandial boluses would prevent postprandial hypoglycaemia.

Glucose control in non-critically ill inpatients with diabetes: towards closed-loop.

Inpatient glycaemic control remains an important issue due to the increasing number of patients with diabetes admitted to hospital. Morbidity and mortality in hospital are associated with poor glucose control, and cost of hospitalization is higher compared to non-diabetes patients. Guidelines for inpatient glycaemic control in the non-critical care setting have been published. Current recommendations include basal-bolus insulin therapy, regular glucose monitoring, as well as enhancing healthcare provider's role and knowledge. In spite of growing focus, implementation in practice is limited, mainly due to increasing workload burden on staff and fear of hypoglycaemia. Advances in healthcare technology may contribute to an improvement of inpatient diabetes care. Integration of glucose measurements with healthcare records and computerized glycaemic control protocols are currently being used in some institutions. Recent interests in continuous glucose monitoring have led to studies assessing its utilization in inpatients. Automation of glucose monitoring and insulin delivery may provide a safe and efficacious tool for hospital staff to manage inpatient hyperglycaemia, whilst reducing staff workload. This review summarizes the evidence on current approaches to managing inpatient glycaemic control; its utility and limitations. We conclude by discussing the evidence from feasibility studies to date, on the potential use of closed loop in the non-critical care setting and its implication for future studies.

Absorption patterns of meals containing complex carbohydrates in type 1 diabetes.

AIMS/HYPOTHESIS: Successful postprandial glycaemia management requires understanding of absorption patterns after meals containing variable complex carbohydrates. We studied eight young participants with type 1 diabetes to investigate a large low-glycaemic-load (LG) meal and another eight participants to investigate a high-glycaemic-load (HG) meal matched for carbohydrates (121 g). METHODS: On Visit 1, participants consumed an evening meal. On follow-up Visit 2, a variable-target glucose clamp was performed to reproduce glucose and insulin levels from Visit 1. Adopting stable-label tracer dilution methodology, we measured endogenous glucose production on Visit 2 and subtracted it from total glucose appearance measured on Visit 1 to obtain meal-attributable glucose appearance. RESULTS: After the LG meal, 25%, 50% and 75% of cumulative glucose appearance was at 88 ± 21, 175 ± 39 and 270 ± 54 min (mean ± SD), whereas glucose from the HG meal appeared significantly faster at 56 ± 12, 100 ± 25 and 153 ± 39 min (p < 0.001 to 0.003), and resulted in a 50% higher peak appearance (p < 0.001). Higher apparent bioavailability by 15% (p = 0.037) was observed after the LG meal. We documented a 20 min deceleration of dietary mixed carbohydrates compared with dietary glucose for the HG meal and a twofold deceleration for the LG meal. CONCLUSIONS/INTERPRETATION: Absorption patterns may be influenced by glycaemic load and/or meal composition, affecting optimum prandial insulin dosing in type 1 diabetes.