Use of Continuous Glucose Monitors to Manage Type 1 Diabetes Mellitus: Progress, Challenges, and Recommendations

Explanatory variables of objectively measured physical activity, sedentary behaviour and sleep in adults with type 1 diabetes: A systematic review

AIMS

This systematic review aimed to summarize knowledge on explanatory variables of PA, SB and sleep in adults with T1D to support the development of healthy lifestyle interventions.

METHODS

A systematic search of four databases (PubMed, Web of Science, Scopus and Embase) was performed. Only objective measurements of PA, SB and sleep were included and all explanatory variables were classified according to the socio-ecological model (i.e. intrapersonal, interpersonal, environmental and policy level). Risk of bias (ROB) (Joanna Briggs Institute appraisal checklists) and level of evidence (Evidence-Based Guideline Development) were assessed.

RESULTS

Twenty-one studies were included (66.7% low ROB). Most explanatory variables were situated at the intrapersonal level. A favourable body composition was associated with more time spent in total PA and moderate-to-vigorous PA (MVPA). Men with T1D spent more time in MVPA than women and a younger age was associated with increased MVPA. Barriers to PA were indeterminately associated with MVPA and HbA1c showed an indeterminate association with sleep. Explanatory variables of SB and light PA were not studied in at least two independent studies.

CONCLUSION

This review underscores the focus on the individual level to identify explanatory variables of movement behaviours in adults with T1D, despite the necessity for a socio-ecological approach to develop effective interventions. More evidence on psychological, interpersonal and environmental variables is needed as these are modifiable.

Glucose control and variability assessed by continuous glucose monitoring in patients with type 1 diabetes and diabetic kidney disease

Continuous glucose monitoring (CGM) has emerged as a superior method to glycated hemoglobin (HbA1c) monitoring for glycemic control assessment in type 1 diabetes (T1D). The association between CGM parameters and diabetic kidney disease (DKD) has not been extensively researched. The aim of the present study was to compare CGM metrics between patients with stable and progressive DKD and T1D. A cross-sectional study was performed with 75 patients with T1D, of which 28 had progressive DKD, defined as an estimated glomerular filtration rate decrease of ≥3 ml/min/year or an increased albuminuria stage over the median follow-up time of 7.46 (6.50-8.16) years. FreeStyle Libre ProiQ Sensors were used for CGM. Insulin sensitivity was calculated according to the estimated glucose disposal rate (eGDR) formula. The results revealed that as compared with subjects with stable DKD, individuals with progressive DKD exhibited a higher average glucose level (P=0.03), spent more time above the target range (P=0.05), less time in time in range (TIR; P=0.03), had a higher median estimated HbA1c (P=0.02) and glucose management indicator (P=0.03), as well as a longer duration of hypoglycemic events (P=0.03). There were no differences in compliance levels and recognition of hypoglycemia between the DKD study groups. Differences in correlation patterns between CGM parameters in patients with stable and progressive DKD were observed. For example, glucose variability was significantly positively correlated with TIR in subjects with DKD (Ρ=0.390; P=0.04) but not in individuals without DKD. The progression of DKD was statistically significantly associated with several CGM parameters in multivariate logistic regression models. Collectively, associations between CGM metrics and DKD status were demonstrated in patients with T1D. The findings of the present study indicate the necessity for regular CGM in patients with progressive DKD for improvement of their glycemic control and DKD outcomes but also call for the development of a personalized approach to CGM data interpretation and establishing therapeutic targets in these subjects.

Glucometrics and Patient-Reported Outcomes in Individuals With Type 1 Diabetes Mellitus: Insights From the Correlation of Time in Range (CorrelaTIR) Study in Real-World Settings

