An algorithm guiding patient responses to real-time-continuous glucose monitoring improves quality of life

Effect of Wearable Technology on Metabolic Control and the Quality of Life in Children and Adolescents with Type 1 Diabetes: A Systematic Review and Meta-Analysis

Background

Type 1 diabetes is one of the most common chronic diseases in children. Wearable technology (insulin pumps and continuous glucose monitoring devices) that makes diabetes management relatively simple, in addition to education and follow-ups, enhances the quality of life and health of individuals with diabetes.

Aims

To evaluate the impact of wearable technology on metabolic management and the quality of life in children and adolescents with type 1 diabetes.

Study Design

Systematic review and meta-analysis.

Methods

The Preferred Reporting System for Systematic Reviews and Meta-Analyses was used to conduct a systematic review and meta-analysis. PubMed, Web of Science, MEDLINE, Cochrane Library, EBSCO, Ulakbim and Google Scholar were searched in July 2022 and July 2023 using predetermined keywords. The methodological quality of the studies was evaluated using the Joanna Briggs Institute’s Critical Appraisal Checklists for randomized controlled experimental and cross-sectional studies. The meta-analysis method was used to pool the data.

Results

Eleven studies published between 2011 and 2022 were included. The total sample size of the included studies was 1,853. The meta-analysis revealed that the decrease in hemoglobin A1C (HbA1c) level in those using wearable technology was statistically significant [mean difference (MD): -0.33, Z = 2.54, p = 0.01]. However, the technology had no effect on the quality of life [standardized mean difference (SMD): 0.44, Z = 1.72, p = 0.09]. The subgroup analyses revealed that the decrease in the HbA1c level occurred in the cross-sectional studies (MD: -0.49, Z = 2.54, p = 0.01) and the 12-19 (MD = 0.59, Z = 4.40, p < 0.001) and 4-18 age groups (MD: -0.31, Z = 2.56, p = 0.01). The subgroup analyses regarding the quality of life revealed that there was no difference according to the research design. However, the quality of life was higher in the wearable technology group than in the control group in the 8-12 and 4-18 age groups (SMD: 1.32, Z = 2.31, p = 0.02 and SMD: 1.00, Z = 5.76, p < 0.001, respectively).

Conclusion

Wearable technology effectively reduces the HbA1c levels in children and adolescents with type 1 diabetes in some age groups. However, it does not affect the quality of life.

"Empowering Us": A Community-Led Survey of Real-World Perspectives of Adults with Type 1 Diabetes Using Insulin Pumps and Continuous Glucose Monitoring to Manage Their Glucose Levels

OBJECTIVE

To conduct an Australian community-led survey of adults with type 1 diabetes (T1D), identifying priorities for, and barriers to, optimal use of advanced glucose management technologies.

RESEARCH DESIGN AND METHODS

A 30-question online survey of current or past users of insulin pump therapy (IPT), real-time continuous glucose monitoring (RT-CGM), or intermittently scanned CGM (isCGM) explored perceptions regarding device design, access, education, outcomes, and support.

RESULTS

Between November 2021 and January 2022, surveys were completed by 3,380 participants (age [mean±SD] 45±16 years; 62% female; 20±14 years diabetes), with 55%, 82%, and 55% reporting experience with IPT, RT-CGM, and isCGM, respectively. Overall, most considered diabetes technology '(extremely) important' for maintaining target glucose levels (98%) and reducing hypoglycaemia severity and frequency (93%). For most, technology contributed positively to emotional well-being (IPT 89%; RT-CGM 91%; isCGM 87%), which was associated with device effectiveness in maintaining glucose in range, comfort, and convenience. Barriers included affordability (IPT 68%; RT-CGM 81%; isCGM 69%) and insufficient information for informed choices about device suitability (IPT 39%; RT-CGM 41%; isCGM 36%).

CONCLUSIONS

Technology is perceived by adults with T1D as important for managing glycaemia and emotional well-being. Modifiable barriers to use include affordability, and information regarding device suitability.

