Clinical performance of three bolus calculators in subjects with type 1 diabetes mellitus: a head-to-head-to-head comparison

Comparison of three insulin bolus calculators to increase time in range of glycemia in a group of poorly controlled adults Type 1 diabetes in a Brazilian public health service

BACKGROUND

A main factor contributing to insufficient glycemic control, during basal/bolus insulin therapy, is poor self-management bolus. Insulin bolus administration frequency is strongly associated with glycated hemoglobin (A1c) in Type 1 Diabetes (T1D). In the present study, we analyzed the performance of two-bolus calculator's software that could be accessible to T1D patients from a Public Health Service to improve glycemic time in range (TIR) and A1c.

METHODS

This prospective, controlled, randomized, parallel intervention clinical trial was carried out with 111 T1D participants on basal/bolus therapy [multiple daily insulin injections (MDI) or subcutaneous infusion pump (CSII)] with basal A1c ≥ 8.5% for 24 weeks. Patients were divided into 3 groups: 2 interventions: COMBO^® (bolus calculator) and GLIC (mobile application) and 1 control (CSII group). Anthropometrics and metabolic variables were assessed on basal, 3 and 6 months of follow-up.

RESULTS

TIR was increased in 9.42% in COMBO group (29 ± 12% to 38.9 ± 12.7%; p < 0.001) in 8.39% in the GLIC® group (28 ± 15% to 36.6 ± 15.1%; p < 0.001) while remained stable in CSII group (40 ± 11% to 39.3 ± 10.3%). A1c decrease in 1.08% (p < 0.001), 0.64% (p < 0.001) and 0.38% (p = 0.01) at 6 months in relation to basal in the COMBO, GLIC and CSII respectively. Daily basal insulin dose was reduced by 8.8% (p = 0.01) in the COMBO group.

CONCLUSION

The COMBO and a mobile applicative (GLIC) bolus calculator had a similar and a good performance to optimize the intensive insulin treatment of T1D in the public health system with increase in the TIR and reduction in A1C without increase hypoglycemia prevalence.

The Evolution of Insulin Administration in Type 1 Diabetes

Insulin has been utilized in the treatment of type 1 diabetes (T1D) for 100 years. While there is still no cure for T1D, insulin administration has undergone a remarkable evolution which has contributed to improvements in quality of life and life expectancy in individuals with T1D. The advent of faster-acting and longer-acting insulins allowed for the implementation of insulin regimens more closely resembling normal insulin physiology. These improvements afforded better glycemic control, which is crucial for limiting microvascular complications and improving T1D outcomes. Suspension of insulin delivery in response to actual and forecasted hypoglycemia has improved quality of life and mitigated hypoglycemia without compromising glycemic control. Advances in continuous glucose monitoring (CGM) and insulin pumps, efforts to model glucose and insulin kinetics, and the application of control theory to T1D have made the automation of insulin delivery a reality. This review will summarize the past, present, and future of insulin administration in T1D.

Comparison of Insulin Pump Bolus Calculators Reveals Wide Variation in Dose Recommendations

BACKGROUND

The introduction of insulin pumps with bolus calculators (BCs) has improved glycemic outcomes and quality of life for those with type 1 diabetes. Despite the increased reliance on BCs, the formulas used to derive recommended boluses are not standardized. Our objective was to examine whether recommendations from different pump BCs vary significantly for identical clinical scenarios.

METHODS

Three commercially available insulin pump BCs were programmed with identical settings and then presented with combinations of blood glucose (BG) and carbohydrates (CHOs) to generate a 4-unit bolus. At one- and two-hour time points, while there was insulin-on-board (IOB) present, we simulated various BG and CHO scenarios in order to compare BC-recommended doses.

RESULTS

Differences in suggested doses were noted between BCs, as well as within the same brand. The greatest variation was apparent when BG was below target. Doses suggested by one BC varied depending on whether the IOB resulted from a previous dose given for BG or CHO, while the other two BCs adjusted for total IOB regardless of the source.

CONCLUSIONS

In this simulation study, there were large differences in recommended doses between BCs due to the unique way each manufacturer incorporates IOB into their formulas as well as the pharmacokinetics used to derive the IOB amount. Providers should be aware that identical pump settings will result in a different dose recommendation for each pump brand and advise patients accordingly.

Intelligent Data-Driven Model for Diabetes Diurnal Patterns Analysis

In type 1 diabetes, diurnal activity routines are influential factors in insulin dose calculations. Bolus advisors have been developed to more accurately suggest doses of meal-related insulin based on carbohydrate intake, according to pre-set insulin to carbohydrate levels and insulin sensitivity factors. These parameters can be varied according to the time of day and their optimal setting relies on identifying the daily time periods of routines accurately. The main issues with reporting and adjustments of daily activity routines are the reliance on self-reporting which is prone to inaccuracy and within bolus calculators, the keeping of default settings for daily time periods, such as within insulin pumps, glucose meters, and mobile applications. Moreover, daily routines are subject to change over periods of time which could go unnoticed. Hence, forgetting to change the daily time periods in the bolus calculator could contribute to sub-optimal self-management. In this paper, these issues are addressed by proposing a data-driven model for identification of diabetes diurnal patterns based on self-monitoring data. The model uses time-series clustering to achieve a meaningful separation of the patterns which is then used to identify the daily time periods and to advise of any time changes required. Further improvements in bolus advisor settings are proposed to include week/weekend or even modifiable daily time settings. The proposed model provides a quick, granular, more accurate, and personalized daily time setting profile while providing a more contextual perspective to glycemic pattern identification to both patients and clinicians.

