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Closed-loop insulin delivery system for management of hypoglycaemia in type 1 diabetics

Source agency:
HPACT
Date of Submission:
13/09/2010
Date of Printing:
21/09/2014
Disclaimer:
This report is work in progress and should not be used for external distribution without permission from the originating agency. Users should be aware that reports are based on information available at the time of research and often on a limited literature search.

Technology, Company & Licensing

Technology name:
Artificial pancreas for management of hypoglycaemia in type 1 diabetics
Technology - description:
Closed-loop insulin delivery is a system that acts as an ‘artificial pancreas’. The system utilises coupled technologies – real-time continuous glucose monitoring and insulin pumps – for improved glucose control among type 1 diabetes patients. Various companies make commercially available glucose monitors and pumps, however, only recently have devices been manufactured to function jointly. These closed-loop devices mimic non-diabetic insulin delivery via real-time control algorithms, rather than by pre-programmed rates that govern insulin pumps alone. Medtronic (Northridge, CA) offers fully integrated systems (the Paradigm Veo™ Insulin Pump and Continuous Glucose Monitoring System is marketed in Australia) with the MiniLink® transmitter for wireless data input to a pump with LCD display.
Company or developer:
Medtronic (Northridge, CA)
Reason for database entry:
This is a innovative treatment that is expected to have a large health benefit - would apply to a large patient group that has significant associated morbidity.
Technology - stage in early warning process:
Assessment complete
Technology - stage of development:
Established
Licensing, reimbursement and other approval:
AUSTRALIAN THERAPEUTIC GOODS ADMINISTRATION APPROVAL ARTG number 95763
Technology - type(s):
Device
Technology - use(s):
Combination

Patient Indication & Setting

Patient indications:
Type 1 Diabetes
Disease description and associated mortality and morbidity:
Diabetes mellitus is characterised by a total or near total insulin deficiency, resulting in an acute elevation of blood glucose levels (hyperglycaemia), rapid acidification of the blood (ketoacidosis), and death, unless treated with insulin. Onset may occur at any age but usually in childhood or adolescence. Type 1 diabetes is often referred to as an auto-immune disease as in most cases it is caused by the immune system attacking and destroying the pancreatic beta-cells, which produce insulin. Although there is a basal release of insulin from the Beta-cells, insulin synthesis and secretion is mainly controlled by the concentration of glucose in the blood, i.e. a high blood glucose level leads to insulin secretion. Insulin is inhibited by a feedback mechanism controlled by the sympathetic nervous system. Insulin affects every tissue in the body but particularly liver, muscle and fat cells. The overall function of insulin is to facilitate the uptake, utilisation and storage of glucose, amino acids and fats after a meal; a fall in insulin causes a reduced uptake of these substances and an increase in the mobilisation of fuel stores. WHO criteria recommend that diagnosis of diabetes should be based on a fasting plasma glucose level in excess of 126 mg/dL (7mmol/L) and/or a 2-hour plasma glucose level in excess of 200 mg/dL (11 mmol/L) following an oral glucose tolerance test (Richter et al 2007).
Despite the importance of overall management of blood glucose, including the avoidance of hyperglycaemia, this summary draws specific attention to the control of hypoglycaemia, which can pose the most immediate adverse and life-threatening effects among type 1 diabetics. Since the danger of hypoglycaemia can limit the application of intensive therapy for type 1 diabetes, there have been initiatives to develop insulin delivery devices that respond to glucose concentrations and automatically regulate blood glucose to the non-diabetic range (El-Khatib et al 2010). This forms the basis for the control of hypoglycaemia using closed-loop insulin delivery systems. The algorithms used in these systems are varied, but primarily work by initialising an individual’s insulin sensitivity from basal insulin requirements, then adapting the estimate in real-time on the basis of administered insulin and resulting sensor glucose concentrations (Hovorka et al 2010). In short, the closed-loop system comprises a pump which continuously infuses rapid-acting insulin at a basal level, whilst at the same time the glucose sensor continuously monitors glucose levels, with the infused insulin dose being adjusted according to the glucose levels obtained.
Number of Patients:
In Australia during the period 2000-2006, the annual age-adjusted incidence rate of type 1 diabetes among children aged 0-14 years was 22.4 new cases per 100,000 population. There has been a slight increase in the incidence in this age group from 19.2 in 2000 to 22.6 in 2006, with the greatest increase occurring in 10-14 year olds (Catanzariti et al 2008). In comparison to other OECD countries, the incidence of type 1 diabetes in Australia is high, with only Norway, Sweden and Finland having a higher annual incidence. Amongst people aged 15-years and over at first insulin use, there were an average of 1,260 new cases per year. The rate of new cases amongst people aged over 15-years decreases dramatically with age and plateaus at age 45-years. The peak annual incidence rate of type 1 diabetes occurs at age 15-years (Pieris-Caldwell et al 2008).
Technology - specialities(s):
Endocrine, nutritional and metabolic
Technology - setting(s):
Community and primary care
Setting - further information:
 

Impact

Alternative and/or complementary technology:
Additive or complementary technology
Current Technology:
Type 1 diabetics are frequently treated with multiple daily injections of slow-acting insulin or insulin analogues (Cohen et al 2007). Injection regimes are usually informed by self-monitoring of blood glucose by capillary finger-prick test, or continuous subcutaneous monitoring may be employed. Standard pumps without the use of CGM data may be used in regimes based on capillary blood glucose measurements (Jacobsen et al 2009).
Health Impact:
Most of the identified sources have shown at least some improvement in overall management of blood glucose associated with closed-loop insulin delivery. However, outcomes in terms of hypoglycaemia were not consistent. One study provided relatively tenuous evidence for improved hypoglycaemic control with closed-loop (Hovorka et al 2010), one indicated a marked statistical difference between groups for hypoglycaemia despite small sample size (Clarke et al 2009), and the remaining studies did not show differences in hypoglycaemia outcomes.
Diffusion:
2012 Diffusion of technology in Australia
Currently there is no fully automated closed loop system (CLS) commercially available anywhere in the world, with varying degree of user input required due to the challenges posed by individual variations in insulin sensitivity and lifestyle such as meal, exercise and stress. Research is underway to develop CLSs of increasing complexity towards the true fully automated close loop system with low glucose suspense, meal announcement, exercise entry and bi-hormonal CLS.1, 2 Despite this, the individual components (eg. continuous glucose monitoring device, insulin pump) of a CLS have been available for some time. CLS is still considered to be at pre-clinical and early clinical development stage, so far mainly limited to inpatient studies and just started to move to outpatient settings.3 According to the FDA, the first Premarket Approval application for a fully automated CLS could be 5-years away.1, 4
Personal communication with Australian leading clinician involved in CLS study has indicated that outpatient trials in Australia are planned in 2013. Further refinements to progress to more sophisticated system and studies to test these systems are required. Optimistically, there may be 4-8 years before fully closed loop system will be available in Australia.
It should be noted that the assessment from the 2010 Priority Summary is more focused on the continuous glucose monitoring (CGM) and insulin pump components of a true CLS, and thus impacting on its judgement on the stage of development of the system and some of the included studies.5, 6