Technological Ecological Momentary Assessment Tools to Study Type 1 Diabetes in Youth: Viewpoint of Methodologies

Type 1 diabetes (T1D) is one of the most common chronic childhood diseases, and its prevalence is rapidly increasing. The management of glucose in T1D is challenging, as youth must consider a myriad of factors when making diabetes care decisions. This task often leads to significant hyperglycemia, hypoglycemia, and glucose variability throughout the day, which have been associated with short- and long-term medical complications. At present, most of what is known about each of these complications and the health behaviors that may lead to them have been uncovered in the clinical setting or in laboratory-based research. However, the tools often used in these settings are limited in their ability to capture the dynamic behaviors, feelings, and physiological changes associated with T1D that fluctuate from moment to moment throughout the day. A better understanding of T1D in daily life could potentially aid in the development of interventions to improve diabetes care and mitigate the negative medical consequences associated with it. Therefore, there is a need to measure repeated, real-time, and real-world features of this disease in youth. This approach is known as ecological momentary assessment (EMA), and it has considerable advantages to in-lab research. Thus, this viewpoint aims to describe EMA tools that have been used to collect data in the daily lives of youth with T1D and discuss studies that explored the nuances of T1D in daily life using these methods. This viewpoint focuses on the following EMA methods: continuous glucose monitoring, actigraphy, ambulatory blood pressure monitoring, personal digital assistants, smartphones, and phone-based systems. The viewpoint also discusses the benefits of using EMA methods to collect important data that might not otherwise be collected in the laboratory and the limitations of each tool, future directions of the field, and possible clinical implications for their use.

Evaluation of the application of the Diabetes Quality of Life Questionnaire in patients with diabetes mellitus

Objective Diabetes mellitus (DM) is a chronic disease with great impact on patients' quality of life (QoL). This variable can be measured using reliable, standardized, and validated instruments. The purpose of this study was to evaluate the application and reporting of the Diabetes Quality of Life Measure (DQOL) or the Diabetes Quality of Life for Youths Measure (DQOLY), an adapted version for young patients with DM. Materials and methods A systematic review of interventional and observational studies using the DQOL or DQOLY was performed. Searches were conducted in the electronic databases Medline, Scopus, Web of Science, Lilacs, and SciELO. Results After conducting the searches, 111 studies met the inclusion criteria and were included in the qualitative analysis. Of these, 32 studies were classified as interventional and 79 as observational, with 27,481 patients. The DQOL was applied in 82 studies, the DQOLY in another 27, and two studies used both instruments. DM was classified as type 1 DM in 69 studies and type 2 DM in 35 studies. Six studies included both patients. Improvement in patients' QoL after an intervention was observed in 13 interventional studies. Most of the studies (90%) provide a detailed description of the instrument and 52% the previous validation. The interpretation of the scores obtained varies among the studies, probably due to the differences inherent in cultural validations, translations, and adaptations. Conclusion The application of the instruments in clinical practice must be rigorously standardized and requires an accurate understanding of psychometric and statistical concepts. Arch Endocrinol Metab. 2020;64(1):59-65.

Continuous glucose monitoring: a review of the evidence, opportunities for future use and ongoing challenges

The advent of devices that can track interstitial glucose levels, which are closely related to blood glucose levels, on a near continuous basis, has facilitated better insights into patterns of glycaemia. Continuous glucose monitoring (CGM) therefore allows for more intensive monitoring of blood glucose levels and potentially improved glycaemic control. In the context of the announcement on 1 April 2017 that the Australian Government will fund CGM monitoring for people with type 1 diabetes under the age of 21 years, this paper provides a review of the evidence for CGM and some of the ongoing challenges. There is evidence that real-time CGM in type 1 diabetes improves HbA1c and hypoglycaemia, while in type 2 diabetes, the evidence is less robust. Initial barriers to widespread implementation of CGM included issues with accuracy and user friendliness; however, as the technology has evolved, these issues have largely improved. Ongoing barriers include cost, and weaker evidence for their benefit in certain populations such as those with type 2 diabetes and less glycaemic variability. CGM has the potential to reduce healthcare costs, although real-world studies, including cost-effectiveness analyses, are needed in this area.

