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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.).

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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.

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AIMS: To explore the difficulties parents encounter in trying to achieve clinically recommended blood glucose levels and how they could be better supported to optimize their child's glycaemic control. METHODS: In-depth interviews were conducted with 54 parents of children with Type 1 diabetes (≤ 12 years). Data were analysed thematically. RESULTS: Parents described being reluctant and finding it difficult to keep their child's blood glucose levels consistently within clinically recommended ranges. As well as worrying about their child's ability to detect/report hypoglycaemia, parents highlighted a multitude of factors that had an impact on their child's blood glucose levels and over which they could exercise little control. These included: leaving their child with other caregivers who could not be trusted to detect hypoglycaemia; difficulties remotely monitoring and regulating their child's food consumption and activity; and physical and social changes accompanying childhood development. Most parents used two sets of blood glucose targets, with clinically recommended targets employed when their child was in their immediate care and higher targets when in the care of others. Parents described health professionals as lacking understanding of the difficulties they encountered keeping blood glucose within target ranges and needing more empathetic, tailored and realistic advice. CONCLUSION: It is not parents' fear of hypoglycaemia in isolation that leads to decisions to raise their child's blood glucose but, rather, parental fear in conjunction with other factors and considerations. Hence, to improve diabetes management in children, these factors may need to be addressed; for instance, by training others in diabetes management and using new technologies. Changes to consultations are also recommended.

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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.

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AIMS: To investigate the knowledge of alcohol and carbohydrate content of commonly consumed alcoholic drinks among young adults with Type 1 diabetes and to explore alcohol consumption while identifying diabetes self-management strategies used to minimize alcohol-associated risk. METHOD: We conducted an open-access, multiple-choice web survey to investigate knowledge of alcohol and carbohydrate content of typical alcoholic drinks using images. Respondents to the survey also recorded their current alcohol consumption and diabetes self-management strategies when drinking. RESULTS: A total of 547 people aged 18-30 years responded to the survey (341 women; 192 men; mean (sd) age 24.5 (3.7) years), of whom 365 (66.7%) drank alcohol. In all, 84 (32.9%) women and 31 (22.6%) men scored higher than the cut-off score for increased-risk drinking. Knowledge accuracy of alcohol units was poor: only 7.3% (n = 40) correctly identified the alcohol content of six or more out of 10 drinks. Knowledge of carbohydrate content was also poor: no respondent correctly identified the carbohydrate content of six or more out of 10 drinks. Various and inconsistent strategies to minimize alcohol-associated risk were reported. CONCLUSIONS: Alcohol consumption was common among the survey respondents, but knowledge of alcohol and carbohydrate content was poor. Greater alcohol-related health literacy is required to minimize alcohol-associated risk. Further research should help develop effective strategies to improve health literacy and support safe drinking for young adults with Type 1 diabetes.

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National Audit Data highlight persistent sub-optimum control among increasing numbers of people living with diabetes, with severe consequences for the individual and the NHS. The aim of the present review was to introduce a new cohesive, holistic model of care, tailored to individual needs to support optimum diabetes outcomes. This model of diabetes is necessary in order to understand the driving forces behind behaviour and their impact on diabetes management. Feelings (an emotional state or reaction) and beliefs (an acceptance that something is true or real) are fundamental behavioural drivers and influence diabetes self-management choices. Individually, these explain some of the complexities of behaviour and, collectively, they impact on personal motivation (rationale/desire to act) to achieve a specific outcome. Inevitably, they independently affect diabetes self-management and the environment in which individuals live. A model of care that proposes the encompassing of environment, intrinsic thought and therapy regimens to provide tailored, personalized healthcare should support enhanced diabetes self-management and outcomes from diagnosis. The Kaleidoscope model of care could be deliverable in routine care, incorporating each of the influences on diabetes self-management, and should benefit both individuals with diabetes and healthcare professionals.