2010 Diffusion in Australia
The Paradigm Veo™ System (see full report) is currently marketed to private patients in Australia by Medtronic Australasia Pty Ltd. Models MMT-554 and MMT-754 are listed under billing codes MC839 and MC840 on the Commonwealth Prostheses List. Under provision of the Private Health Insurance Act 2007, private health insurers are obliged to pay a benefit towards listed prostheses provided as part of an episode of hospital or hospital substitute treatment for which a patient has cover and for which a Medicare benefit is payable for the associated professional service (Department of Health and Ageing 2010).
Cost, infrastructure and economic consequences:
2012 Cost Impact
According to ECRI 1, the costs of CLS has not been determined. Currently CGMs cost approximately US$1,000, and the cost of an individual sensor varies from US$35 to US$115 and that a monthly cost of sensors ranges from US$300 to US$400. Available insulin pumps cost US$4,000 to US$6,000, with yearly maintenance costs over US$1,000. The cost of a CLS will exceed the combined cost of CGM and insulin pumps, as a result of addition of complex control software and a portable computing device. It is anticipated that the first-generation portable CLSs will cost more than US$10,000 initially, with additional cost of more than US$1,500 to US$2,000 annually for maintenance and suppliers.
A few models of Medtronic MiniMed insulin infusion pump are list on the Prostheses list, with a minimum benefit of A$8,950 for the Paradigm model and A$9,500 for the Paradigm Veo model. Personal communication with Medtronic Australasia Pty Ltd indicates that the sensors for the Paradigm Veo™ System cost A$375 for a box of five and the insulin pump is covered by a four-year warranty.

2010 Cost Impact
In Australia, for the year 2004-05, diabetes accounted for 1.9 per cent of the year’s total allocated recurrent health expenditure with a direct health-care expenditure of $989 million. It is estimated that expenditure on Type 1 diabetes accounted for 14% of this expenditure, at $139 million and $22 million related to diabetes prevention services. The greatest proportion of diabetes expenditure was on hospital services, $371 million (37.5%) followed by out-of-hospital medical services, $288 million (29.1%), diabetes-related pharmaceuticals, $275 million (27.8%), and research, $55 million (5.6%).
The National Diabetes Services Scheme (NDSS) provides access to products and services including syringes, insulin infusion pump consumables and blood and urine glucose testing reagents that are required for self-management of diabetes at prices subsidised by the Australian Government. The state and territory governments contribute co-payments for needles and syringes. In 2006–07, there were 844,062 people registered with the NDSS and the Australian government expenditure on the NDSS in that financial year was approximately $114 million (Pieris-Caldwell et al 2008).
Medtronic Australasia Pty Ltd markets the Paradigm Veo™ System for A$8,000; however the transmitter costs an additional A$1,250. Cost of sensors is also extra; A$725 for a box of 10 or A$310 for a box of four. Each sensor typically lasts for six days of normal use, after which a replacement is recommended (Medtronic personal communication).
Ethical, social, legal, political and cultural impact:
No ethical, cultural or religious issues were identified/raised in the sources examined.

Evidence & Policy

Clinical evidence and safety:
2012 Safety and Effectiveness
Since the 2010 HealthPACT Priority Summary on CLS was developed, a large number of in-patient trials on CLS, or its components, have been or are being conducted 1. For the purpose of this update, generally only comparative studies on CLS with the three key components (continuous glucose monitoring device, insulin pump and a control algorithm) with a sample size of at least 10 are considered, with the exception of the first out-patient pilot studies and two Australian studies to provide local data for reference. In summary, a brief report of pilot of CLS on two outpatients3, a meta-analysis combining data from four RCTs of Cambridge cohorts for both children and adults 7, five cross-over trials,8-11 two Australian studies12, 13 are included in the update. The results from one of the cross-over study by Hovorka 9 are not presented separately as it has been included in the meta-analysis.
So far, artificial pancreas (AP) has only been piloted on two adult patients with type 1 diabetes in an out-of-hospital setting (a hotel located within one km from the emergency room)3 (level IV intervention). The AP is developed by the University of Virginia, with the algorithm including safety supervision responsible for the prevention of hypoglycaemia and a range of correction module delivering insulin corrections as needed. AP initiation allows for patient-specific characteristics, confirmation of meal boluses, and optional entries of exercise and hypoglycaemia treatment. The study lasted for three days, with three consecutive phases labelled as open-loop in the hotel (day 1), closed-loop in the clinic (day 2), and closed-loop in the hotel (day 3). Meal bolus was recommended by the AP and was approved by the patients, whereas basal rate and corrections were automatically delivered by the AP. During the study, the data from the sensor, insulin pump and system were sent to a remote server every five minutes to ensure continuous monitoring of the patients and the system. The pilot studies showed that the AP avoided hypoglycaemia (<3.9mmol/L) and major hyperglycaemia (>15mmol/L) in both cases. No adverse events occurred. The results demonstrate that the system for ambulatory use is feasible and safe, thus warranting further testing.
Breton et al reported the results of two multi-centre randomised cross-over trials to assess the effectiveness of two fully integrated CLS, compared with open-loop CSII, implementing a strategy known as control to range (CTR)11 (level II intervention). The first system, standard CTR (sCTR), aims to prevent hypoglycaemia and mitigate extreme hyperglycaemia, without truly aiming for optimal glucose control. The second system, enhanced CTR (eCTR), aims for optimal glucose control within a target range. CGM devices, either Dexcom 7 (Dexcom Inc.) or Navigator (Abbott), and Omnipod insulin pump (Insulet Corporation) were used for the studies. Study 1 (sCTR vs CSII) included 26 patients (11 adolescents and 15 adults) with T1DM and Study 2 (eCTR vs CSII) recruited 12 adults with T1DM. Both studies adopted identical design which lasted for 22 hours for both admissions, including 30 minutes of moderate exercise, a patient-selected meal, a standard snack, and an 18-hour CLS on the experimental days. Reference glucose values were monitored at least every hour over the study period and more frequently during the exercise. Hypoglycaemia was defines as reference glucose reading < 3.9mmol/L or the presence of hypoglycaemia symptoms.
Study1 (sCTR vs CSII): As shown in Figure 1 (can be accessed in the full report available on the weblink), time spent in near normoglycaemia (3.9-10mmol/L) increased significantly both overall (p=0.01) and, especially, overnight (p=0.016) during sCTR compared to CSII. An overall 2.7-fold reduction in hypoglycaemic events was observed from 27 events during open-loop to 10 events during sCTR, with the maximum 6-fold reduction overnight observed. However, average glucose was not reduced significantly either overall or overnight, whereas a significant decrease in the overnight risk of hyperglycaemia was observed as measured by high blood glucose index (HBGI) (8.39±1.85 vs 4.35±0.82 for CSII and sCTR respectively, p=0.014).

