Flash Glucose Monitoring and Patient Satisfaction: A Meta-Review of Systematic Reviews

Summary of clinical investigation plan for The DIATEC trial: in-hospital diabetes management by a diabetes team and continuous glucose monitoring or point of care glucose testing - a randomised controlled trial

BACKGROUND

Worldwide, up to 20 % of hospitalised patients have diabetes mellitus. In-hospital dysglycaemia increases patient mortality, morbidity, and length of hospital stay. Improved in-hospital diabetes management strategies are needed. The DIATEC trial investigates the effects of an in-hospital diabetes team and operational insulin titration algorithms based on either continuous glucose monitoring (CGM) data or standard point-of-care (POC) glucose testing.

METHODS

This is a two-armed, two-site, prospective randomised open-label blinded endpoint (PROBE) trial. We recruit non-critically ill hospitalised general medical and orthopaedic patients with type 2 diabetes treated with basal, prandial, and correctional insulin (N = 166). In both arms, patients are monitored by POC glucose testing and diabetes management is done by ward nurses guided by in-hospital diabetes teams. In one of the arms, patients are monitored in addition to POC glucose testing by telemetric CGM viewed by the in-hospital diabetes teams only. The in-hospital diabetes teams have operational algorithms to titrate insulin in both arms. Outcomes are in-hospital glycaemic and clinical outcomes.

DISCUSSION

The DIATEC trial will show the glycaemic and clinical effects of in-hospital CGM handled by in-hospital diabetes teams with access to operational insulin titration algorithms in non-critically ill patients with type 2 diabetes. The DIATEC trial seeks to identify which hospitalised patients will benefit from CGM and in-hospital diabetes teams compared to POC glucose testing. This is essential information to optimise the use of healthcare resources before broadly implementing in-hospital CGM and diabetes teams.

TRIAL REGISTRATION

Prospectively registered at ClinicalTrials.gov with identification number NCT05803473 on March 27th 2023.

Statistical Packages and Algorithms for the Analysis of Continuous Glucose Monitoring Data: A Systematic Review

BACKGROUND

Continuous glucose monitoring (CGM) measures glucose levels every 1 to 15 minutes and is widely used in clinical and research contexts. Statistical packages and algorithms reduce the time-consuming and error-prone process of manually calculating CGM metrics and contribute to standardizing CGM metrics defined by international consensus. The aim of this systematic review is to summarize existing data on (1) statistical packages for retrospective CGM data analysis and (2) statistical algorithms for retrospective CGM analysis not available in these statistical packages.

METHODS

A systematic literature search in PubMed and EMBASE was conducted on September 19, 2023. We also searched Google Scholar and Google Search until October 12, 2023 as sources of gray literature and performed reference checks of the included literature. Articles in English and Danish were included. This systematic review is registered with PROSPERO (CRD42022378163).

RESULTS

A total of 8731 references were screened and 46 references were included. We identified 23 statistical packages for the analysis of CGM data. The statistical packages could calculate many metrics of the 2022 CGM consensus and non-consensus CGM metrics, and 22/23 (96%) statistical packages were freely available. Also, 23 statistical algorithms were identified. The statistical algorithms could be divided into three groups based on content: (1) CGM data reduction (eg, clustering of CGM data), (2) composite CGM outcomes, and (3) other CGM metrics.

CONCLUSION

This systematic review provides detailed tabular and textual up-to-date descriptions of the contents of statistical packages and statistical algorithms for retrospective analysis of CGM data.

Expanding the Role of Continuous Glucose Monitoring in Modern Diabetes Care Beyond Type 1 Disease