A Retrospective Review of the Clinical Characteristics and Blood Glucose Data from Cellnovo System Users using Data Collected from the Cellnovo Online Platform

Technological advances have led to innovative insulin delivery systems for patients with type 1 diabetes mellitus. In particular, the combination of miniature engineering and software algorithms contained in continuous subcutaneous insulin infusion (CSII) system pumps provide the user and the healthcare practitioner with an opportunity to review and adjust blood glucose (BG) levels according to system feedback, and to modify or programme their regimen according to their needs. While CSII pumps record a number of data parameters such as BG level, carbohydrate intake, activity and insulin delivered, these data are generally ‘locked in’ and can only be accessed by uploading to a cloud-based system, thus information is not contemporaneous. The Cellnovo Diabetes Management System (Cellnovo, Bridgend, UK) allows data to be transmitted securely and wirelessly in real time to a secure server, which is then retrieved by an online platform, the Cellnovo Online platform, enabling continuous access by the user and by clinicians. In this article, the authors describe a retrospective review of the patient data automatically uploaded to the Cellnovo Online platform. Baseline clinical and demographic characteristics collected at the start of pump therapy are shown for all patients, and BG data from a sub-cohort of patients who have been using the system for at least 6 months and who take and record an average of three BG level tests per day are presented to demonstrate glycaemic data over time.

Comparison of different insulin pump makes under routine care conditions in adults with Type 1 diabetes

AIMS

To compare long-term HbA_1c changes associated with different insulin pumps during routine care in a large cohort of adults with Type 1 diabetes representative of other clinic populations.

METHODS

Observational, retrospective study of 508 individuals starting pump therapy between 1999 and 2014 (mean age, 40 years; 55% women; diabetes duration, 20 years; 94% Type 1 diabetes; median follow-up, 3.7 years). Mixed linear models compared covariate-adjusted HbA_1c changes associated with different pump makes.

RESULTS

The pumps compared were: 50% Medtronic, 24% Omnipod, 14% Roche and 12% Animas. Overall HbA_1c levels improved and improvements were maintained during a follow-up extending to 10 years (HbA_1c : pre-continuous subcutaneous insulin infusion (pre-CSII) vs. 12 months post CSII, 71 (61, 82) vs. 66 (56, 74) mmol/mol; 8.7 (7.7, 9.6) vs. 8.2 (7.3, 8.9)%; P < 0.0001). The percentage of individuals with HbA_1c ≥ 64 mmol/mol (8.0%) reduced from a pre-CSII level of 68% to 55%. After adjusting for baseline confounders, there were no between-pump differences in HbA_1c lowering (P = 0.44), including a comparison of patch pumps with traditional catheter pumps (P = 0.63). There were no significant (P < 0.05) between-pump differences in HbA_1c lowering in pre-specified subgroups stratified by pre-pump HbA_1c , age or diabetes duration. HbA_1c lowering was positively related to baseline HbA_1c (P < 0.001) and diabetes duration (P = 0.017), and negatively related to the number of years of CSII use (P = 0.024).

CONCLUSIONS

Under routine care conditions, there were no covariate-adjusted differences in HbA_1c lowering when comparing different pump makes, including a comparison of patch pumps vs. traditional catheter pumps. Therefore, the choice of CSII make should not be influenced by the desired degree of HbA_1c lowering.

Frequent use of an automated bolus advisor improves glycemic control in pediatric patients treated with insulin pump therapy: results of the Bolus Advisor Benefit Evaluation (BABE) study

BACKGROUND

The relationship between frequency and sustained bolus advisor (BA) use and glycemic improvement has not been well characterized in pediatric populations.

OBJECTIVE

The objective of this study is to assess the impact of frequent and persistent BA use on glycemic control among pediatric type 1 diabetes patients.

METHODS

In this 6-month, single-center, retrospective cohort study, 104 children [61 girls, mean age: 12.7 yr, mean HbA1c 8.0 (1.6)% [64 (17.5) mmol/mol]], treated with the Accu-Chek Aviva Combo insulin pump, were observed. Frequency of BA use, HbA1c, hypoglycemia (<70 mg/dL), therapy changes, mean blood glucose, and glycemic variability (standard deviation) was assessed at baseline and month 6. Sub-analyses of the adolescent patient use (12 months) and longitudinal use (24 months) were also conducted.

RESULTS

Seventy-one patients reported high frequency (HF) device use (≥50%); 33 reported low frequency (LF) use (<50%) during the study. HF users achieved lower mean (SE) HbA1c levels than LF users: 7.5 (0.1)% [59 (1.1) mmol/mol] vs. 8.0 (0.2)% [64 (2.2) mmol/mol], p = 0.0252. No between-group differences in the percentage of hypoglycemia values were seen at 6 months. HF users showed less glycemic variability (84.0 vs. 94.7, p = 0.0045) than LF users. More HF patients reached HbA1c target of <7.5 at 6 months 66.2% (+16.9) vs. 27.3% (-9.1), p = 0.0056. Similar HbA1c results were seen in adolescents and BA users at 24 months.