Study 2 (eCTR vs CSII): Compared to CSII, significant decrease in the average plasma glucose were observed both overall (p<0.01) and overnight (p=0.042) during eCTR (see Figure 2 (in the report accessible on the weblink) in the report on the weblink). Time spent in near normoglycaemia increased significantly overall (p<0.05) but not overnight, whereas time spent in tight control (4.4-7.8mmol/L) increased significantly overnight (42.7% vs 79.3% CSII and eCTR respectively, p=004). Hypoglycaemia events occurred similarly during the CSII and eCTR phases (1.4 events/patient and 1.6 events/patient respectively, p=0.43). In addition, intra-subject glucose variability was significantly reduced overnight (CSII 1.35±0.14, eCTR 0.84±0.16, p=0.045).
The authors concluded that the two CTR algorithms represent sequential steps toward automated glycaemic control. As intended, sCTR significantly decreased hypoglycaemic events and, at the same time, increased time spent in near normoglycaemia. eCTR improved glucose control without apparent increase in the risk of hypoglycaemia. The companies provided the insulin pump and glucose sensors for the trials, no other potential conflicts of interest were reported.
A meta-analysis included a) two children and adolescent studies where CLS (Medtronic MiniMed) was used following a standard evening meal (APCam01) or following 40 minutes of moderate-intensity exercise (APCam 03) and b) two adult studies where CLS (Abbott Diabetes Care) was used following a medium-size evening meal (Angela01) or a large evening meal accompanied by alcohol (Angela02) 7 (level I intervention). All included studies adopted a randomised cross-over design where each patient with T1DM completed two overnight visits 1-3 weeks apart, one using CLS and the other CSII. All meals were accompanied by an individualised insulin bolus. Plasma glucose and insulin were monitored every 15 and 30 minutes respectively; however the glucose level was not used to adjust the insulin infusion rates during visits. The sensor glucose was inputted by the research nurse into the computer to calculate the basal infusion rate on the insulin pump.
Seventeen children and 24 adults completed 45 CLS and 45 CSII visits. The study result was summarised in Table 1 and Figure 3 (in the report accessible on the weblink). The primary outcomes, proportion of plasma glucose in target range (3.91-8.0 mmol/L) overnight, was significantly higher during the CLS visits compared to CSII visits for both young and adult patients. Similar result was seen in the pooled analysis with 71 per cent in the CLS and 43 per cent in the CSII of plasma glucose measures being in the target range overnight (p<0.001) (see Figure 3 in the report accessible on the weblink). Time spend in the hypoglycaemia was significantly less during the CLS visits compared to CSII visits for both young and adult patients. Pooled analysis showed that overall 2.1 per cent of the measures during CLS, compared to 4.1 per cent during CSII, were in hypoglycaemia (p=0.01). Low glucose index was also decreased during the CLS visits in both groups and the pooled analysis. In the child and adolescent studies, one episode of hypoglycaemia (plasma glucose ≤ 3 mmol/L) during CLS and six episodes during the CSII occurred in seven patients, with one episode in the CSII resulting in early termination of study. In the adult studies, four hypoglycaemic events during CLS and seven during CSII occurred in nine patients, and one event led to early termination of study. The proportions of glucose values > 8.0 mmol/L were lower during CLS compared with CSII for both young and adult patients, however the difference was not significant in the child and adolescent studies among which five glucose measurements were > 16.7 mmol/L (one during CLS and four during CSII). No plasma glucose values > 16.7 mmol/L recorded in the adult studies. The pooled analysis showed a significant difference in time spent in hyperglycaemia (20% for CLS vs 33% for CSII, p=0.03). It can be seen from Figure 3 that there was less variability of plasma glucose overnight during the CLS compared with CSII, however there was no difference in the average plasma glucose and insulin concentration (see Table 1 in the report accessible on the weblink).
The authors concluded that overnight CLS can improve glycaemic control and reduce the risk of nocturnal hypoglycaemia in both young and adult patients with T1DM, and the performance was maintained when variation due to lifestyle was taken into account. It is worth noting though that the study results need to be interpreted with caution given the variation in study population, study protocols and noted conflicts of interest for a number of investigators.
A randomised crossover study compared the safety and efficacy of closed-loop system (Animas 2020, Johnson & Johnson) over two 24-hour visits in pregnant women with T1DM10 (level II intervention). Twelve pregnant women were randomly assigned to either closed-loop or CSII group then crossed over to the other group after a between-visit interval of 1─6 weeks. Hypoglycaemic was defines as plasma glucose levels ≤ 54 mg/dL with symptoms or ≤ 45 mg/dL without symptoms. The main study results are summarised in Table 2 (available in the report on the weblink). There were 13 hypoglycaemic episodes during the closed-loop phase compared to 20 hypoglycaemic episodes during CSII. The risk of severe hypoglycaemia, measured by low blood glucose index, was lower during the closed-loop phase (p=0.03), with less time spent below 45 mg/dL (p=0.04). The time spent in the target range for overnight plasma glucose was high in both phases, with no difference between the two visits. However the authors reported that there was significantly more time spent in target for glucose measurements according to CGM during closed-loop (98% vs 83% for CSII, p=0.03), no discrepancies were observed between plasma and CGM measurements during any other time period. The study concluded that CLS was as effective as CSII but potentially safer due to reduced duration and extent of hypoglycaemia. Conflicts of interest were declared by a number of authors in a range of forms from the industries.
A small multinational cross-over study compared CLS and CSII in 20 T1DM adult patients in three centres in the USA, Italy and France8 (level III-2 intervention evidence). The study included two 22-hour overnight admissions separated by 2-4 weeks waiting period with the first admission using CSII and the second CLS (OmniPod, Insulet Corp.). Standard meals with same carbohydrate content were consumed during both admission periods. The insulin boluses suggested by the algorithm every 15 minutes was programmed into the insulin pump by the attending physician, when the values were acceptable. Reference blood glucose was sampled every 30 minutes and fast-acting carbohydrate was given when reference glucose fell below 3.9mmol/L regardless of the CGM readings. Primary outcomes were number of hypoglycaemic events (plasma glucose<3.9 mmol/L) and percentage of time within target range (plasma glucose 3.9-7.8 mmol/L). As shown in Figure 4 (available in the report on the weblink), the percentage of time spend in the target range overnight increased significantly from 64 per cent during CSII to 78 per cent during CLS (p=0.029), although there was no difference in average plasma glucose level between the groups. Overnight, five hypoglycaemic episodes occurred during CLS compared to 23 hypoglycaemic episodes during CSII (p<0.01), resulting in an almost 5-fold reduction. However no between groups difference on any of the outcomes was detected during the breakfast control phase. The study concluded that, compared with open-loop, CLS improved overnight regulation of diabetes. Similarly, conflicts of interest were noted by a number of authors.
An abstract of a recent Australian study investigated the efficacy and safety of a fully automated, portable CLS (Medtronic Portable Glucose Control System (PGCS)) in eight adolescent patients with TIDM 13 (level IV intervention evidence). PGCS consists of two subcutaneous glucose sensors, a control algorithm with insulin feedback operating from a BlackBerry Storm smartphone platform, Bluetooth radiofrequency translator, and a Paradigm Veo insulin pump. Patients underwent two consecutive in-clinic, overnight, closed-loop control after a baseline open-loop assessment. The proportion of time the sensor glucose values were maintained between 3.9 and 8mmol/L was greater for closed-loop than open-loop (84.5% vs 46.7% respectively, p < 0.0001), and time spent sensor glucose < 3.3mmol/L was also reduced (0.9% vs 3% respectively, p < 0.0001). In addition, the proportion of time with venous plasma glucose < 3.9mmol/L, between 3.9 and 8mmol/L (70 and 144 mg/dL), and > 8mmol/L was 7 per cent, 78 per cent, and 15 per cent, respectively. The authors concluded that that the automated CLS is safe and effective in achieving overnight glucose control in patients with type 1 diabetes.
Another Australian study evaluated an algorithm guiding responses of continuous insulin infusion using real-time CGM (Medtronic MiniMed) in type 1 diabetic patients12 (level II intervention evidence). This two-phase RCT included 60 age, sex and AIC-matched adolescent and adult patients. Phase 1 (16 weeks) compared glycaemia in patients using CLS plus an algorithm (group A) to patients using CLS without the algorithm (group B), and a follow-up phase 2 (16 weeks) evaluated whether glucose changes persisted after CGM withdrawal (group A returning to usual care (CSII)) and whether late algorithm introduction improved glycaemia (group B continuing with CLS plus the algorithm). At the end of phase 1, the change in percentage of time in target glucose time, the primary study outcome, and AIC did not differ between the groups, however more patients in group A achieved A1C≤7% compared with group B (14/29 vs 7/28 respectively, p=0.015). During phase 2, A1C in group A increased from 16 weeks and reversed to the baseline value, whereas there was no significant changes in target or low glucose times and A1C in group B compared to baseline or 16 weeks (see Figure 5 in the report accessible on the weblink). No statistical between-group comparison was performed for the outcomes at phase 2. Severe hypoglycaemic episodes occurred in two patients in group A in phase 1 and one group A patient in phase 2. Other adverse events happened infrequently during the study period.