Continuous glucose monitoring: A review of the technology and clinical use

Continuous glucose monitoring (CGM) is an increasingly adopted technology for insulin-requiring patients that provides insights into glycemic fluctuations. CGM can assist patients in managing their diabetes with lifestyle and medication adjustments. This article provides an overview of the technical and clinical features of CGM based on a review of articles in PubMed on CGM from 1999 through January 31, 2017. A detailed description is presented of three professional (retrospective), three personal (real-time) continuous glucose monitors, and three sensor integrated pumps (consisting of a sensor and pump that communicate with each other to determine an optimal insulin dose and adjust the delivery of insulin) that are currently available in United States. We have reviewed outpatient CGM outcomes, focusing on hemoglobin A1c (A1C), hypoglycemia, and quality of life. Issues affecting accuracy, detection of glycemic variability, strategies for optimal use, as well as cybersecurity and future directions for sensor design and use are discussed. In conclusion, CGM is an important tool for monitoring diabetes that has been shown to improve outcomes in patients with type 1 diabetes mellitus. Given currently available data and technological developments, we believe that with appropriate patient education, CGM can also be considered for other patient populations.

Assessing quality of life in diabetes: II - Deconstructing measures into a simple framework

A growing number of instruments measuring diabetes-specific health-related quality of life (HRQOL) have been identified in previous systematic reviews, the most recent being published in 2008. The purpose of this paper is report on an updated systematic review of diabetes-specific HRQOL measures highlighting the time period 2006-2016; to deconstruct existing diabetes-specific HRQOL measures into a simple framework for evaluating the goodness-of-fit between specific research needs and instrument characteristics; and to present core characteristics of measures not yet reported in other reviews to further facilitate scale selection. Using the databases Medline, Pubmed, CINAHL, OVID Embase, and PsycINFO, we identified 20 diabetes-specific HRQOL measures that met our inclusion criteria. For each measure, we extracted eight core characteristics for our measurement selection framework. These characteristics include target population (type 1 vs. type 2), number and type of HRQOL dimensions measured and scored, type of score and calculation algorithm, sensitivity to change data reported in subsequent studies, number of survey items, approximate time length to complete, number of studies using the instrument in the past 10years, and specific languages instruments is translated. This report provides a way to compare and contrast existing diabetes-specific HRQOL measures to aid in appropriate scale selection and utilization.

Psychological Reactions Associated With Continuous Glucose Monitoring in Youth

Glucose monitoring is prerequisite to all other diabetes self-care behaviors and helps patients to reduce their risk for diabetes-related complications due to elevated glycemia. Because of the amount of information available and the ability to deliver glucose results in real-time, continuous glucose monitoring (CGM) has the ability to improve on self-monitoring blood glucose. However, epidemiologic data demonstrate slow uptake of CGM by patients, especially among youth. Several new diabetes therapies rely on CGM for feedback on patients' glucose levels to optimize treatment (eg, the low-glucose suspend insulin pump) and there are new technologies currently in development that will also need this information to work (eg, the artificial pancreas). To help patients to realize the potential benefits of these new treatments, it is essential to explore patients' psychological and behavioral reactions to CGM and then target device enhancements and/or the development of behavioral therapies to minimize negative reactions and to improve patients' CGM adoption rates. Limited research is available examining the psychological and behavioral reactions of CGM use in youth exclusively, but there are more studies examining these reactions in mixed samples of youth, parents, and adults. The purpose of this review is to summarize the available literature examining psychological and behavioral reactions to CGM use in young people with diabetes and to highlight how the results of past and future studies can inform device updates and/or behavioral intervention development to minimize barriers.

