Diabetes Technology and the Human Factor

Identifying the deficiencies of currently available CGM to improve uptake and benefit

BACKGROUND AND AIMS

The use of diabetes technologies is increasing worldwide, with health systems facilitating improved access to devices. Continuous glucose monitoring is a complex intervention that provides information on glucose concentration, rate and direction of change, historical data and alerts and alarms for extremes of glucose. These data do not themselves change glycaemia and require translation to a meaningful action for impact. It is, therefore, crucial that such systems advance to better meet the needs of individuals using them.

METHODS

Narrative review of the use of, engagement with, limitations and unmet needs of continuous glucose monitoring systems.

RESULTS

CGM devices have made a significant contribution to the self-management of diabetes; however, challenges with access and user experience persist, with multiple limitations to uptake and benefit. These limitations include physical size and implementation, with associated stigma, alarm fatigue, sleep disturbance and the challenge of addressing large volumes of real-time data. Greater personalisation throughout the continuous glucose monitoring journey, with a focus on usability, may improve the benefits derived from the device and reduce the burden of self-management. Healthcare professionals may have unconscious biases that affect the provision of continuous glucose monitors due to deprivation, education, age, ethnicity and other characteristics.

CONCLUSIONS

Continuous glucose monitoring exerts a dose-dependent response; the more it is used, the more effective it is. For optimal use, continuous glucose monitors must not just reduce the burden of management in one dimension but facilitate net improvement in all domains of self-management for all users.

DiabetesWise: An innovative approach to promoting diabetes device awareness

BACKGROUND

DiabetesWise is an unbranded, data-driven online resource that tailors device recommendations based on preferences and priorities of people with insulin-requiring diabetes. The objective of this study is to examine whether DiabetesWise increases uptake of diabetes devices, which are empirically supported to improve glycemic and psychosocial outcomes.

METHODS

The sample included 458 participants (M_age  = 37.1, SD = 9.73; 66% female; 81% type 1 diabetes) with insulin-requiring diabetes and minimal diabetes device use at enrollment. Participants used DiabetesWise and completed online surveys. Chi-square and t tests evaluated requests for a device prescription, receiving a prescription, and starting a new device at 1 and 3 months post use. Baseline predictors of these variables and past use of continuous glucose monitors (CGMs) and changes in diabetes distress post use were also examined.

RESULTS

Within the first month of interacting with DiabetesWise 19% of participants asked for a prescription for a diabetes device. This rate rose to 31% in the first 3 months. These requests resulted in 16% of the sample starting a new device within the first 3 months. Whereas several factors were associated with prior CGM use, receiving a prescription, and starting a new device, more diabetes distress (t(343) = -3.13, p = .002) was the only factor associated with asking for a prescription. Diabetes distress decreased after interacting with DiabetesWise within 1 month (t(193) = 3.51, p < .001) and 3 months (t(180) = 5.23, p < .001).

CONCLUSIONS

Within 3 months of interacting with DiabetesWise, one in three participants had requested a prescription for a new diabetes device and average distress levels were reduced, indicating benefit from this low-intensity online platform.

Patch Pumps: What are the advantages for people with diabetes?

AIM

Patch pumps, i.e. insulin pumps without tubing, are an attractive alternative to conventional insulin pumps for people with type 1 diabetes and type 2 diabetes on insulin therapy. In this review, potential patient-relevant advantages and disadvantages of patch pumps are summarized and respective studies on patient-reported outcomes (PROs) are assessed.

METHODS

Relevant studies were identified through a systematic PubMed search. Reference lists in respective articles and Google Scholar were also checked for additional references. Articles in English published before June 30, 2021, were included; no other criteria on publication dates were set.

RESULTS

A total of 12 studies were included. The results of this analysis provide evidence that patch pumps improve quality of life, reduce diabetes-related distress, increase patient satisfaction, and are preferred by patients compared to conventional insulin pumps and multiple daily injection therapy (MDI). However, several methodological limitations of the studies identified constrain the significance of this analysis.

CONCLUSIONS

Despite the limited number of studies evaluating the benefits of patch pumps on PROs, there is increasing evidence that people with diabetes prefer patch pumps. Although there are numerous PROs for patch pumps, it is surprising that this aspect has been relatively understudied. More systematic evaluation studies of the benefits of patch pumps on PROs are needed.

Barriers to Continuous Glucose Monitoring in People With Type 1 Diabetes: Clinician Perspectives

The purpose of this study was to determine clinician attitudes about the distinct barriers to uptake of continuous glucose monitoring (CGM) among people with diabetes. Survey data were collected measuring individual barriers, prerequisites to CGM, confidence in addressing barriers, and clinic staff resources. Results show that clinicians commonly report barriers to using CGM among people with diabetes in their clinic. Furthermore, clinicians who report a high number of barriers do not feel confident in overcoming the barriers to CGM. Interventions that attempt to empower clinicians to address concerns about CGM among people with diabetes may be warranted because low uptake does not appear to be directly related to available resources or prerequisites to starting CGM.