2010 Evidence
Continuous glucose monitoring has previously been assessed for use in Type-I diabetes and for women with gestational diabetes.
Literature detailing the use of closed-loop insulin delivery is extensive and many small studies were identified. Therefore, this summary only considers larger studies and Australian research in determining whether closed-loop systems offer safe and improved management of hypoglycaemia, relative to the appropriate comparators.
The RealTrend study in France randomised 132 adults and children (81 adults and 51 children aged 2to 65 years) to receive standard insulin pump or closed-loop therapy across eight centres, and followed outcomes for six months (Raccah et al 2009) (level III-1 intervention evidence). All subjects had uncontrolled type 1 diabetes (glycated haemoglobin ≥ 8% - the internationally recommended target is HbA1C < 7%) and were being treated with multiple daily injections. Patients assigned to closed-loop therapy were fitted with the Medtronic MiniMed Paradigm Real-Time system (PRT group) and agreed to wear the sensor component for at least 70 per cent of the study period. Outcomes of interest, obtained for 115 patients, included HbA1C levels and glycaemic variability. A difference of ≥ 0.5 per cent between treatment groups was taken as clinically meaningful. It is critical to note that because HbA1C levels are measured and sometimes reported as a per cent, a change of ≥ 0 5 per cent in fact represents an absolute change.
Screening was performed to determine HbA1C levels at study commencement (visit 1), three and six months (study physicians and patients were blinded to the centralised HbA1C data ). Two weeks after screening, biochemical hyper- and hypoglycaemic parameters were collected using a blinded continuous glucose monitoring (CGM) device over three days (this process was required to initialise the closed-loop algorithm). Blinded CGM data were retrieved at the end of this period (visit 2), and PRT patients were then asked to start using the unblinded sensor component of their closed-loop equipment while continuing multiple injection treatment for nine days. During this period, PRT patients were free to use CGM information as desired. At visit 3, insulin pump therapy began in both groups – patients in the PRT started using the pump function of their device, while subjects in the standard continuous subcutaneous insulin infusion (CSII) group were fitted with the Medtronic MiniMed Paradigm 512/712 (no CGM). Subjects in both groups continued use of their usual blood glucose meters to obtain a minimum of three daily readings, which served as reference for therapeutic decisions. The PRT group were advised on appropriate pump programming in response to CGM information.
One month after pump therapy commencement (visit 4), data from both groups devices were downloaded and patients discussed treatment with a study physician. Sensor alarm settings for hypo- and hyperglycaemia were adjusted as necessary. At the conclusion of three months pump therapy (visit 5), data were again downloaded, blood samples were taken for HbA1C determination, and treatment guidelines adjusted as required. Three days before the final study visit, following six months of pump therapy, all subjects again wore a blinded CGM device. Blinded CGM, PRT and CSII data were downloaded at study conclusion.
Although analysis was possible for 115 patients, only 91 out of this full set of patients were protocol compliant. Consequently, analysis was conducted for the full set and then separately for the 91 compliant patients. Of the 55 PRT patients, 23 failed to comply with the study protocol, i.e. did not use the sensor component of their device at least 70 per cent of the time, whereas 59 of the 60 CSII patients met the protocol requirements (one failed screening).
In the full set analysis, HbA1C levels between baseline and study end were significantly reduced in both groups (PRT -0.81 ± 1.09%, p < 0.01; CSII -0.57 ± 0.94%, p < 0.001), but the difference in favour of the PRT was not statistically significant (p=0.087). For patients who were fully compliant with the protocol, HbA1C was significantly more reduced among PRT subjects (PRT -0.96 ± 0.93%, p < 0.001; CSII -0.55 ± 0.93%, p < 0.001; intergroup comparison, p=0.004).
The initial decline in HbA1C between screening and baseline could indicate an immediate benefit of exposure to CGM data and possibly explain blunting of the difference seen between baseline and study end. The authors suggest a more meaningful comparison of HbA1C data between screening and study end, however such an analysis falls outside the scope of this summary which is limited to appraisal of CGM and insulin pump therapy in tandem, not the benefits of CGM alone.
Analysis of glycaemic control for the full set of 115 subjects showed a decrease in mean glucose concentration among both groups between baseline and study end. This reduction was significantly greater in the PRT group (-30.6 ± 54.0) than in the CSII group (-10.8 ± 39.6, p=0.005). Significant differences favouring the PRT group were also observed with respect to hyperglycaemia, mean amplitude of glycaemic excursions and overall standard deviation of blood glucose values. Similarly, trends of improved glycaemic variation were observed among protocol compliant patients (n = 91), although it is thought that the small sample size meant that some trends did not reach statistical significance. Measures of hypoglycaemia remained constant and comparable in both groups. Results for changes in the glycaemic profiles of the patient groups are available in the full report.
Tabulated patient numbers (see full report) for the various groups do not appear to match with the in text data and there were problems ascertaining where patients may have been lost. The authors were contacted regarding this but no response was obtained. It is also uncertain whether the results for change in hyperglycaemia episodes per day are reliable.
The large standard deviations observed (see full report) are a cause for concern as this indicates a large degree of variability within each group. The authors duly acknowledge the high attrition rate as a major limitation, and propose that a more comprehensive run-in period could have selected for the most motivated patients. Additionally they conclude that the short duration does not provide information on the long-term impact of the treatments. Their results suggest patients who incorporate pump therapy with at least 70 per cent sensor component use can expect some additional benefit in glycaemic control. However, benefits in hypoglycaemic profiles were not statistically or clinically different between patients receiving CGM guided treatment (closed-loop) or those with stand-alone pump therapy (Raccah et al 2009).
A UK study described three randomised crossover trials investigating closed-loop and standard continuous subcutaneous insulin infusion. Nineteen type 1 diabetes patients aged 5 to 18 years were recruited of whom 17 were studied overnight for 33 closed-loop and 21 continuous infusion sessions, following. The aim was to determine whether closed-loop insulin delivery could control overnight blood glucose in young people (Hovorka et al 2010) (level II intervention evidence). Main outcomes were time for which plasma glucose was in target range (3.91 to 8.00 mmol/L) or in the hypoglycaemic range (≤ 3.90mmol/L). Secondary outcomes were mean glucose concentration, time for which glucose concentration was higher than 8.0mmol/L, mean rate of insulin infusion and mean plasma insulin concentration. See full report to view the randomised crossover design of the three studies.
On all study occasions, plasma glucose was obtained via sampling cannula at regular intervals to validate the accuracy of sensors used for continuous glucose monitoring. Blood glucose data were not used to calculate or change insulin doses in any groups during any of the protocols. APCam01 used the Guardian Real-Time (Medtronic, Northridge, CA) during closed-loop control and the non-real-time CGMS Gold (Medtronic) during CSII for sensor glucose data. The relative absolute difference between sensor and blood glucose data was 9.2 (4.3-16.7) per cent for the Guardian Real-Time and 7.6 (3.8-14.1) per cent for CGMS. In APCam02 and APCam03, sensor glucose data were obtained using the FreeStyle Navigator (Abbott Diabetes Care, Alameda, CA), for which the relative absolute difference from blood glucose data was 12.7 (5.6-21.9) per cent. The study pump employed in both closed-loop and CSII was the Deltec Cozmo (Smiths Medical, St Paul, MN), which replaced the patients’ regular pumps for the duration of the study periods. The closed-loop system used an adaptive algorithm based on model-predictive control. Real-time glucose sensor data were entered every 15 minutes and the algorithm calculated infusion rates for the insulin pump which was adjusted manually by a nurse. The algorithm was initialised using data on patient weight, total daily insulin dose and basal insulin requirements.