CONCLUSION

Frequent use of the Accu-Chek Aviva Combo insulin pump BA feature was associated with improved and sustained glycemic control with no increase in hypoglycemia in this pediatric population.

Unknown Safety and Efficacy of Smartphone Bolus Calculator Apps Puts Patients at Risk for Severe Adverse Outcomes

Manual calculation of bolus insulin dosages can be challenging for individuals treated with multiple daily insulin injections (MDI) therapy. Automated bolus calculator capability has recently been made available via enhanced blood glucose meters and smartphone apps. Use of this technology has been shown to improve glycemic control and reduce glycemic variability without changing hypoglycemia; however, the clinical utility of app-based bolus calculators has not been demonstrated. Moreover, recent evidence challenges the safety and efficacy of these smartphone apps. Although the ability to automatically calculate bolus insulin dosages addresses a critical need of MDI-treated individuals, this technology raises concerns about efficacy of treatment and the protection of patient safety. This article discusses key issues and considerations associated with automated bolus calculator use.

8th Annual Symposium on Self-Monitoring of Blood Glucose (SMBG): April 16-18, 2015, Republic of Malta

International experts in the fields of diabetes, diabetes technology, endocrinology, mobile health, sport science, and regulatory issues gathered for the 8(th) Annual Symposium on Self-Monitoring of Blood Glucose (SMBG) with a focus on personalized diabetes management. The aim of this meeting was to facilitate new collaborations and research projects to improve the lives of people with diabetes. The 2015 meeting comprised a comprehensive scientific program, parallel interactive workshops, and two keynote lectures.

Method for automatic adjustment of an insulin bolus calculator: in silico robustness evaluation under intra-day variability

BACKGROUND AND OBJECTIVE

Insulin bolus calculators are simple decision support software tools incorporated in most commercially available insulin pumps and some capillary blood glucose meters. Although their clinical benefit has been demonstrated, their utilisation has not been widespread and their performance remains suboptimal, mainly because of their lack of flexibility and adaptability. One of the difficulties that people with diabetes, clinicians and carers face when using bolus calculators is having to set parameters and adjust them on a regular basis according to changes in insulin requirements. In this work, we propose a novel method that aims to automatically adjust the parameters of a bolus calculator. Periodic usage of a continuous glucose monitoring device is required for this purpose.

METHODS

To test the proposed method, an in silico evaluation under real-life conditions was carried out using the FDA-accepted Type 1 diabetes mellitus (T1DM) UVa/Padova simulator. Since the T1DM simulator does not incorporate intra-subject variability and uncertainty, a set of modifications were introduced to emulate them. Ten adult and ten adolescent virtual subjects were assessed over a 3-month scenario with realistic meal variability. The glycaemic metrics: mean blood glucose; percentage time in target; percentage time in hypoglycaemia; risk index, low blood glucose index; and blood glucose standard deviation, were employed for evaluation purposes. A t-test statistical analysis was carried out to evaluate the benefit of the presented algorithm against a bolus calculator without automatic adjustment.

RESULTS

The proposed method statistically improved (p<0.05) all glycemic metrics evaluating hypoglycaemia on both virtual cohorts: percentage time in hypoglycaemia (i.e. BG<70 mg/dl) (adults: 2.7±4.0 vs. 0.4±0.7, p=0.03; adolescents: 7.1±7.4 vs. 1.3±2.4, p=0.02) and low blood glucose index (LBGI) (adults: 1.1±1.3 vs. 0.3±0.2, p=0.002; adolescents: 2.0±2.19 vs. 0.7±1.4, p=0.05). A statistically significant improvement was also observed on the blood glucose standard deviation (BG SD mg/dL) (adults: 33.5±13.7 vs. 29.2±8.3, p=0.01; adolescents: 63.7±22.7 vs. 44.9±23.9, p=0.01). Apart from a small increase in mean blood glucose on the adult cohort (129.9±11.9 vs. 133.9±11.6, p=0.03), the rest of the evaluated metrics, despite showing an improvement trend, did not experience a statistically significant change.

CONCLUSIONS

A novel method for automatically adjusting the parameters of a bolus calculator has the potential to improve glycemic control in T1DM diabetes management.

Safe and Efficacious Use of Automated Bolus Advisors in Individuals Treated With Multiple Daily Insulin Injection (MDI) Therapy: Lessons Learned From the Automated Bolus Advisor Control and Usability Study (ABACUS)

Numerous studies have shown that use of integrated automated bolus advisors (BAs) provides significant benefits to individuals using insulin pump devices, including improved glycemic control and greater treatment satisfaction. Within the past few years, BA devices have been developed specifically for individuals treated with multiple daily insulin injection (MDI) therapy; however, many clinicians who treat these individuals may be unfamiliar with insulin pump therapy and, thus, BA use. Findings from the Automated Bolus Advisor Control and Usability Study (ABACUS) revealed that BA use can be efficacious and clinically meaningful in MDI therapy, and that most patients are willing and able to use this technology appropriately when adequate clinical support is provided. The purpose of this article is to review key learnings from ABACUS and provide practical advice for initiating BA use and monitoring therapy.

