Effect of Continuous Glucose Monitoring on Glycemic Control in Patients With Type 2 Diabetes Treated With Basal Insulin: A Randomized Clinical Trial

Narrative Review: Continuous Glucose Monitoring (CGM) in Older Adults with Diabetes

INTRODUCTION

Continuous glucose monitoring (CGM) has revolutionised diabetes care, with proven effect on glycaemic control, adverse diabetic events (such as hypoglycaemia and diabetic ketoacidosis) and hospitalisations in the general population. However, the evidence for CGM in older people is less robust.

METHOD

We conducted a narrative review of trials reporting data comparing standard blood glucose monitoring (SBGM) and CGM in adults over 65 with type 1 or type 2 diabetes who were treated with insulin published between 1999 and 2024.

RESULTS

Seventeen studies were identified, including eight retrospective cohort studies and five randomised controlled trials (RCTs). Sixteen of the 17 papers were based in Europe or North America. The studies were highly heterogeneous; however, they provided clear evidence supporting the use of CGM in reducing hypoglycemia in older adults, with potential benefits for overall wellbeing and quality of life..

CONCLUSIONS

Current approaches to diabetes care in older adults may over-rely on HbA1c (haemoglobin A1c) as a measurement of control given accuracy may be reduced in older adults and propensity for hypoglycaemia. Although goals should be personalised, avoidance of hypoglycaemia is a key goal for many older people with diabetes. There is good evidence that CGM can improve time-in-range and reduce hypoglycaemia and glucose variability in older adults. CGM should be considered for older adults as a means of reducing hypoglycaemia and associated potential harm.

Efficacy and safety of continuous glucose monitoring on glycaemic control in patients with chronic pancreatitis and insulin-treated diabetes: A randomised, open-label, crossover trial

AIMS

Continuous glucose monitoring (CGM) improves glycaemic control and reduces hypoglycaemia in type 1 and 2 diabetes, but its role in managing diabetes in chronic pancreatitis is unknown. We aimed to investigate the effect of CGM compared to self-monitoring of blood glucose (SMBG) on hypoglycaemia and glycaemic control in patients with chronic pancreatitis and insulin-treated diabetes.

MATERIALS AND METHODS

In a randomised, open-label, crossover trial, 30 participants with chronic pancreatitis and insulin-treated diabetes were randomised to 50 days of CGM or SMBG, separated by a 20-day washout period. The primary endpoint was time in level 2 hypoglycaemia (<3.0 mmol/L). Secondary endpoints included additional CGM metrics, HbA1c, daily insulin dose, questionnaires, and safety outcomes.

RESULTS

Twenty-nine participants completed the trial (mean age 64.4 ± 8.8 years; 22 men [75.9%]). There was a numerical reduction in time spent in level 2 hypoglycaemia with CGM compared to SMBG (mean difference -0.36%, 95% confidence interval (CI) -0.78% to 0.06%; p = 0.09). CGM improved time in range (3.9-10.0 mmol/L; mean difference 7.46%, 95% CI 1.67% to 13.25%; p = 0.01), reduced time above range (>10.0 mmol/L; mean difference -6.55%, 95% CI -12.59% to -0.51%; p = 0.04), and reduced time below range (<3.9 mmol/L; mean difference -0.91%, 95% CI -1.79% to -0.03%; p = 0.04) compared to SMBG. No differences were observed for the safety endpoints.

CONCLUSIONS

In patients with chronic pancreatitis and insulin-treated diabetes, CGM increased time in range and reduced time above and below range. These findings highlight the potential of CGM in improving glycaemic control.

Workplace-based continuous glucose monitoring with structured education for pre-diabetes and type 2 diabetes: A prospective community cohort study

AIMS

We investigated the effect of continuous glucose monitoring (CGM) with personalised structured education on patients with type 2 diabetes (T2D) and pre-diabetes in a workplace setting.