Application of continuous glucose monitoring (CGM) has moved diabetes care from a reactive to a proactive process, in which a person with diabetes can prevent episodes of hypoglycemia or hyperglycemia, rather than taking action only once low and high glucose are detected. Consequently, CGM devices are now seen as the standard of care for people with type 1 diabetes mellitus (T1DM). Evidence now supports the use of CGM in people with type 2 diabetes mellitus (T2DM) on any treatment regimen, not just for those on insulin therapy. Expanding the application of CGM to include all people with T1DM or T2DM can support effective intensification of therapies to reduce glucose exposure and lower the risk of complications and hospital admissions, which are associated with high healthcare costs. All of this can be achieved while minimizing the risk of hypoglycemia and improving quality of life for people with diabetes. Wider application of CGM can also bring considerable benefits for women with diabetes during pregnancy and their children, as well as providing support for acute care of hospital inpatients who experience the adverse effects of hyperglycemia following admission and surgical procedures, as a consequence of treatment-related insulin resistance or reduced insulin secretion. By tailoring the application of CGM for daily or intermittent use, depending on the patient profile and their needs, one can ensure the cost-effectiveness of CGM in each setting. In this article we discuss the evidence-based benefits of expanding the use of CGM technology to include all people with diabetes, along with a diverse population of people with non-diabetic glycemic dysregulation.

Effects of E-health-based interventions on glycemic control for patients with type 2 diabetes: a Bayesian network meta-analysis

The high disease burden of type 2 diabetes seriously affects the quality of life of patients, and with the deep integration of the Internet and healthcare, the application of electronic tools and information technology to has become a trend for disease management. The aim of this study was to evaluate the effectiveness of different forms and durations of E-health interventions in achieving glycemic control in type 2 diabetes patients. PubMed, Embase, Cochrane, and Clinical Trials.gov were searched for randomized controlled trials reporting different forms of E-health intervention for glycemic control in type 2 diabetes patients, including comprehensive measures (CM), smartphone applications (SA), phone calls (PC), short message service (SMS), websites (W), wearable devices (WD), and usual care. The inclusion criteria were as follows: (1) adults (age≥18) with type 2 diabetes mellitus; (2) intervention period ≥1 month; (3) outcome HbA1c (%); and (4) randomized control of E-health based approaches. Cochrane tools were used to assess the risk of bias. R 4.1.2 was used to conduct the Bayesian network meta-analysis. A total of 88 studies with 13,972 type 2 diabetes patients were included. Compared to the usual care group, the SMS-based intervention was superior in reducing HbA1c levels (mean difference (MD)-0.56, 95% confidence interval (CI): -0.82 to -0.31), followed by SA (MD-0.45, 95% CI: -0.61 to -0.30), CM (MD-0.41, 95% CI: -0.57 to -0.25), W (MD-0.39, 95% CI: -0.60 to -0.18) and PC (MD-0.32, 95% CI: -0.50 to -0.14) (p < 0.05). Subgroup analysis revealed that intervention durations of ≤6 months were most effective. All type of E-health based approaches can improve glycemic control in patients with type 2 diabetes. SMS is a high-frequency, low-barrier technology that achieves the best effect in lowering HbA1c, with ≤6 months being the optimal intervention duration.

Systematic review registration

https://www.crd.york.ac.uk/prospero, identifier CRD42022299896.

Using flash glucose monitoring in pregnancies in routine care of patients with gestational diabetes mellitus: a pilot study

AIM

Flash glucose monitoring (FGM) has been approved for the care of pregnant women with preexisting diabetes since 2017. However, its use in gestational diabetes (GDM) has been critically discussed. Inaccuracy and missing recommendations for target values are the main arguments against the use of FGM in GDM. To date, there is a lack of data to justify routine use of FGM in GDM pregnancies. Consequently, this new technology has been withheld from GDM-patients. Aim of our pilot study was to analyze the impact of FGM use on pregnancy outcomes, patient's satisfaction and to confirm the safe use in GDM pregnancies.

METHODS

Cohort study of 37 FGM-managed GDM pregnancies compared with 74 matched women using self-monitoring of blood glucose (SMBG). Group comparison using nonparametric testing concerning patients characteristic and perinatal outcome focusing on adverse outcomes (preeclampsia, preterm delivery, large for gestational age, C-sections, neonatal intensive care unit admission, hyperbilirubinemia and hypoglycemia). Evaluation of patient's treatment satisfaction using the "Diabetes Treatment Satisfaction Questionnaire change" (DTSQc) and patient interviews.

RESULTS

No significant differences in patient's characteristics despite gestational age at diagnosis (FGM with 20 vs. SMBG with 25 weeks). No difference in gestational weight gain, HbA1c progression and perinatal outcome. Treatment satisfaction obtained by the DTSQc revealed a high level of satisfaction with FGM use.