Clinical evaluation of the use of a multifunctional remotely controlled insulin pump: multicenter observational study

Current insulin pumps now feature advanced functions for calculating insulin dosages, delivering insulin and analyzing data, however, the perceived usefulness of these functions in clinical settings has not been well studied. We assessed the use and patient perceptions of an insulin delivery system (Accu-Chek® Combo, Roche Diagnostics, Mannheim, Germany) that combines an insulin pump and a handheld multifunctional blood glucose meter with integrated remote control functions. This prospective, observational, multicenter study enrolled 74 type 1 diabetes patients within 13 weeks after starting use of the pump system. At 4 to 24 weeks, investigators collected usage data from the latest 14-day period. Seventy-two patients completed the evaluation, aged 39 ± 15 years, diabetes duration 16 ± 13 years, HbA1c 8.3 ± 1.6%. At follow-up, 62 (86.1%) patients used the remote control for ≥50% of all boluses, 20 (27.8%) used the bolus advisor for ≥50% of all boluses, and 42 (58.3%) viewed at least 1 of the e-logbook reports. More than 95% of users appraised the functions as easy-to-use and useful; median scores from VAS (0 = useless to 100 = indispensable) ranged from 72 to 85. A high percentage of study patients used the system's advanced features, especially the remote control feature for bolusing. Overall, patients assessed the functions as useful and easy to use. Results support the implementation of these smart capabilities in further insulin pump developments.

Can integrated technology improve self-care behavior in youth with type 1 diabetes? A randomized crossover trial of automated pump function

Automated blood glucose (BG) and insulin pump systems allow wireless transmission of all BG readings to a user's pump. This study aimed to assess whether use of such a system, as compared with a manual BG entry insulin pump, resulted in higher mean daily frequency of BGs recorded after 6 months. A 12-month randomized crossover trial, comprising 2 phases, was conducted. All participants used insulin pump devices with automated vs manual BG entry for 6 months each; order of system use was randomly assigned. Device interactions were assessed from pump and glucometer downloads. Thirty-five participants were enrolled; 9 withdrew during the study. Use of the automated insulin pump system resulted in higher mean daily BG recorded over 6 months of use when compared to a manual BG entry system (5.8 ± 1.7 vs 5.0 ± 1.9; P = .02 [95% confidence interval, 0.14 to 1.58]). Bolus frequency was similar between groups. No HbA1c difference was observed between groups at 6 months (8.0% [64 mmol/l] ± 1.3 automated vs 7.7% [61 mmol/l] ± 0.9 manual; P = .38). Post hoc analysis demonstrated improved ΔHbA1c with automated system use in an adolescent subgroup with suboptimal baseline BG frequency (-0.9% vs + 0.5%; P = .003). Use of an automated glucometer/insulin pump resulted in higher number of BGs recorded over 6 months when compared to an insulin pump with manual BG entry. This may be especially beneficial for adolescent manual system users who enter <5 BGs per day into their pump.

Cross-sectional survey and retrospective analysis of a large cohort of adults with type 1 diabetes with long-term continuous subcutaneous insulin infusion treatment

Background. Continuous subcutaneous insulin infusion (CSII) is an established modality for intensive insulin treatment of type 1 diabetes (T1D), but long-term data concerning satisfaction, CSII function use, safety, and efficacy in real-life conditions are scarce. Methods. We analyzed a cohort of adult patients with T1D treated with CSII for more than 1 year in a single diabetes center. We performed a cross-sectional survey in 2010 (tolerance/satisfaction and behavior forms) and a retrospective analysis of medical records (including HbA1c level, hospitalization, and catheter infections). The primary objective was to assess long-term tolerance/satisfaction, and secondary objectives were safety and efficacy. Results. There were 295 patients analyzed. After a median duration of CSII use of 5 years, overall satisfaction was high for about 90% of patients. Mean CSII-related discomfort scores were low for work, recreation, and sleep and moderate for sport and sexual activity (2.5 ± 1.9, 2.6 ± 1.8, 2.6 ± 2.1, 3.4 ± 2.3, and 4.0 ± 2.9 of 10, respectively). Despite a high level of diabetes education, only one third of patients were using advanced CSII functions. During long-term follow-up, the safety of CSII treatment was good; the hospitalization rate was 0.18 patients/year, and catheter infections were scarce. The HbA1c level dropped about -0.5% independently from CSII duration (P < .05). Conclusions. In this adult cohort, satisfaction and tolerance, together with safety, of CSII were maintained at long-term follow up. The sole basic functions of CSII were currently used by patients. A 0.5% decrease in the HbA1c level was maintained during the study period.