Embedded Model Predictive Control for a Wearable Artificial Pancreas

While artificial pancreas (AP) systems are expected to improve the quality of life among people with type 1 diabetes mellitus (T1DM), the design of convenient systems that optimize the user experience, especially for those with active lifestyles, such as children and adolescents, still remains an open research question. In this work, we introduce an embeddable design and implementation of model predictive control (MPC) of AP systems for people with T1DM that significantly reduces the weight and on-body footprint of the AP system. The embeddable controller is based on a zone MPC that has been evaluated in multiple clinical studies. The proposed embedded zone MPC features a simpler design of the periodic safe zone in the cost function and the utilization of state-of-the-art alternating minimization algorithms for solving the convex programming problems inherent to MPC with linear models subject to convex constraints. Off-line closed-loop data generated by the FDA-accepted UVA/Padova simulator is used to select an optimization algorithm and corresponding tuning parameters. Through hardware-in-the-loop in silico results on a limited-resource Arduino Zero (Feather M0) platform, we demonstrate the potential of the proposed embedded MPC. In spite of resource limitations, our embedded zone MPC manages to achieve comparable performance of that of the full-version zone MPC implemented in a 64-bit desktop for scenarios with/without meal-disturbance compensations. Metrics for performance comparison included median percent time in the euglycemic ([70, 180] mg/dL range) of 84.3% vs. 83.1% for announced meals, with an equivalence test yielding p = 0.0013 and 66.2% vs. 66.0% for unannounced meals with p = 0.0028.

The Development and Psychometric Validation of the Diabetes Impact and Device Satisfaction Scale for Individuals with Type 1 Diabetes

BACKGROUND

With the rapid development of new insulin delivery technology, measuring patient experience has become especially pertinent. The current study reports on item development, psychometric validation, and intended use of the newly developed Diabetes Impact and Device Satisfaction (DIDS) Scale.

METHOD

The DIDS Scale was informed by a comprehensive literature review, and field tested as part of two focus groups. The finalized measure was used at baseline and 6 months post-assessment with a large US cohort. Exploratory factor analyses (EFAs) were conducted to determine and confirm factor structure and item selection. Internal reliability, test-retest reliability, and convergent/divergent validity of the emerged factors were tested with demographics, diabetes-specific information, and diabetes behavioral and satisfaction measures.

RESULTS

In all, 778 participants with type 1 diabetes (66% female, mean age 47.13 ± 17.76 years, 74% insulin pump users) completed surveys at both baseline and post-assessment. EFA highlighted two factors-Device Satisfaction (seven items, Cronbach's α = 0.85-0.90) and Diabetes Impact (four items, Cronbach's α = 0.71-0.75). DIDS Scale demonstrated good concurrent validity and test-retest reliability.

CONCLUSION

The DIDS Scale is a novel and a brief assessment tool with robust psychometric properties. It is recommended for use across all insulin delivery devices and is considered appropriate for use in longitudinal studies. Future studies are recommended to evaluate the performance of DIDS Scale in diverse populations with diabetes.

Comparison of Different Treatment Modalities for Type 1 Diabetes, Including Sensor-Augmented Insulin Regimens, in 52 Weeks of Follow-Up: A COMISAIR Study

OBJECTIVE

To compare different treatment modalities for patients with type 1 diabetes (T1D) based on real-time continuous glucose monitoring (RT-CGM) or self-monitoring of blood glucose (SMBG) combined with multiple daily injections (MDIs) or continuous subcutaneous insulin infusion (CSII).

RESEARCH DESIGN AND METHODS

Sixty-five T1D patients were followed up for a year. Of these, 27 started RT-CGM as part of a sensor-augmented insulin regimen (SAIR); within this SAIR group, 15 subjects started sensor-augmented pump (SAP) therapy and the remaining 12 continued with MDIs (MDIs + RT-CGM). A second group of 20 patients initiated CSII without RT-CGM, while a third group of 18 subjects continued on MDIs and SMBG. The main endpoints were reduction of HbA1c, glycemic variability (GV), and incidence of hypoglycemia.

RESULTS

After a year, the baseline mean HbA1c in the SAIR group (8.3%) decreased to 7.1% (P < 0.0001); both SAIR subgroups, SAP and MDIs + RT-CGM, showed comparable improvement. The CSII group also had reduced HbA1c (8.4% ± 0.9% vs. 7.9% ± 0.7%; P < 0.05). Both SAIRs were superior to MDIs (P = 0.002) and CSII (P = 0.0032). GV was also lowered, both in the SAIR (P < 0.0001) and CSII (P < 0.05) groups. Reduced incidence of hypoglycemia was observed only with SAIR (8% ± 4% vs. 6% ± 3%; P < 0.01).

CONCLUSION

Both SAIRs, SAP and MDIs + RT-CGM, provided significant and comparable decrease of HbA1c with concurrent reduction of hypoglycemia. This improvement was greater than that seen with CSII. The combination of RT-CGM and MDIs can be a suitable alternative to SAP for some patients.