In APCam01, 13 patients aged 5 to 18 years were randomly assigned treatment with overnight closed-loop delivery or standard treatment on two occasions with a one to three week interval. Two weeks prior to study commencement, insulin pump delivery was optimised by analysis of non-real time sensor glucose over 72 hours. On both occasions, patients ate a meal of choice (mean carbohydrates = 87 ± 23g) at 18.00 and were administered 9U (nine units) of prandial insulin calculated in accordance with their insulin-to-carbohydrate ratio and capillary finger-stick glucose value. Closed-loop delivery or standard CSII was between 20.00 and 8.00. On CSII nights, standard insulin pump settings were applied. Results for APCam01 showed that more time was spent in the plasma glucose target range during closed-loop delivery than during CSII, though the difference was not significant. It is necessary to note that for the results of the primary analysis (which used re-sampling) significance was corrected at 0.0125 using a non-parametric permutation test. Results for APCam02 are not reported, since this trial assessed two closed-loop control scenarios, not closed-loop control against an appropriate comparator. In APCam03, ten patients (aged 12 to 18 years) were assigned for two study occasions. The patients exercised on a treadmill for 45 minutes (18.00 – 18.45) at 55 per cent of peak VO2 with a five minute break at the half-way point. Closed-loop or CSII was from 20.00 to 8.00. On CSII nights, patients’ standard pump settings were applied. See full report for summary of results.
Secondary outcomes were derived from analysis of pooled APCam01 and APCam03 data and suggested that closed-loop delivery increased time in the plasma glucose target range and reduced time in the hypoglycaemic range (< 3.90mmol/L). Time in the target range was more apparent after midnight, when the authors suggest closed-loop control became fully effective. Closed-loop delivery performed consistently better than CSII at low and high plasma glucose concentrations. See full report for summary of results.

Importantly, the devices used in this study required manual control by nurses and did not incorporate a wireless data transmission feature that characterises fully automated closed-loop systems, such as those manufactured by Medtronic. The authors indicated that the logical advancement toward such systems could improve closed-loop systems in the future. This logical progression to fully automated systems has in fact occurred, but appears to have been contemporaneous with recent publications detailing work in this area conducted in the preceding years. Though the distinction between fully automated and manually controlled systems in an institutional setting should not differ in terms of basic performance, the advantage of the former is the accessibility for regular use in home and every-day settings. Overall, the primary analysis provided the most relevant and promising data in this study, establishing some elementary evidence for the benefit of closed-loop insulin delivery to control nocturnal hypoglycaemia in children and adolescents.
A randomised multicenter study enrolled 146 type 1 diabetics (aged 12 to 72 years) to compare clinical effectiveness and safety of a closed-loop system with a standard pump and blood glucose monitoring (Hirsch et al 2008) (level III-1 intervention evidence). All patients had an initial HbA1C level ≥ 7.5 per cent. The six month study was conducted with a therapy goal to achieve HbA1C of 7.0 in adolescent subjects (without excessive hypoglycaemia) and less than 7.0 in adults.
Subsequent to initial screening, subjects in both groups wore blinded CGM sensors (Medtronic, Northridge, CA) for 10 days to obtain baseline data. At the first visit, subjects underwent randomisation in a 1:1 ratio to either the sensor group using the Paradigm 722 System, or the control group using self-obtained blood glucose measurements and the Paradigm 715 Insulin Pump. Subjects in the sensor group used real-time sensor features in addition to the Bolus Wizard™. The Bolus Wizard™ was also available to the control group. Both groups received training in intensive management of diabetes, with the sensor group receiving additional training in the use of CGM data. Midway through the study (week 13) and at study conclusion (week 26) control subjects wore two subcutaneous blinded CGM sensors consecutively (two 3-day periods). HbA1C values were collected on each occasion and insulin pump data were downloaded. The primary end-point was average change in HbA1C measured from baseline to study end. Predetermined secondary end-points included percentage of subjects achieving HbA1C level of 7.0, area under the curve (AUC) for hypo- and hyperglycaemia, incidence/frequency of hypo- and hyperglycaemic events, and safety. Data were obtained for 138 subjects who completed the study. See full report for change in HbA1C results.
Change in HbA1C levels from baseline was significant for both groups (p < 0.001), however, the difference between groups was not statistically significant (p=0.371). It has been reported elsewhere (Raccah et al 2009) that an absolute difference in HbA1C of ≥ 0.5, the magnitude of difference noted in this study, can be considered as clinically important. This was independently substantiated by personal communication with a diabetes specialist (University of Adelaide). It should be noted that the effect of sensor use compliance was marginally significant (p=0.046) for HbA1C outcomes. Each 10 per cent increase in compliance was associated with a 41 per cent increase in the probability of an absolute HbA1C reduction of 0.5.
Twenty (30.8%) of sensor subjects achieved HbA1C levels of seven per cent by midway through the study, while eight (11.1%) controls achieved this target (p=0.007). However, subjects remaining within target at study end did not show a statistically significant difference between groups; 16 (24.2%) in the sensor group versus 12 (19.4%) in the control group. The number of sensor subjects who reached seven per cent HbA1C at either midway or study end was greater (p=0.003) than the number of controls.