Novel insulin delivery profiles for mixed meals for sensor-augmented pump and closed-loop artificial pancreas therapy for type 1 diabetes mellitus

Maintaining euglycemia for people with type 1 diabetes is highly challenging, and variations in glucose absorption rates with meal composition require meal type specific insulin delivery profiles for optimal blood glucose control. Traditional basal/bolus therapy is not fully optimized for meals of varied fat contents. Thus, regimens for low- and high-fat meals were developed to improve current insulin pump therapy. Simulations of meals with varied fat content demonstrably replicated published data. Subsequently, an insulin profile library with optimized delivery regimens under open and closed loop for various meal compositions was constructed using particle swarm optimization. Calculations showed that the optimal basal bolus insulin profiles for low-fat meals comprise a normal bolus or a short wave. The preferred delivery for high-fat meals is typically biphasic, but can extend to multiple phases depending on meal characteristics. Results also revealed that patients that are highly sensitive to insulin could benefit from biphasic deliveries. Preliminary investigations of the optimal closed-loop regimens also display bi- or multiphasic patterns for high-fat meals. The novel insulin delivery profiles present new waveforms that provide better control of postprandial glucose excursions than existing schemes. Furthermore, the proposed novel regimens are also more or similarly robust to uncertainties in meal parameter estimates, with the closed-loop schemes demonstrating superior performance and robustness.

Use of an insulin bolus advisor facilitates earlier and more frequent changes in insulin therapy parameters in suboptimally controlled patients with diabetes treated with multiple daily insulin injection therapy: results of the ABACUS trial

BACKGROUND

We assessed the impact of using an automated bolus advisor integrated into a blood glucose meter on the timing and frequency of adjusting insulin therapy parameter settings and whether the availability of this technology would increase blood glucose test strip utilization in diabetes patients treated with multiple daily insulin injection (MDI) therapy.

SUBJECTS AND METHODS

The Automated Bolus Advisor Control and Usability Study (ABACUS) trial, a 26-week, prospective, randomized, controlled, multinational study that enrolled 218 type 1 and type 2 diabetes patients, demonstrated that use of an automated insulin bolus advisor helps improve glycemic control in suboptimally controlled, MDI-treated patients. Patient data were assessed to determine when and how often changes in insulin parameter settings occurred during the study. Patient meters were downloaded to determine blood glucose monitoring frequency.

RESULTS

One hundred ninety-three patients completed the study: 93 control arm (CNL) and 100 intervention (experimental) arm (EXP). Significantly more EXP (47.5%) than CNL (30.7%) patients received one or more changes in their insulin sensitivity factor (ISF) settings during the study (P=0.0191). Changes in ISF settings occurred earlier and more frequently in EXP than CNL patients throughout the study. A similar trend was seen in changes in insulin-to-carbohydrate ratios. There were no differences in daily self-monitoring of blood glucose frequency [mean (SD)] between CNL and EXP patients: 4.7 (1.5) versus 4.6 (1.3) (P=0.4085).

CONCLUSIONS

Use of an automated bolus advisor was associated with earlier, more frequent changes in key insulin parameters, which may have contributed to subsequent improvements in glycemic control but without increased glucose test strip utilization.

Carbohydrate counting with an automated bolus calculator helps to improve glycaemic control in children with type 1 diabetes using multiple daily injection therapy: an 18-month observational study

AIMS

This study aimed to investigate the effect of carbohydrate counting (carbC), with or without an automated bolus calculator (ABC), in children with type 1 diabetes treated with multiple daily insulin injections.

METHODS

We evaluated 85 children, aged 9-16 years, with type 1 diabetes, divided into four groups: controls (n=23), experienced carbC (n=19), experienced carbC+ABC (n=18) and non-experienced carbC+ABC (n=25). Glycated haemoglobin (HbA1c), insulin use, and glycaemic variability - evaluated as high blood glucose index (HBGI) and low blood glucose index (LBGI) - were assessed at baseline and after 6 and 18 months.

RESULTS

At baseline, age, disease duration, BMI, HbA1c, insulin use, and HBGI (but not LBGI; p=0.020) were similar for all groups. After 6 months, HbA1c improved from baseline, although not significantly - patients using ABC (according to manufacturer's recommendations) HbA1c 7.14 ± 0.41% at 6 months vs. 7.35 ± 0.53% at baseline, (p=0.136) or without carbC experience HbA1c 7.61±0.62% vs. 7.95 ± 0.99% (p=0.063). Patients using ABC had a better HBGI (p=0.001) and a slightly worse LBGI (p=0.010) than those not using ABC. ABC settings were then personalised. At 18 months, further improvements in HbA1c were seen in children using the ABC, especially in the non-experienced carbC group (-0.42% from baseline; p=0.018).

CONCLUSIONS

CarbC helped to improve glycaemic control in children with type 1 diabetes using multiple daily injections. ABC use led to greater improvements in HbA1c, HBGI and LBGI compared with patients using only carbC, regardless of experience with carbC.

Bolus calculator and wirelessly communicated blood glucose measurement effectively reduce hypoglycaemia in type 1 diabetic children - randomized controlled trial

BACKGROUND

The aim of this study was to assess the effect of bolus calculator function and wireless communication between insulin pump and blood glucose metre on metabolic control in children with type 1 diabetes, treated with insulin pumps.

METHODS

In this randomized, controlled, 12-week trial, 156 patients, aged 12.9 ± 2.6 years, with a history of diabetes of 5.1 ± 3.3 years and glycated haemoglobin values of 7.3 ± 1.2% (56.3 ± 13.44 mmol/mol) were included. Children were assigned to one of three arms: group A, subjects using bolus calculator and wireless communication between insulin pump and blood glucose metre; group B, subjects using bolus calculator without communication between the devices and group C, control group. Devices were downloaded at 0, 6 and 12 weeks.