Background This study aimed to measure the association between time in range (TIR) and other continuous glucose monitoring (CGM)-derived glucometrics, quality of life (QoL), healthcare resource use (HCRU), and costs in persons with type 1 diabetes mellitus (T1DM) in routine clinical practice in Spain. Methods This observational, cross-sectional, multicentre study evaluated persons with T1DM who received insulin via multiple daily injections. The study collected data on the participants (demographic and clinical), the use of the CGM devices, patient-reported outcomes (PROs) for general and diabetes-related QoL, treatment satisfaction, work productivity and activity impairment, HCRU, and costs. Data were analysed descriptively. The Spearman correlation coefficient was used to measure the association between glucometrics and PROs, HCRU and costs. Results Participants (N=114) had a mean age (standard deviation) of 44.53 (14.39) years, were 50.88% men, and 53.51% had glycated haemoglobin ≤7%. A higher TIR was significantly associated with better diabetes-related QoL but not with general QoL. HCRU and PRO scores for treatment satisfaction and work productivity and activity impairment showed no correlation with TIR. Higher TIR correlated with a lower number of emergency room visits. Conclusion Good glycaemic control (high TIR) is favourably associated with some aspects of diabetes-related QoL.

American Diabetes Association Professional Practice Committee, ElSayed NA, McCoy RG, Aleppo G, Balapattabi K, Beverly EA, Briggs Early K, Bruemmer D, Echouffo-Tcheugui JB, Ekhlaspour L, Garg R, Khunti K, Lal R, Lingvay I, Matfin G, Pandya N, Pekas EJ, Pilla SJ, Polsky S, Segal AR, Seley JJ, Stanton RC, Bannuru RR. 7. Diabetes Technology: Standards of Care in Diabetes-2025

The American Diabetes Association (ADA) "Standards of Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, an interprofessional expert committee, are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations and a full list of Professional Practice Committee members, please refer to Introduction and Methodology. Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

Adolescents' Diabetes Self-Management Regimens and Outcomes During the COVID-19 Pandemic: A Scoping Review

Adolescents with diabetes mellitus (DM) experience poorer glycemic outcomes and lower adherence to self-management regimens compared to other age groups. The coronavirus 2019 (COVID-19) pandemic posed new barriers to DM self-management, including social distancing measures and additional stressors. We conducted a scoping review of peer-reviewed literature to examine self-management regimens and outcomes among adolescents aged 10-17 years with type 1 and type 2 DM during the pandemic. Our scoping review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched three online databases, screened articles through a rigorous process, and assessed bias using the Joanna Briggs Institute (JBI) Critical Appraisal Checklists. The findings from the included articles were categorized into six thematic areas: glycemic control/monitoring, insulin administration/regimens, weight/lifestyle behaviors, inpatient care/acute complications, outpatient care/telemedicine utilization, and psychosocial well-being. The findings from the included articles (n = 32) varied. Adolescents who used continuous glucose monitoring (CGM), regularly adjusted insulin doses, and utilized telemedicine generally maintained or improved glycemic control during the pandemic. However, many adolescents gained weight, reduced their physical activities, worsened their diet and sleep habits, and experienced increased stress, all of which negatively impacted glycemic control. Rates of acute complications and hospitalizations varied among adolescents. Telemedicine was widely used and viewed positively by adolescents with DM. Adolescents with DM faced various physical, behavioral, and psychosocial challenges during the COVID-19 pandemic. Further research is needed to assess the long-term impacts of the pandemic on this population. Multilevel interventions and preparedness efforts are required to improve and sustain adolescents' DM self-management outcomes during public health emergencies, particularly focused on promoting CGM use, increasing physical activity levels, improving dietary habits, and reducing stress.

[The impact of remote monitoring of glycemia self-control on carbohydrate metabolism and quality of life in patients with type 1 diabetes mellitus]

BACKGROUND

Self-monitoring of blood glucose (SMBG) is the main tool to achieve carbohydrate metabolism targets in patients with type 1 diabetes mellitus (DM). Remote monitoring of SMBG in Russia appeared relatively recently and needs to be evaluated for effectiveness.

AIM

To evaluate the effect of remote monitoring of SMBG on carbohydrate metabolism and quality of life in patients with type 1 DM in order to form new therapeutic approaches.

MATERIALS AND METHODS

Patients with type 1 DM with glycated hemoglobin (HbA1c) from 8.0 to 12.0% were divided into the main (n=107) and control group (n=20). Patients from the main group performed SMBG using glucometers with the possibility of remote data transmission, patients from the control group continued the traditional SMBG. The dynamics of HbA1c, derived time spent in the target ranges, recognition of hypoglycemia (GOLD scale, Clarke questionnaire), quality of life according to the SF-36 questionnaire were evaluated. The statistical analysis was carried out in the SPSS Version 26.0 program (IBM, USA).