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AIMS: Quality of life (QoL) is recognized widely as an important health outcome in diabetes, where the burden of self-management places great demands on the individual. However, the concept of QoL remains ambiguous and poorly defined. The aim of our review is to clarify the measurement of QoL in terms of conceptualization, terminology and psychometric properties, to review the instruments that have been used most frequently to assess QoL in diabetes research and make recommendations for how to select measures appropriately. METHODS: A systematic literature search was conducted to identify the ten measures most frequently used to assess QoL in diabetes research (including clinical trials) from 1995 to March 2008. RESULTS: Six thousand and eight-five abstracts were identified and screened for instrument names. Of the ten instruments most frequently used to assess 'QoL', only three actually do so [i.e. the generic World Health Organization Quality of Life (WHOQOL) and the diabetes-specific Diabetes Quality of Life (DQOL) and Audit of Diabetes-Dependent Quality of Life (ADDQoL)]. Seven instruments more accurately measure health status [Short-Form 36 (SF-36), EuroQoL 5-Dimension (EQ-5D)], treatment satisfaction [Diabetes Treatment Satisfaction Questionnaire (DTSQ)] and psychological well-being [Beck Depression Inventory (BDI), Hospital Anxiety and Depression Scale (HADS), Well-Being Questionnaire (W-BQ), Problem Areas in Diabetes (PAID)]. CONCLUSIONS: No single measure can suit every purpose or application but, when measures are selected inappropriately and data misinterpreted, any conclusions drawn are fundamentally flawed. If we value QoL as a therapeutic goal, we must ensure that the instruments we use are both valid and reliable. QoL assessment has the proven potential to identify ways in which treatments can be tailored to reduce the burden of diabetes. With careful consideration, appropriate measures can be selected and truly robust assessments undertaken successfully.

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AIM: To review systematically the published literature addressing whether continuous subcutaneous insulin infusion (CSII) provides any quality of life benefits to people with Type 1 diabetes. METHODS: Electronic databases and published references were searched and a consultation with two professional groups was undertaken to identify relevant studies published up to July 2005. A multistep selection process was then undertaken to identify those articles which met the specific selection criteria, which were then critically reviewed. RESULTS: Eighty-four potential relevant articles were identified from examination of titles and abstracts published during the specified time frame. Of these, 28 articles were retrieved in full text, of which 17 fulfilled the specific criteria for inclusion. Mixed results emerged from existing literature. Of the five randomized controlled trials, three reported mixed results, with one study reporting quality of life benefits and one reporting no evidence of quality of life benefits. CONCLUSIONS: There is conflicting evidence reported in the various studies on the quality of life benefits of CSII in Type 1 diabetes. Existing research is flawed, making a judgement about the quality of life benefits of insulin pump use difficult. There is no strong evidence against quality of life benefits associated with CSII or otherwise, with poor methodology and inconsistent assessment of quality of life clouding the issue. The lack of reported benefit is probably a function of this rather than pump therapy not offering any quality of life benefits.

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AIM: To review the literature estimating the cross-sectional prevalence of clinical depression in adults with Type 1 diabetes. METHODS: Electronic databases and published references were used to identify studies published between January 2000 and June 2004, with a previous meta-analysis used to identify studies before 1 January 2000. RESULTS: Between January 2000 and June 2004, a further five eligible studies were identified. Only one was a controlled study using diagnostic interviewing to determine rates of depression. Taking all of the eligible studies identified by the previous meta-analysis and this search, the prevalence of clinical depression in controlled studies was 12.0% for people with diabetes compared with 3.2% for control subjects. In studies with no control group, the prevalence of clinical depression was 13.4%. CONCLUSION: There are wide-ranging differences reported in the various studies on the prevalence of depression in Type 1 diabetes. In view of the differing methods of diagnosis and small participant numbers, the results should be viewed with caution. A controlled study using diagnostic interviewing techniques to determine levels of depression is recommended to provide a clearer picture of both the prevalence and characteristics of that depression.

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