RESULTS

There were statistically fewer episodes of hypoglycaemia in children using bolus calculator compared with the control group: A versus C (3.8 ± 3.1 versus 7.8 ± 5.13 episodes/2 weeks, respectively, p < 0.0001); B versus C (3.6 ± 3.3 versus 7.8 ± 5.1 episodes/2 weeks, respectively, p < 0.0001). Patients in group A used bolus calculator function significantly more frequently than patients in group B (4.9 ± 3.4 versus 2.5 ± 2.9 times/24 h, respectively, p = 0.0006). No significant differences in glycated haemoglobin levels were found between the experimental and the control groups: group A versus C (p = 0.699). The use of bolus calculator did not influence post-prandial glycaemia, body mass index-SD score or insulin/kg/24 h.

CONCLUSIONS

Bolus calculator use reduces hypoglycaemic episodes independently of communication between insulin pump and blood glucose metre. Wireless communication between devices results in more frequent bolus calculator use.

Use of an insulin bolus advisor improves glycemic control in multiple daily insulin injection (MDI) therapy patients with suboptimal glycemic control: first results from the ABACUS trial

OBJECTIVE

Use of automated bolus advisors is associated with improved glycemic control in patients treated with insulin pump therapy. We conducted a study to assess the impact of using an insulin bolus advisor embedded in a blood glucose (BG) meter on glycemic control and treatment satisfaction in patients treated with multiple daily insulin injection (MDI) therapy. The study goal was to achieve >0.5% A1C reduction in most patients.

RESEARCH DESIGN AND METHODS

This was a 26-week, prospective, randomized, controlled, multinational study that enrolled 218 MDI-treated patients with poorly controlled diabetes (202 with type 1 diabetes, 16 with type 2 diabetes) who were 18 years of age or older. Participants had mean baseline A1C of 8.9% (SD, 1.2 [74 mmol/mol]), mean age of 42.4 years (SD, 14.0), mean BMI of 26.5 kg/m(2) (SD, 4.2), and mean diabetes duration of 17.7 years (SD, 11.1). Control group (CNL) patients used a standard BG meter and manual bolus calculation; intervention group (EXP) patients used the Accu-Chek Aviva Expert meter with an integrated bolus advisor to calculate insulin dosages. Glucose data were downloaded and used for therapy parameter adjustments in both groups.

RESULTS

A total of 193 patients (CNL, n = 93; EXP, n = 100) completed the study. Significantly more EXP than CNL patients achieved >0.5% A1C reduction (56.0% vs. 34.4%; P < 0.01). Improvement in treatment satisfaction (Diabetes Treatment Satisfaction Questionnaire scale) was significantly greater in EXP patients (11.4 [SD, 6.0] vs. 9.0 [SD, 6.3]; P < 0.01). Percentage of BG values <50 mg/dL was <2% in both groups during the study.

CONCLUSIONS

Use of an automated bolus advisor resulted in improved glycemic control and treatment satisfaction without increasing severe hypoglycemia.

ProAct study: new features of insulin pumps improve diabetes management and glycemic control in patients after transition of continuous subcutaneous insulin infusion systems

BACKGROUND

Continuous subcutaneous insulin infusion (CSII) patients experience switches of pump systems on a regular basis. We investigated the impact of transition from older pumps to the Accu-Chek(®) Combo system (Roche Diagnostics Deutschland GmbH, Mannheim, Germany) on a patient's glycemic control and diabetes management.

PATIENTS AND METHODS

In total, 299 patients (172 female, 127 male; mean±SD age, 39.4±15.2 years; CSII duration, 7.0±5.2 years) were enrolled by 61 European sites into this uncontrolled prospective trial. Glycemic control, safety, and diabetes management parameters were measured at baseline and after 3 and 6 months. Changes from baseline were analyzed.

RESULTS

After transition to the new insulin pump, mean±SD hemoglobin A1c (HbA1c) values decreased from 7.8±1.1% (baseline) to 7.7±1.1% (end point). The proportion of patients with HbA1c <7.0% was slightly higher at the end of the study (29.6%) than at baseline (25.2%), whereas the proportion of patients with HbA1c >8.0% decreased (baseline, 36.2%; end point, 32.7%; P<0.05). The number of hypoglycemic episodes (blood glucose<70 mg/dL) improved slightly during the study (baseline, 40.4±34.0 events/quarter; end point, 39.2±33.9 events/quarter). Glycemic control improved significantly in the group with an initial HbA1c >8.0% (-0.46%; P<0.001) and remained solidly stable in the group with an initial HbA1c <7% (+0.04%; not significant). Short-term (<3 years) pump users (n=48) had a larger HbA1c decrease (-0.40%) than long-term (≥3 years) users (n=251) (-0.07%; P<0.05). The number of blood glucose measurements increased (3.7±1.9/day vs. 4.4±1.8/day; P<0.05), whereas the number of insulin boluses decreased (5.1±1.9/day vs. 4.6±1.5/day; P<0.05) during the study.