MATERIALS AND METHODS

This 8-week prospective study enrolled adults with T2D or pre-diabetes at Samsung Electronics Device Solutions between March and September 2023. Participants underwent CGM (Freestyle Libre) for 2 weeks and received personalized structured education on diet and physical activity. The primary outcome was the change in HbA1c level at 8 weeks compared with baseline. Secondary outcomes included changes in fasting blood sugar (FBS), lipid profile, weight and patient-related outcome measures (PROMs) at 8 weeks and longer.

RESULTS

Among 234 participants (161 T2D and 73 pre-diabetes), significant improvements were observed in the T2D group patients in terms of HbA1c (6.9% ± 1.2%-6.5% ± 0.8%), FBS (128.4 ± 36.9-117.6 ± 22.2 mg/dL), weight (81.9 ± 13.5-80.7 ± 13.6 kg) and low-density lipoprotein (LDL) cholesterol (106.0 ± 41.5 to 95.1 ± 35.9 mg/dL) (all p < 0.001) levels. Meanwhile, patients with pre-diabetes showed significant improvements in weight (79.7 ± 14.0-78.5 ± 13.9 kg) and LDL cholesterol (124.5 ± 32.8-113.8 ± 29.1 mg/dL) (all p < 0.001), with no significant changes in HbA1c or FBS. These improvements were maintained during follow-up check-ups after a mean of 6.4 months. Participants in both groups demonstrated improvements in their PROMs.

CONCLUSIONS

Among adults with T2D and pre-diabetes, the use of CGM with structured education in a workplace-based setting helped with weight loss and improved LDL cholesterol levels in both groups, while also improving glycaemia in patients with T2D.

Flash glucose monitoring for Indigenous Australians with type 2 diabetes: a randomised pilot and feasibility study

BACKGROUND

Flash glucose monitoring (FGM) can improve diabetes management, but no randomised controlled trials (RCTs) of FGM have been undertaken in Indigenous Australian populations. This study aimed to assess the feasibility of performing a RCT of FGM in Indigenous Australians with type 2 diabetes.

METHODS

In this open-labelled pilot RCT, Indigenous adults with type 2 diabetes were randomised to FGM or standard care for 6 months. Eligible participants were being treated with injectable diabetes medications and had a glycosylated haemoglobin (HbA1c) ≥ 7.0%. The feasibility outcome was the proportion of participants completing the trial, and the primary outcome for the future trial was change in HbA1c from baseline to 6 months. Secondary outcomes included change in time spent in target blood glucose (4.0-10.0 mmol/L), safety (hypoglycaemic episodes), and quality of life (EuroQol 5-dimension 3-level (EQ-5D-3L) score).

RESULTS

Of 126 screened individuals, 74 were eligible, 40 (54%) were randomised, and 39 (97.5%) completed the study. Participants' baseline characteristics were similar between the FGM and usual care groups, except for sex and body mass index. No between-group differences were observed for the following: change in HbA1c; percentage of time spent in target blood glucose (4.0-10.0 mmol/L), low glucose (< 3.9 mmol/L), and high glucose (> 15.0 mmol/L); or EQ-5D-3L scores. No severe hypoglycaemic episodes occurred.

CONCLUSIONS

This is the first pilot RCT of FGM in Indigenous Australians with type 2 diabetes. The results support a larger RCT.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry (ANZCTR12621000021875), retrospectively registered on 14 January 2021.