Perceived accuracy in continuous glucose monitoring: understanding the impact on patients

In terms of accuracy and reliability, the technology of real-time (RT) continuous glucose monitoring (CGM) is advancing quickly. Still, current devices are imperfect; as a result, patient complaints and frustrations are not uncommon. How do patients' perceptions of device accuracy affect their experience with RT-CGM? In this article, we argue that patients' satisfaction, or dissatisfaction, with accuracy has a major impact on how much they are likely to trust the device and how confident they may feel in using the information that is displayed. The available data suggest that greater satisfaction with accuracy is linked to better RT-CGM adherence, more confident and aggressive insulin adjustments, improvements in quality of life, reduced reliance on self-monitoring of blood glucose, and--potentially--less alarm fatigue. As the technology continues to mature, RT-CGM will become increasingly accurate and patients' confidence and trust in the available devices will likely grow, leading to greater uptake and more proactive use of RT-CGM.

Monitoring glycemia in diabetes

Monitoring of glycemic control is a key component of the diabetes treatment plan. Patients who are not meeting targets often require more intensive monitoring, ranging from frequent self-monitored glucose to continuous glucose monitoring in order to facilitate medication and lifestyle changes. However, more intensive monitoring demands more training and a structured plan for interpretation and use of the data. Better patient and provider tools to support decision-making and progress toward an artificial pancreas may help to alleviate this burden.

Feasibility of adjacent insulin infusion and continuous glucose monitoring via the Medtronic Combo-Set

BACKGROUND

Subcutaneously infused insulin may interfere with the function of nearby glucose-sensing electrodes and vice versa. The prototype of the Combo-Set device (Medtronic) incorporates a subcutaneous insulin delivery catheter and continuous glucose monitoring (CGM) sensor assembled on the same platform and separated by 11 mm. We aim to evaluate Combo-Set's insulin delivery and glucose-sensing functions.

METHODS

Ten subjects with type 1 diabetes wore a Combo-Set and a Sof-Sensor inserted subcutaneously in contralateral abdominal areas connected to iPro recorders (Medtronic) for 53.25 ± 0.75 h (mean ± standard deviation). The Combo-Set delivered insulin diluent except during meal tests on days 1 and 3 when insulin lispro was delivered as a meal bolus and postmeal basal. Venous plasma samples were collected at the following time points from meal start: 0, 30, 60, 120, and 180 min for insulin measurements. The accuracy of the Combo-Set sensors was evaluated and compared with that of the Sof-Sensor, with each referenced against capillary glucose values (Contour Link Meter, Bayer).

RESULTS

Accuracy of the Combo-Set sensor was comparable to that of the Sof-Sensor. Clarke error grid analysis showed that 97% of Combo-Set and 93% of Sof-Sensor values were in the A+B regions (p = .20, not significant). The Combo-Set showed the expected postbolus peak insulin time (67 ± 9 min, mean ± standard error). One "no delivery" alarm occurred during the 21 patient days of use.

CONCLUSION

A device providing for simultaneous adjacent placement of an insulin infusion catheter and a CGM sensor is feasible and functions within acceptable limits. The low "no delivery" alarm rate was similar to that of other infusion sets.

Is continuous glucose monitoring (CGM) for everyone? To whom should CGM be prescribed and how?

Are all type 1 diabetes (T1DM) patients potential candidates for continuous glucose monitoring (CGM)? Clearly, some patients improve their metabolic control with this tool, such as adults with poor metabolic control, especially those treated with continuous subcutaneous insulin infusion (CSII), and compliant patients with HbA(1c) levels <7%. There are also less good candidates for CGM, such as patients aged 8-18 years because they are reluctant to wear the sensors or those with new-onset T1DM. Other patient groups have not yet been evaluated, such as patients aged <8 years, women during pregnancy, and those with HbA(1c) >10% and/or severe hypoglycaemia. Beyond the indications, the mode of use of CGM is crucial. An appropriate patient selection, in order to choose those able to run the tool and motivated to use it, is necessary. How to prescribe the sensors is also an important question. Two approaches have been compared: patient-led and physician-driven prescription. Both modes of using CGM provide similar long-term metabolic improvement. However, physician-driven prescription is probably more cost-effective. The last key question is the education of patients by an experienced team. It can help them to translate the large amount of data from the monitor into effective self-management for optimalizing the CGM experience. However, elaboration of a validated algorithm is necessary to take full advantage of this device.