For hyperglycaemia (> 180mg/dL) area under curve analysis, both study groups experienced a significant decrease in mean values at study end (control group, -9.7 ± 16.5mg/dL/min; sensor group, -11.3 ± 19.3mg/dL/min, p < 0.0001). However, the difference in change from baseline between groups was not significant (2.8mg/dL/min, p=0.291). Mean hyperglycaemic events per patient per day at baseline for control and sensor subjects were 2.667 ± 0.649 and 2.635 ± 0.635, respectively. Comparison within groups showed small changes in the number of hyperglycaemic events at study end (controls, 2.657 ± 0.805, p=0.77; sensor group 2.869 ± 0.913, p=0.03). Change between groups was not significant. For hypoglycaemia (< 70mg/dL) area under curve, there was no mean change among the sensor group, but mean values in the control group increased significantly (p=0.001). Change from baseline between the groups was statistically significant (least square mean ± SE = 0.465 ± 0.121mg/dL/min, p < 0.0002). Mean hypoglycaemic events per patient per day at baseline for control and sensor subjects were 0.835 ± 0.728 and 0.838 ± 0.725, respectively. Hypoglycaemic events in control subjects increased significantly to 1.166 ± 0.744 (p=0.0008) at study end compared to sensor subjects (0.883 ± 0.756, p=0.62). There was no significant difference between groups.
Fourteen severe hypoglycaemic events occurred; 11 were in the sensor group, six of which occurred while the sensor was not being worn/used. For the remaining five events, a Safety Review Board established that subjects ignored alerts associated with low sensor readings, tended to inject multiple insulin boluses without using the Bolus Wizard (causing insulin-stacking), or ‘blind bolused’ (based treatment decisions on sensor readings only, without confirmatory blood glucose test). In terms of other safety considerations, one patient twice experienced skin abscess at the insulin infusion site and one patient (sensor group) developed diabetic ketoacidosis.
Overall, these data suggest that improved glycaemic control is possible with the use of a closed-loop system, without increasing time spent in hypoglycaemia. However, compliance is highlighted as a major factor in the success or failure of closed-loop systems, and the authors rightly conclude that patient selection for CGM guided pump therapy needs to carefully assess willingness and ability to use the technology appropriately.
Conflict of interest issues were identified in this study, a number of the authors having received honoraria and grant support from several manufacturers (including Medtronic) and pharmaceuticals companies (Hirsh et al 2008).
The majority of studies identified have included clinician-led review and adjustments to insulin delivery when using closed-loop systems. Since such protocols may impact on accrued glycaemic improvements, an Australian study (n=62) investigated whether type 1 diabetics can adapt to and employ real-time CGM to increase their own glycaemic control (O'Connell et al 2009) (level II intervention evidence). The effect of patient-led closed-loop control was compared with standard insulin pump therapy.
The RCT was conducted across five Australian centres, and recruited diabetics aged 13 to 40 years in age- and sex-matched pairs. When an individual consented to participate, the next suitable age- and sex-matched person was approached to complete the pair. Recruited pairs were then randomised by computer-generated schedule to either self-led closed-loop (intervention) or open-loop (standard pump) therapy and studied over three months. All pump and sensor equipment was supplied by Medtronic Australia. Time spent in the target glycaemic range of 4.0 to 10mmol/L was the primary outcome. Secondarily, differences in HbA1C, proportion of time spent in hypoglycaemia (≤ 3.9mmol/L) and hyperglycaemia (≥ 10.1 mmol/L), and glycaemic variability were assessed.
At baseline and end-of-study, all participants underwent six days of blinded CGM, using the CGMS Gold (Medtronic), and HbA1C measurements. Participants in the intervention group received standard instruction on using CGM enabled pumps from the same instructor across all sites. Systems were calibrated using capillary blood glucose and alarm features were set to alert the user at sensor glucose levels less than 4.5 and greater than 12.0mmol/L. Subjects were finally instructed to perform confirmatory blood glucose measurements if real-time data suggested administration of therapeutic action (e.g. correction bolus of insulin).
Seven participants withdrew from the study; five from the intervention group and two controls. End-of-study data were therefore available for 26 out of 31 participants in the intervention arm and for 29 out of 31 controls. Median time spent using the sensor component in the intervention group was 62.5 per cent (range 17.7% to 93.8%) during the three-month study period. Eleven out of 25 participants were compliant with the protocol requirement of ≥ 70 per cent sensor use. See full report for glycaemic outcomes for both groups (compliant and non-compliant patients).
Overall, HbA1C reduction was achieved by 16 out of 26 (64%) participants who used closed-loop management, compared with only five out of 29 (17%) participants who used standard pumps. At study-end HbA1C levels below 7.0 per cent were achieved more often among the intervention group compared to controls (56% versus 17%, respectively; p=0.004). End-of-study HbA1C levels were lower (6.7%) among patients with sensor use of 70 per cent or more, while those not compliant with this level of usage had significantly worse outcomes (HbA1C = 7.4%), p=0.04. No episodes of severe hypoglycaemia or diabetic ketoacidosis occurred.
The authors note that the nature of the intervention in their study precluded participant blinding and this is a potential source of ascertainment bias. Individuals with suboptimal diabetes control were excluded; therefore the findings may only be applicable within patient groups who are already well controlled on insulin pump therapy. Even among these motivated groups, this study has revealed that compliance may remain an obstacle in the uptake of patient-led closed-loop devices. Nonetheless, it is anticipated that continued technological developments, particularly in relation to better algorithms will overcome limitations related to current behavioural responses still required for optimal effectiveness of closed-loop devices. No differences in time spent in hypoglycaemia were observed between the study groups, showing that although blood glucose was better overall due to closed-loop management, neither treatment was more effective in avoiding hypoglycaemia.
Conflicts of interest were noted for a number of the authors, having variously obtained honoraria and education, research and/or travel support (O’Connell et al 2009).
Results of a US study showed positive effects for closed-loop model predictive control, but due to small sample size (n = 8), these are not discussed in detail. The study indicated closed-loop control was at least as effective as patient-led open-loop control in the management of post-prandial rises in blood glucose. Of more interest, closed-loop demonstrated a clear advantage over open-loop in the prevention of overnight hypoglycaemia (Clarke et al 2009).

Economic evaluation:
 
Ongoing research:
None known.
Ongoing or planned HTA:
2012 HealthPACT Assessment:
HeathPACT recognised that although there was limited evidence available in respect to closed-looped insulin delivery systems, that this technology has the potential to have a great impact on Type I diabetics as well as the health system. Therefore it has recommended that a New and Emerging Health Technology Report on insulin replacement therapies, including stem cell and closed-loop technologies, be commissioned in 24 months.