Assessing the Accuracy of Continuous Glucose Monitoring Metrics: The Role of Missing Data and Imputation Strategies

Aim: This study aims to evaluate the accuracy of continuous glucose monitoring (CGM)-derived metrics, particularly those related to glycemic variability, in the presence of missing data. It systematically examines the effects of different missing data patterns and imputation strategies on both standard glycemic metrics and complex variability metrics. Methods: The analysis modeled and compared the effects of three types of missing data patterns-missing completely at random, segmental, and block-wise gaps-with proportions ranging from 5% to 50% on CGM metrics derived from 14-day profiles of individuals with type 1 and type 2 diabetes. Six imputation strategies were assessed: data removal, linear interpolation, mean imputation, piecewise cubic Hermite interpolation, temporal alignment imputation, and random forest-based imputation. Results: A total of 933 14-day CGM profiles from 468 individuals with diabetes were analyzed. Across all metrics, the coefficient of determination (R2) improved as the proportion of missing data decreased, regardless of the missing data pattern. The impact of missing data on the agreement between imputed and reference metrics varied depending on the missing data pattern. To achieve high accuracy (R2 > 0.95) in representing true metrics, at least 70% of the CGM data were required. While no imputation strategy fully compensated for high levels of missing data, simple removal outperformed others in most scenarios. Conclusion: This study examines the impact of missing data and imputation strategies on CGM-derived metrics. The findings suggest that while missing data may have varying effects depending on the metric and imputation method, removing periods without data is a general acceptable approach.

Assessing the Financial Sustainability of a Virtual Clinic Providing Comprehensive Diabetes Care

INTRODUCTION

The Virtual Diabetes Specialty Clinic (VDiSC) study demonstrated the feasibility of providing comprehensive diabetes care entirely virtually by combining virtual visits with continuous glucose monitoring support and remote patient monitoring (RPM). However, the financial sustainability of this model remains uncertain.

METHODS

We developed a financial model to estimate the variable costs and revenues of virtual diabetes care, using visit data from the 234 VDiSC participants with type 1 or type 2 diabetes. Data included virtual visits with certified diabetes care and education specialists (CDCES), endocrinologists, and behavioral health services (BHS). The model estimated care utilization, variable costs, reimbursement revenue, gross profit, and gross profit margin per member, per month (PMPM) for privately insured, publicly insured, and overall clinic populations (75% privately insured). We performed two-way sensitivity analyses on key parameters.

RESULTS

Gross profit and gross profit margin PMPM (95% confidence interval) were estimated at $-4 ($-14.00 to $5.68) and -4% (-3% to -6%) for publicly insured patients; $267.26 ($256.59-$277.93) and 73% (58%-88%) for privately insured patients; and $199.41 ($58.43-$340.39) and 67% (32%-102%) for the overall clinic. Profits were primarily driven by CDCES visits and RPM. Results were sensitive to insurance mix, cost-to-charge ratio, and commercial-to-Medicare price ratio.

CONCLUSIONS

Virtual diabetes care can be financially viable, although profitability relies on privately insured patients. The analysis excluded fixed costs of clinic infrastructure, and securing reimbursement may be challenging in practice. The financial model is adaptable to various care settings and can serve as a planning tool for virtual diabetes clinics.

A Randomized Trial of Automated Insulin Delivery in Type 2 Diabetes

BACKGROUND

Automated insulin delivery (AID) systems have been shown to be beneficial for patients with type 1 diabetes, but data are needed from randomized, controlled trials regarding their role in the management of insulin-treated type 2 diabetes.

METHODS

In this 13-week, multicenter trial, adults with insulin-treated type 2 diabetes were randomly assigned in a 2:1 ratio to receive AID or to continue their pretrial insulin-delivery method (control group); both groups received continuous glucose monitoring (CGM). The primary outcome was the glycated hemoglobin level at 13 weeks.

RESULTS

A total of 319 patients underwent randomization. Glycated hemoglobin levels decreased by 0.9 percentage points (from 8.2±1.4% at baseline to 7.3±0.9% at week 13) in the AID group and by 0.3 percentage points (from 8.1±1.2% to 7.7±1.1%) in the control group (mean adjusted difference, -0.6 percentage points; 95% confidence interval [CI], -0.8 to -0.4; P<0.001). The mean percentage of time that patients were in the target glucose range of 70 to 180 mg per deciliter increased from 48±24% to 64±16% in the AID group and from 51±21% to 52±21% in the control group (mean difference, 14 percentage points; 95% CI, 11 to 17; P<0.001). All other multiplicity-controlled CGM outcomes reflective of hyperglycemia that were measured were significantly better in the AID group than in the control group. The frequency of CGM-measured hypoglycemia was low in both groups. A severe hypoglycemia event occurred in one patient in the AID group.