RESULTS

In the main group (n=88) the HbA1c was statistically significant decreased after 6 months from 9.0% [8.4; 9.9] to 8.1% [7.4; 9.2] (p<0.001), with SMBG more than 4 times a day - up to 7.3% [7.0; 7.8] (p=0.001). In the control group (n=20), by the 6th month, HbA1c increased to 10.1% [8,9; 11,2] (p=0,010). Derived Time In Range in the main group increased to 69.9±13.0 (95% CI 65.73-74.03; p<0.001); derived Time Above Range significantly decreased to 9.5% [6.4; 15.0] (p<0.001), derived Time Below Range - to 6.7% [2.8; 12.2] (p=0.044); Coefficient of Variation reached 36.3±7.9 (95% CI 33.7-38.8; p<0.001). According to the results of SF-36, the physical and psychological components of the quality of life in the main group significantly improved (p<0.001). Recognition of hypoglycemia improved in the intervention group (-4.5% of patients (p=0.046) according to the Clarke questionnaire; -8% (p=0.008) on the GOLD scale).

CONCLUSION

Remote monitoring of SMBG is a prospective therapeutic approach due to its positive effect on carbohydrate metabolism and quality of life in patients with type 1 DM.

Personalized and predictive strategies for diabetic foot ulcer prevention and therapeutic management: potential improvements through introducing Artificial Intelligence and wearable technology

Diabetic foot ulcers represent a serious and costly complication of diabetes, with significant morbidity and mortality. The purpose of this study was to explore advancements in Artificial Intelligence, and wearable technologies for the prevention and management of diabetic foot ulcers. Key findings indicate that Artificial Intelligence-driven predictive analytics can identify early signs of diabetic foot ulcers, enabling timely interventions. Wearable technologies, such as continuous glucose monitors, smart insoles, and temperature sensors, provide real-time monitoring and early warnings. These technologies promise to revolutionize diabetic foot ulcer prevention by offering personalized care plans and fostering a participatory healthcare model. However, the review also highlights challenges such as patient adherence, socioeconomic barriers, and the need for further research to validate these technologies' effectiveness. The integration of artificial intelligence and wearable technologies holds the potential to significantly improve diabetic foot ulcer outcomes, reduce healthcare costs, and provide a more proactive and personalized approach to diabetic care. Further investments in digital infrastructure, healthcare provider training, and addressing ethical considerations are essential for successful implementation.

Applying technologies to simplify strategies for exercise in type 1 diabetes

Challenges and fears related to managing glucose levels around planned and spontaneous exercise affect outcomes and quality of life in people living with type 1 diabetes. Advances in technology, including continuous glucose monitoring, open-loop insulin pump therapy and hybrid closed-loop (HCL) systems for exercise management in type 1 diabetes, address some of these challenges. In this review, three research or clinical experts, each living with type 1 diabetes, leverage published literature and clinical and personal experiences to translate research findings into simplified, patient-centred strategies. With an understanding of limitations in insulin pharmacokinetics, variable intra-individual responses to aerobic and anaerobic exercise, and the features of the technologies, six steps are proposed to guide clinicians in efficiently communicating simplified actions more effectively to individuals with type 1 diabetes. Fundamentally, the six steps centre on two aspects. First, regardless of insulin therapy type, and especially needed for spontaneous exercise, we provide an estimate of glucose disposal into active muscle meant to be consumed as extra carbohydrates for exercise ('ExCarbs'; a common example is 0.5 g/kg body mass per hour for adults and 1.0 g/kg body mass per hour for youth). Second, for planned exercise using open-loop pump therapy or HCL systems, we additionally recommend pre-emptive basal insulin reduction or using HCL exercise modes initiated 90 min (1-2 h) before the start of exercise until the end of exercise. Modifications for aerobic- and anaerobic-type exercise are discussed. The burden of pre-emptive basal insulin reductions and consumption of ExCarbs are the limitations of HCL systems, which may be overcome by future innovations but are unquestionably required for currently available systems.