2010 HealthPACT Assessment
The modest levels of evidence demonstrate the potential for further development and accessibility of closed-loop insulin delivery. However, HealthPACT have concerns about the reliability of the sensor components and therefore wish to monitor the technology, which will be reviewed in 24 months time.
Web link:
http://www.health.qld.gov.au/healthpact/
References and sources:
2012 and 2010 References
1. ECRI (2012). Artificial pancreas (closed-loop system) for treating diabetes requiring exogenous insulin, ECRI Institute Available from:
2. Kumareswaran, K, Evans, ML&Hovorka, R (2012). 'Closed-loop insulin delivery: towards improved diabetes care'. Discov Med, 13 (69), 159-70.
3. Cobelli, C, Renard, E et al (2012). 'Pilot studies of wearable outpatient artificial pancreas in type 1 diabetes'. Diabetes Care, 35 (9), e65-7.
4. Weinzimer, SA (2012). 'Closed-loop artificial pancreas: current studies and promise for the future'. Curr Opin Endocrinol Diabetes Obes, 19 (2), 88-92.
5. Hirsch, IB, Abelseth, J et al (2008). 'Sensor-augmented insulin pump therapy: results of the first randomized treat-to-target study'. J Diabetes Sci Technol, 10 (5), 377-83.
6. O'Connell, MA, Donath, S et al (2009). 'Glycaemic impact of patient-led use of sensor-guided pump therapy in type 1 diabetes: a randomised controlled trial'. Diabetologia, 52 (7), 1250-7.
7. Kumareswaran, K, Elleri, D et al (2011). 'Meta-analysis of overnight closed-loop randomized studies in children and adults with type 1 diabetes: the Cambridge cohort'. J Diabetes Sci Technol, 5 (6), 1352-62.
8. Kovatchev, B, Cobelli, C et al (2010). 'Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results'. J Diabetes Sci Technol, 4 (6), 1374-81.
9. Hovorka, R, Kumareswaran, K et al (2011). 'Overnight closed loop insulin delivery (artificial pancreas) in adults with type 1 diabetes: crossover randomised controlled studies'. BMJ, 342, d1855.
10. Murphy, HR, Kumareswaran, K et al (2011). 'Safety and efficacy of 24-h closed-loop insulin delivery in well-controlled pregnant women with type 1 diabetes: a randomized crossover case series'. Diabetes Care, 34 (12), 2527-9.
11. Breton, M, Farret, A et al (2012). 'Fully Integrated Artificial Pancreas in Type 1 Diabetes: Modular Closed-Loop Glucose Control Maintains Near Normoglycemia'. Diabetes, 61 (9), 2230-7.
12. Jenkins, AJ, Krishnamurthy, B et al (2010). 'Evaluation of an algorithm to guide patients with type 1 diabetes treated with continuous subcutaneous insulin infusion on how to respond to real-time continuous glucose levels: a randomized controlled trial'. Diabetes Care, 33 (6), 1242-8.
13. O'Grady, MJ, Retterath, AJ et al (2012). 'The Use of an Automated, Portable, Glucose Control System for Overnight Glucose Control in Adolescents and Young Adults With Type 1 Diabetes'. Diabetes Care.
14. Garg, S, Brazg, RL et al (2012). 'Reduction in duration of hypoglycemia by automatic suspension of insulin delivery: the in-clinic ASPIRE study'. Diabetes Technol Ther, 14 (3), 205-9.
15. Choudhary, P, Shin, J et al (2011). 'Insulin pump therapy with automated insulin suspension in response to hypoglycemia: reduction in nocturnal hypoglycemia in those at greatest risk'. Diabetes Care, 34 (9), 2023-5.
16. Ly, TT, Nicholas, JA et al (2012). 'Analysis of glucose responses to automated insulin suspension with sensor-augmented pump therapy'. Diabetes Care, 35 (7), 1462-5.
17. Castle, JR, Engle, JM et al (2010). 'Novel use of glucagon in a closed-loop system for prevention of hypoglycemia in type 1 diabetes'. Diabetes Care, 33 (6), 1282-7.
18. El-Khatib, FH, Russell, SJ et al (2010). 'A bihormonal closed-loop artificial pancreas for type 1 diabetes'. Sci Transl Med, 2 (27), 27ra.
19. Renard, E, Place, J et al (2010). 'Closed-loop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas'. Diabetes Care, 33 (1), 121-7.
20. Elleri, D, Acerini, CL et al (2010). 'Parental attitudes towards overnight closed-loop glucose control in children with type 1 diabetes'. Diabetes Technol Ther, 12 (1), 35-9.
21. Richter, B, Bergerhoff, K et al (2007). Cochrane Metabolic and Endocrine Disorders Group. [Internet]. The Cochrane Library. Available from: http://www.mrw.interscience.wiley.com/cochrane/clabout/articles/ENDOC/frame.html [Accessed 9th February 2010].
22. Catanzariti, L, Faulks, K&Waters, AM (2008). Incidence of Type I diabetes in Australia 2000-2006: first results, Australian Institute for Health and Welfare, Canberra Available from: http://www.aihw.gov.au/publications/cvd/iot1dia00-06-fr/iot1dia00-06-fr.pdf.
23. Pieris-Caldwell, I, Templeton, M et al (2008). Diabetes: Australian facts 2008, Australian Institute for Health and Welfare, Canberra Available from: http://www.aihw.gov.au/publications/cvd/daf08/daf08.pdf.
24. Health Funding Authority (2000). Diabetes 2000, Health Funding Authority, Wellington Available from: http://www.moh.govt.nz/moh.nsf/7004be0c19a98f8a4c25692e007bf833/4735077ed3fd9b56cc256a41000975ca/$FILE/Diabetes2000.PDF.
25. Department of Health and Ageing (2010). Prostheses List. Available from: http://www.health.gov.au/internet/main/publishing.nsf/Content/prostheses-list-excel.htm [Accessed 21st April 2010].
26. Medtronic Australasia (2010). MiniMed Paradigm™ Veo™ System: Factsheet. Available from: http://www.minimed.com.au/downloads/Paradigm%20Veo%20Factsheet.pdf [Accessed 12 May 2010].
27. Cohen, N, Minshall, ME et al (2007). 'Continuous subcutaneous insulin infusion versus multiple daily injections of insulin: economic comparison in adult and adolescent type 1 diabetes mellitus in Australia'. Pharmacoeconomics, 25 (10), 881-97.
28. Jacobsen, IB, Henriksen, JE et al (2009). 'Evidence-based insulin treatment in type 1 diabetes mellitus'. Diabetes Res Clin Pract, 86(1):1-10 (1), 1-10.
29. Raccah, D, Sulmont, V et al (2009). 'Incremental value of continuous glucose monitoring when starting pump therapy in patients with poorly controlled type 1 diabetes: the RealTrend study'. Diabetes Care, 32 (12), 2245-50.
30. American Diabetes Association (2009). 'Standards of medical care in diabetes--2009'. Diabetes Care, 32, S13 - S61.
31. Hovorka, R, Allen, JM et al (2010). 'Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial'. Lancet, 375 (9716), 743-51.
32. Clarke, WL, Anderson, S et al (2009). 'Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience'. J Diabetes Sci Technol, 3 (5), 1031-8.
33. Hovorka, R (2006). 'Continuous glucose monitoring and closed-loop systems'. Diabet Med, 23 (1), 1-12.