CONCLUSIONS

Transition from older pump systems to the Accu-Chek Combo system in a large patient population resulted in stable glycemic control with significant improvements in HbA1c in patients with unsatisfactory baseline HbA1c and shorter pump use. Increased frequency of self-monitoring of blood glucose and decrease of bolus frequency could suggest a more confident diabetes management and a reduced need for correction boluses.

Glucose meters with built-in automated bolus calculator: gadget or real value for insulin-treated diabetic patients?

Self-monitoring of blood glucose is now widely recognized as efficacious to enhance and facilitate diabetes management. More than just a means of recording and storing data, some blood glucose meters (BGMs) are now designed with an embedded automated bolus calculator (ABC) with the goal to propose patients recommendations about insulin dosage. The growing literature in this field tends to claim that these new smart BGMs make patient's life easier and decision making safer. The main purpose of this review is to verify whether BGMs with a built-in ABC indeed improve the willingness and the ability of insulin-treated patients to make adequate therapeutic decisions and positively impact the metabolic control and the quality of life of ABC users. It appears that, as long as the education provided by caregivers remains a top priority, BGMs with a built-in ABC (more than just electronic gadgets) can be regarded as bringing real value to insulin-treated patients with diabetes.

Insulin bolusing software: the potential to optimize health outcomes in type 1 diabetes mellitus

BACKGROUND

Insulin bolusing calculators alleviate the burden of having to calculate insulin bolus doses for patients with type 1 diabetes mellitus (T1DM). Three important pieces of information are needed: a blood glucose monitoring (BGM) result, carbohydrates to be consumed, and the amount of insulin bolus delivered. The purpose of this study was to describe insulin pump adherence behaviors associated with the use of bolus calculators in youth who use Medtronic insulin pumps.

METHODS

Data were downloaded from the MiniMed Paradigm insulin pumps (Medtronic) of 31 youth with T1DM. Areas of adherence that were evaluated included fundamental insulin pump adherence behaviors (e.g., BGM, carbohydrate entry, and insulin bolusing), decisions about Wizard® recommendations, and three Wizard steps: BGM result-carbohydrate input-insulin bolus.

RESULTS

On average, patients conducted BGM ≥4 times/day on 69% of days, inputted carbohydrates ≥3 times/day on 63% of days, and insulin bolused ≥3 times/day on 85% of days. Participants generally followed Wizard recommendations. Finally, participants completed all three Wizard steps (BGM, carbohydrate input, insulin bolus) within 30 min for an average of 29% of boluses. Almost 3% of boluses that were preceded by Wizard use were delivered without conducting BGM or inputting carbohydrates.

CONCLUSION

There was substantial variability in insulin pump adherence behaviors (e.g., days when no BGM occurred, reliance on basal insulin). Interventions targeting insulin pump adherence behaviors have the potential to optimize diabetes health outcomes and glycemic control. Improving insulin pump software reports is one promising avenue for improving adherence.

Improving the computational effort of set-inversion-based prandial insulin delivery for its integration in insulin pumps

OBJECTIVE

Set-inversion-based prandial insulin delivery is a new model-based bolus advisor for postprandial glucose control in type 1 diabetes mellitus (T1DM). It automatically coordinates the values of basal-bolus insulin to be infused during the postprandial period so as to achieve some predefined control objectives. However, the method requires an excessive computation time to compute the solution set of feasible insulin profiles, which impedes its integration into an insulin pump. In this work, a new algorithm is presented, which reduces computation time significantly and enables the integration of this new bolus advisor into current processing features of smart insulin pumps.

METHODS

A new strategy was implemented that focused on finding the combined basal-bolus solution of interest rather than an extensive search of the feasible set of solutions. Analysis of interval simulations, inclusion of physiological assumptions, and search domain contractions were used. Data from six real patients with T1DM were used to compare the performance between the optimized and the conventional computations.

RESULTS

In all cases, the optimized version yielded the basal-bolus combination recommended by the conventional method and in only 0.032% of the computation time. Simulations show that the mean number of iterations for the optimized computation requires approximately 3.59 s at 20 MHz processing power, in line with current features of smart pumps.

CONCLUSIONS

A computationally efficient method for basal-bolus coordination in postprandial glucose control has been presented and tested. The results indicate that an embedded algorithm within smart insulin pumps is now feasible. Nonetheless, we acknowledge that a clinical trial will be needed in order to justify this claim.

Automated bolus advisor control and usability study (ABACUS): does use of an insulin bolus advisor improve glycaemic control in patients failing multiple daily insulin injection (MDI) therapy? [NCT01460446]

BACKGROUND

People with T1DM and insulin-treated T2DM often do not follow and/or adjust their insulin regimens as needed. Key contributors to treatment non-adherence are fear of hypoglycaemia, difficulty and lack of self-efficacy associated with insulin dose determination. Because manual calculation of insulin boluses is both complex and time consuming, people may rely on empirical estimates, which can result in persistent hypoglycaemia and/or hyperglycaemia. Use of automated bolus advisors (BA) has been shown to help insulin pump users to more accurately meet prandial insulin dosage requirements, improve postprandial glycaemic excursions, and achieve optimal glycaemic control with an increased time within optimal range. Use of a BA containing an early algorithm based on sliding scales for insulin dosing has also been shown to improve HbA1c levels in people treated with multiple daily insulin injections (MDI). We designed a study to determine if use of an automated BA can improve clinical and psychosocial outcomes in people treated with MDI.