Evaluation of time in tight range and the glycaemia risk index in adults with type 1 diabetes using an advanced hybrid closed loop system: A 1-year real-world assessment

AIM

To assess the long-term glycaemic outcomes, with additional metrics, in adults with type 1 diabetes (T1D) using the Tandem t:slim X2 with Control-IQ technology advanced hybrid closed-loop (AHCL) system.

METHODS

This was a single-centre, retrospective study involving 56 T1D patients who transitioned to the Tandem t:slim X2 with Control-IQ system. The primary and secondary endpoints consisted of variations in time in tight range (TiTR; 70-140 mg/dL) and the glycaemia risk index (GRI), respectively. Additional standardized continuous glucose monitoring (CGM) metrics, mean sensor glucose, coefficient of variation, the glucose management indicator (GMI), HbA1c and insulin daily dose, were also evaluated. Variables were measured at baseline and at 15 days, 3 months, 6 months and 1 year after Tandem t:slim X2 Control-IQ initiation. Glucose outcomes are expressed as mean (standard deviation).

RESULTS

Use of Tandem t:slim X2 with Control-IQ over 1 year was associated with an increase in mean TiTR, from 38.11% (17.05%) to 43.10% (13.20%) (P = .059), and with a decline in the GRI, from 41.03 (25.48) to 28.55 (16.27) (P = .008). CGM metrics, including time in range and time above range, showed consistent improvements. Mean sensor glucose, the GMI and HbA1c decreased significantly over time. After an initial increase, insulin daily dose remained stable throughout the 12 months.

CONCLUSIONS

The results highlight the sustained effectiveness of Tandem t:slim X2 with Control-IQ in improving glycaemic outcomes over 1 year and support the use of this technology for the management of T1D.

Association Between Adherence, A1C Improvement, and Type of Continuous Glucose Monitoring System in People with Type 1 Diabetes or Type 2 Diabetes Treated with Intensive Insulin Therapy

INTRODUCTION

Use of continuous glucose monitoring (CGM) systems by people with diabetes is associated with improved glycemic outcomes, including lower glycated hemoglobin (A1C). Less is known about adherence to CGM systems, whether glycemic outcomes are impacted by levels of adherence, or whether adherence rates differ between types of CGM systems-intermittently scanned CGM (isCGM) or real-time CGM (rtCGM).

METHODS

A retrospective analysis of de-identified US administrative health claims and linked laboratory data was conducted using the Merative™ MarketScan® Research Database. The cohort included CGM-naïve people with type 1 diabetes (T1D) or type 2 diabetes treated with intensive insulin therapy (T2D-IIT) who initiated rtCGM or isCGM between August 1, 2019 and March 31, 2021 (defined as the index date). Adherence was calculated over a 12-month period using the proportion of days covered (PDC) with PDC ≥ 0.8 defined as adherent. A1C values were obtained within 6 months of the index date.

RESULTS

A total of 7669 individuals were identified. Subgroups included T1D using isCGM (n = 1578), T1D using rtCGM (n = 1244), T2D-IIT using isCGM (n = 3567), and T2D-IIT using rtCGM (n = 1280). After 12 months, PDC was 0.71 (0.30)-0.72 (0.31) (mean(SD)) for T1D and T2D-IIT rtCGM users and 0.55 (0.34)-0.56 (0.34) for T1D and T2D-IIT isCGM users. The proportion of adherent users (PDC ≥ 0.8) was 56.8-59.7% for rtCGM users and 36.3-37.6% for isCGM users. Overall, regardless of diabetes type, the odds of adherence were over two times higher for rtCGM users compared to isCGM users. For those with available A1C information (T1D n = 213; T2D-IIT n = 346), independent of CGM type, adherence to CGM was associated with a greater reduction in A1C and more people reaching A1C targets of < 7.0% or < 8.0%.

CONCLUSION

For people with T1D or T2D-IIT, higher adherence to CGM is associated with greater reductions in A1C, and higher adherence rates were observed with rtCGM systems than with isCGM systems.