Emergent technologies applied to diabetes: what do we need to integrate continuous glucose monitoring into daily practice? Where the long-term use of continuous glucose monitoring stands in 2011

The earliest continuous glucose monitoring (CGM) devices did not permit real-time readouts of glucose measurements. Instead, they were used to determine the glucose profile of patients in "real life" and as educational tools. In contrast, the latest real-time devices, whether linked or not to an insulin pump, give the patient access to glucose measurements and incorporate alarms that can be set. Thus, they are the newest self-management tools for patients with type 1 diabetes requiring an intensive insulin regimen. Some long-term studies in a selected population of patients with type 1 diabetes have shown improvement of glycaemic control as measured by HbA(1c). Although the characteristics of "responsive" patients have yet to be identified, the ability of the patient to use the system on a near-daily basis (about 80% of the time) is a key point. Initial training of the patient by a professional team with expertise in CGM is also of the utmost importance. To date, CGM is not reimbursed by Social Security in France.

Personal continuous glucose monitoring (CGM) in diabetes management: review of the literature and implementation for practical use

AIM

Despite recent advances in diabetes therapy including the new long- and rapid-insulin analogs, insulin intensification strategies such as basal/bolus or pump therapy and sophisticated methods for insulin titration derived from the principles of functional insulin therapy, many patients fail to reach or maintain target glycosylated hemoglobin (HbA1c) values, putting them at increased risk for vascular complications. Continuous glucose monitoring (CGM) systems represent an important advance in diabetes technology that can facilitate optimal glucose control in type 1 diabetes.

METHOD

This review focuses on the efficacy and safety of CGM systems in diabetes management. The different CGM devices available are also described, as the way to use them and the educational approach to the patient in a step-by-step progression toward optimal glycemic control.

RESULTS

In type 1 diabetes, CGM systems are associated with 0.5-1% reduction in HbA1c without increased risk of hypoglycemia. CGM efficacy correlates with compliance to sensor wear, whatever the patient's age range.

CONCLUSION

Efficacy of CGM systems is now proven but indications, terms of use and educational issues of this new technology still need to be specified.

Assessment of patient-led or physician-driven continuous glucose monitoring in patients with poorly controlled type 1 diabetes using basal-bolus insulin regimens: a 1-year multicenter study

OBJECTIVE

The benefits of real-time continuous glucose monitoring (CGM) have been demonstrated in patients with type 1 diabetes. Our aim was to compare the effect of two modes of use of CGM, patient led or physician driven, for 1 year in subjects with poorly controlled type 1 diabetes.

RESEARCH DESIGN AND METHODS

Patients with type 1 diabetes aged 8-60 years with HbA(1c) ≥ 8% were randomly assigned to three groups (1:1:1). Outcomes for glucose control were assessed at 1 year for two modes of CGM (group 1: patient led; group 2: physician driven) versus conventional self-monitoring of blood glucose (group 3: control).

RESULTS

A total of 257 subjects with type 1 diabetes underwent screening. Of these, 197 were randomized, with 178 patients completing the study (age: 36 ± 14 years; HbA(1c): 8.9 ± 0.9%). HbA(1c) improved similarly in both CGM groups and was reduced compared with the control group (group 1 vs. group 3: -0.52%, P = 0.0006; group 2 vs. group 3: -0.47%, P = 0.0008; groups 1 + 2 vs. group 3: -0.50%, P < 0.0001). The incidence of hypoglycemia was similar in the three groups. Patient SF-36 questionnaire physical health score improved in both experimental CGM groups (P = 0.004). Sensor consumption was 34% lower in group 2 than in group 1 (median [Q1-Q3] consumption: group 1: 3.42/month [2.20-3.91] vs. group 2: 2.25/month [1.27-2.99], P = 0.001).

CONCLUSIONS

Both patient-led and physician-driven CGM provide similar long-term improvement in glucose control in patients with poorly controlled type 1 diabetes, but the physician-driven CGM mode used fewer sensors.