CONCLUSION

FGM use was well accepted and did not affect perinatal outcome. Use of FGM during pregnancy is safe and non-inferior to the management with SBGM. FGM should be considered as an option in the management of GDM patients.

Continuous glucose monitoring and metrics for clinical trials: an international consensus statement

Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.

Effectiveness of a flash glucose monitoring systems implementation program through a group and telematic educational intervention in adults with type 1 diabetes

OBJECTIVES

Verifying the clinical effectiveness and the impact on quality-of-life parameters, fear of hypoglycaemia and satisfaction with the treatment obtained with a flash glucose monitoring (MFG) devices implantation program that includes a telematic and group educational intervention in adults with type 1 diabetes.

PATIENTS AND METHODS

Prospective quasi-experimental study, carried out during the COVID-19 pandemic period with a 9-month follow-up at the Virgen Macarena University Hospital, Sevilla.

RESULTS

Eighty-eight participants were included (men: 46.6%; mean age (years) 38.08, SD: 9.38); years of DM1 evolution: 18.4 (SD: 10.49); treatment with multiple doses insulin (MDI) 70.5% vs 29.5% subcutaneous insulin infusion therapy (CSII)). Baseline HbA1c was 7.74% (1.08). After the intervention, the global decrease in HbA1c was -0.45% (95% CI [-0.6, -0.25], P < 0.01), increasing to -1.08% in the group that started with HbA1c ≥ 8% (P < 0.01). A mean decrease in the Fear of Hypoglycemia 15 (FH15) test score of -6.5 points was observed (P < 0.01). In the global score of the Spanish version of Diabetes Quality Of Life (DQOL-s) test, the decrease was -8.44 points (P < 0.01). In Diabetes Treatment Satisfaction Questionnaire test (DTQ-s), global score increased in + 4 points (P < 0.01).

CONCLUSIONS

The incorporation of an educational program in group and telematic format within the development of MFG devices implantation strategies is an effective option, with associated benefits in quality of life and fear of hypoglycemia in adult patients with DM1. This option can be implemented in usual clinical practice.

Moving with technological advancements: blood glucose monitoring from a district nurse's perspective

Capillary blood glucose monitoring is a standard safety protocol before administering insulin. Over the past 12 months, there has been a notable increase in patients under the district nursing service using a flash glucose sensor (FGS), which is a portable technological device inserted into the skin via a stamp-like mechanism. The device sits in the interstitial fluid under the skin; the device can be scanned using a sensor to obtain glucose readings, which can eliminate the need for capillary finger pricking. From experience, some people opt for this device, considering the pain and inconvenience associated with capillary finger pricking. Despite some patients already utilising FGS, some community teams may still have to take a capillary finger prick before insulin administration, depending on local trust policy. Interestingly, while looking into the reasons for this, one discovered some contradictory concerns over the safety of FGS due to a difference in time lag, where interstitial fluid readings differ from blood glucose readings. However, new national guidelines reflect the push towards this technological innovation that could revolutionise patient care in glucose monitoring and diabetes management.

Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation

Traditional continuous glucose monitoring and flash glucose monitoring systems are proven to lower glycated haemoglobin levels, decrease the time and impact of hypoglycaemia or hyperglycaemia and, consequently, improve the quality of life for children and adults with type 1 diabetes mellitus (T1DM) and adults with type 2 diabetes mellitus (T2DM). These glucose-sensing devices can generate large amounts of glucose data that can be used to define a detailed glycaemic profile for each user, which can be compared with targets for glucose control set by an International Consensus Panel of diabetes experts. Targets have been agreed upon for adults, children and adolescents with T1DM and adults with T2DM; separate targets have been agreed upon for older adults with diabetes, who are at higher risk of hypoglycaemia, and women with pregestational T1DM during pregnancy. Along with the objective measures and targets identified by the International Consensus Panel, the dense glucose data delivered by traditional continuous glucose monitoring and flash glucose monitoring systems is used to generate an ambulatory glucose profile, which summarizes the data in a visually impactful format that can be used to identify patterns and trends in daily glucose control, including those that raise clinical concerns. In this article, we provide a practical guide on how to interpret these new glucometrics using a straightforward algorithm, and clear visual examples that demystify the process of reviewing the glycaemic health of people with T1DM or T2DM such that forward-looking goals for diabetes management can be agreed.