METHODS/DESIGN

The Automated Bolus Advisor Control and Usability Study (ABACUS) is a 6-month, prospective, randomised, multi-centre, multi-national trial to determine if automated BA use improves glycaemic control as measured by a change in HbA1c in people using MDI with elevated HbA1c levels (#62;7.5%). A total of 226 T1DM and T2DM participants will be recruited. Anticipated attrition of 20% will yield a sample size of 90 participants, which will provide #62;80% power to detect a mean difference of 0.5%, with SD of 0.9%, using a one-sided 5% t-test, with 5% significance level. Other measures of glycaemic control, self-care behaviours and psychosocial issues will also be assessed.

DISCUSSION

It is critical that healthcare providers utilise available technologies that both facilitate effective glucose management and address concerns about safety and lifestyle. Automated BAs may help people using MDI to manage their diabetes more effectively and minimise the risk of long-term diabetes related complications. Findings from a recent study suggest that BA use positively addresses both safety and lifestyle concerns; however, randomised trials are needed to confirm these perceptions and determine whether bolus advisor use improves clinical outcomes. Our study is designed to make these assessments.

TRIAL REGISTRATION

NCT01460446.

Closed-loop insulin delivery in type 1 diabetes

Advances in diabetes technology have led to significant improvements in the quality of life and care received by individuals with diabetes. Despite this, achieving tight glycemic control through intensive insulin therapy and modern insulin regimens is challenging because of the barrier of hypoglycemia, the most feared complication of insulin therapy as reported by patients, caregivers, and physicians. This article outlines the individual components of the closed-loop system together with the existing clinical evidence. The artificial pancreas prototypes currently used in clinical studies are reviewed as well as obstacles and limitations facing the technology.

Use of an automated bolus calculator reduces fear of hypoglycemia and improves confidence in dosage accuracy in patients with type 1 diabetes mellitus treated with multiple daily insulin injections

BACKGROUND

Many patients do not intensify their insulin regimens. It is believed that lack of adherence may be largely due to fear of hypoglycemia. We hypothesized that utilization of an automated bolus calculator (bolus advisor) might reduce fear of hypoglycemia and encourage patients to achieve improved glycemic control.

METHOD

We surveyed 1,412 type 1 diabetes mellitus (T1DM) patients treated with multiple daily insulin injection therapy at 270 hospitals in the United Kingdom and Republic of Ireland to assess their attitudes and behaviors regarding insulin therapy after use of a bolus advisor (Accu-Chek® Aviva Expert blood glucose meter and bolus advisor system, Roche Diagnostics). The device automatically calculates bolus dosages based on current blood glucose values, anticipated meal intake, and other parameters.

RESULTS

Five hundred eighty-eight T1DM patients responded to the survey. Respondents were predominantly female, age <1 to 70 years, with diabetes duration of <1 to >15 years. Respondents had 4-12 weeks prior experience using the bolus advisor. 76.7% of respondents indicated current bolus advisor use to calculate insulin boluses for meals/snacks always or quite often. 52.0% of respondents indicated that fear of hypoglycemia was reduced (39.0%) or significantly reduced (13.0%). 78.8% indicated that confidence in the insulin dose calculation improved (50.8%) or significantly improved (28.0%). 89.3% indicated that the bolus advisor made bolus calculation easy or very easy compared with manual calculation.

CONCLUSIONS

Most patients felt that using the bolus advisor was easier than manual bolus calculation, improved their confidence in the accuracy of their bolus dosage, and reduced their fear of hypoglycemia. Randomized trials are needed to confirm these perceptions and determine whether bolus advisor use improves clinical outcomes.

Multicenter user evaluation of ACCU-CHEK® Combo, an integrated system for continuous subcutaneous insulin infusion

BACKGROUND

The aim of this study was to evaluate a newly developed system for insulin delivery incorporating a multifunctional blood glucose meter and a remotely controlled insulin pump (ACCU-CHEK® Combo system) in established pump users with type 1 diabetes. The technology was assessed both from device performance and subject usability perspectives.

METHOD

A multicenter, prospective, single group study was carried out in five centers in the Netherlands and four centers in the United Kingdom for more than 6 months. The study was divided into two phases: Phase 1 (4 weeks) for device validation purposes and phase 2 (22 weeks) to observe the impact of the system on metabolic control, patient satisfaction [using the Diabetes Treatment Satisfaction Questionnaire (DTSQ)] and device safety.

RESULTS

Eighty subjects completed the planned study period. There were no unexpected device errors. Treatment satisfaction was high at baseline and further increased to study end (DTSQ change version: sum score, 10.6±7.2; scale score range, -18 to +18, p<0.0001). Hemoglobin A1c improved continuously over time, from 7.9% (±0.9%) to 7.7% (±0.8%) at month 3 (p<0.001) and 7.6% (±0.8%) at month 6 (p<0.0001). The frequency of severe hypoglycemia was 0.08 per patient years. There was no case of ketoacidosis.

CONCLUSIONS

The new system was evaluated by experienced continuous subcutaneous insulin infusion users as safe in daily practice and associated with favorable treatment satisfaction and a modest improvement in glycemic control.