2010 References
American Diabetes Association (2009). 'Standards of medical care in diabetes--2009', Diabetes Care, 32, S13 - S61.
Catanzariti, L., Faulks, K. & Waters, A. M. (2008). Incidence of Type 1 diabetes in Australia 2000-2006: first results, Australian Institute for Health and Welfare, Canberra.
Clarke, W. L., Anderson, S. et al (2009). 'Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience', J Diabetes Sci Technol, 3 (5), 1031-1038.
Cohen, N., Minshall, M. E. et al (2007). 'Continuous subcutaneous insulin infusion versus multiple daily injections of insulin: economic comparison in adult and adolescent type 1 diabetes mellitus in Australia', Pharmacoeconomics, 25 (10), 881-897.
Department of Health and Ageing (2010). Prostheses List [Internet]. Available from: http://www.health.gov.au/internet/main/publishing.nsf/Content/prostheses-list-excel.htm [Accessed 21st April].
El-Khatib, F. H., Russell, S. J. et al (2010). 'A bihormonal closed-loop artificial pancreas for type 1 diabetes', Sci Transl Med, 2 (27), 27ra27.
Health Funding Authority (2000). Diabetes 2000, Health Funding Authority, Wellington.
Hirsch, I. B., Abelseth, J. et al (2008). 'Sensor-augmented insulin pump therapy: results of the first randomized treat-to-target study', J Diabetes Sci Technol, 10 (5), 377-383.
Hovorka, R. (2006). 'Continuous glucose monitoring and closed-loop systems', Diabet Med, 23 (1), 1-12.
Hovorka, R., Allen, J. M. et al (2010). 'Manual closed-loop insulin delivery in children and adolescents with type 1 diabetes: a phase 2 randomised crossover trial', Lancet, 375 (9716), 743-751.
Medtronic Australasia (2010). MiniMed Paradigm™ Veo™ System: Factsheet [Internet]. Available from: http://www.minimed.com.au/downloads/Paradigm%20Veo%20Factsheet.pdf [Accessed 12 May].
Jacobsen, I. B., Henriksen, J. E. et al (2009). 'Evidence-based insulin treatment in type 1 diabetes mellitus', Diabetes Res Clin Pract, 86(1):1-10 (1), 1-10.
O'Connell, M. A., Donath, S. et al (2009). 'Glycaemic impact of patient-led use of sensor-guided pump therapy in type 1 diabetes: a randomised controlled trial', Diabetologia, 52 (7), 1250-1257.
Pieris-Caldwell, I., Templeton, M. et al (2008). Diabetes: Australian facts 2008, Australian Institute for Health and Welfare, Canberra.
Raccah, D., Sulmont, V. et al (2009). 'Incremental value of continuous glucose monitoring when starting pump therapy in patients with poorly controlled type 1 diabetes: the RealTrend study', Diabetes Care, 32 (12), 2245-2250.
Renard, E., Place, J. et al (2010). 'Closed-loop insulin delivery using a subcutaneous glucose sensor and intraperitoneal insulin delivery: feasibility study testing a new model for the artificial pancreas', Diabetes Care, 33 (1), 121-127.
Richter, B., Bergerhoff, K. et al (2007). Cochrane Metabolic and Endocrine Disorders Group [Internet]. The Cochrane Library. Available from: http://www.mrw.interscience.wiley.com/cochrane/clabout/articles/ENDOC/frame.html [Accessed 9th February].
Notes:
2012 Other Issues
Recently active research is being conducted on a low glucose suspension (LGS) system to automatically stop insulin delivery when predetermined glucose threshold is reached, representing the step further toward the goal of developing an automated insulin delivery system to treat diabetes, especially for reducing nocturnal hypoglycaemia. The Paradigm™ Veo™ sensor augmented insulin pump system (Medtronic MiniMed, Inc.) is the first insulin pump to have such LGS feature. Pump suspension lasts for 2 hours in the absence of user intervention, but the pump can be manually restarted at any time. The LGS feature is optional, and the pump functions normally if the feature is switched off.14 Available results have shown that automatic suspension of insulin delivery was safe and significantly reduced the duration and severity of hypoglycaemia without causing rebound hyperglycaemia.14-16 The detailed results are not presented here as this is only an add-on feature of the CLS.
Apart from examining the efficiency of CLS for overnight control of glycaemia and during and after exercise, a number of studies have also investigated performance of different type of CLS regarding the route of insulin admission or hormones infused. One example is bi-hormonal (insulin and glucagon) CLS based on that glucagon rapidly raises circulating glucose levels within minutes via glycogenolysis, even when given subcutaneously, countering the effect of insulin.17, 18 Although a system with the capability of glucagon delivery would mandate the need for a second hormone chamber with additional algorithm to determine glucagon delivery rates, it may lead to substantially less hypoglycaemia. In addition, closed loop with intraperitoneal insulin delivery was also an area of investigation.19 The results were not presented here as these feasibility studies are generally small and do not compared the effects of the new system with that of the CSII.
From the technology point of view, the challenges of CLS software component, which could have fatal consequences, pose major barrier for regulatory approval. Although administration of a CLS is not labour intensive, the use of the technology will present many training issues for clinicians and patients. An interdisciplinary diabetic management team trained in the use and calibration of the system to meet the needs of different type of patients, such as paediatric, pregnant and patients with co-morbidities. Clinical protocols will need to be developed to monitor patients using CLS to address any problems immediately to prevent potential hazards. In addition, the team will be responsible for patient education on the appropriate use and monitoring of a CLS and for close follow-up of patients using CLS. Additional staff may be required, if increased number of patients receive CLS, due to additional time to educate patients, frequent patient visits and monitoring time.
From the patients’ perspective, it has been suggested that the CLS will not be suitable for every patient with diabetes who requires exogenous insulin. Patients should have some experience operating sensor-augmented pumps and for-six weeks of training should be provided for those without prior experience. Candidates will need to be motivated and capable of learning how to use the pumps and self-monitoring how well the CLS is functioning.1 As nocturnal hypoglycaemia is a particular concern for caregivers in children with type 1 diabetes, a study has confirmed that the development of a CLS is welcomed and trusted to help them achieve improved blood glucose control overnight without the risk of hypoglycaemia.20


2010
There is evidence to suggest that sensor-guided subcutaneous insulin delivery via an external pump can experience delays and variability in absorption (Hovorka 2006). This has led some investigators to consider the use of implantable intraperitoneal closed-loop devices. To some extent, these have demonstrated fast insulin action and low basal plasma insulin levels. The claimed benefit is tight glucose control and low incidence of hypoglycaemic events (Renard et al 2010).
A case-series in the US has reported the results of experiments with a bi-hormonal closed-loop system at an early stage of development (El-Khatib et al 2010). Bi-hormonal systems differ from other closed-loop equipment in the ability to deliver glucagon in addition to insulin, thus potentiating a broader scope for glycaemic control via processes not dissimilar to the bi-hormonal secretions of a normal pancreas. The appeal in using the two hormones is the ability of glucagon to counteract the effects of insulin and increase glucose production by the liver, thereby stabilising post-prandial glucose concentrations and preventing hypoglycaemia. It is re-emphasised, however, that the equipment used in these experiments appeared to be at prototype level. The protocol required two intravenous catheters for sampling of blood glucose, an insulin analogue and glucagon. Additionally, three pumps were connected to each patient; one for glucagon infusion, one for low resolution insulin dosing, and one for high resolution insulin dosing (insulin diluted to achieve increments of 0.005U, below the pump’s minimum bolus size of 0.05U). Since these requirements are cumbersome even in an institutional setting, considerable development of bi-hormonal closed-loop systems will be necessary if such therapy is to reduce the risk of hypoglycaemia in every-day settings (El-Khatib et al 2010).