CONCLUSIONS

In this 13-week, randomized, controlled trial involving adults with insulin-treated type 2 diabetes, AID was associated with a greater reduction in glycated hemoglobin levels than CGM alone. (Funded by Tandem Diabetes Care; 2IQP ClinicalTrials.gov number, NCT05785832.).

The effect of type 2 diabetes genetic predisposition on non-cardiovascular comorbidities

Type 2 diabetes (T2D) is epidemiologically associated with a wide range of non-cardiovascular comorbidities, yet their shared etiology has not been fully elucidated. Leveraging eight non-overlapping mechanistic clusters of T2D genetic profiles, each representing distinct biological pathways, we investigate putative causal links between cluster-stratified T2D genetic predisposition and 21 non-cardiovascular comorbidities. Most of the identified putative causal effects are driven by distinct T2D genetic clusters. For example, the risk-increasing effects of T2D genetic predisposition on cataracts and erectile dysfunction are primarily attributed to obesity and glucose regulation mechanisms, respectively. When surveyed in populations across the globe, we observe opposing effect directions for depression, asthma and chronic obstructive pulmonary disease between populations. We identify a putative causal link between T2D genetic predisposition and osteoarthritis. To underscore the translational potential of our findings, we intersect high-confidence effector genes for osteoarthritis with targets of T2D-approved drugs and identify metformin as a potential candidate for drug repurposing in osteoarthritis.

Use of technology in prediabetes and precision prevention

Controlling the epidemic of diabetes is an urgent global healthcare challenge. The low uptake of diabetes prevention programs highlights difficulties in scalability, partly due to the need for intensive face-to-face contact and its impact on healthcare resource utilization. In this narrative review, we will summarize the latest evidence in technology-assisted lifestyle interventions. We will appraise evidence of digital diabetes prevention programs that use internet platforms or text messaging tools to support information delivery, lifestyle coaching, or peer support. We will also discuss the use of wearables, including physical activity trackers and continuous glucose monitoring (CGM) as part of lifestyle intervention. Experience from diabetes highlights the potential for CGM as a motivational tool to promote lifestyle change. The integration of digital data may facilitate earlier detection of prediabetes, sub-phenotyping, and personalized nutritional predictions. We will highlight major gaps in research and the need for rigorous clinical trials to evaluate the acceptability and cost-effectiveness of integrating technologies as part of a multicomponent strategy in diabetes prevention.

Most hospitalised patients with type 2 diabetes benefit from continuous glucose monitoring compared to point-of-care glucose testing in a non-intensive care unit setting: A heterogeneity of treatment effect analysis

AIMS

Understanding whether improved glycaemic outcomes from continuous glucose monitoring (CGM) compared to point-of-care (POC) glucose testing apply uniformly to all hospitalised non-intensive care unit (non-ICU) patients with type 2 diabetes or vary among subgroups is crucial for allocating healthcare resources.

MATERIALS AND METHODS

This two-site randomised controlled trial DIAbetes TEam and Cgm (DIATEC) enrolled 166 non-ICU patients with type 2 diabetes. Diabetes management was based on either POC glucose testing or CGM. Diabetes management was carried out by general hospital staff, under the guidance of specialised diabetes teams, using insulin titration protocols in both groups. We conducted heterogeneity of treatment effect regression analyses to assess whether certain patient characteristics (e.g., age, gender, haemoglobin A1c, etc.) modified the effects of CGM, compared to POC glucose testing, on the glycaemic outcomes time in/above/below range, mean glucose level, standard deviation (SD), coefficient of variation (CV) and hypoglycaemic events.

RESULTS

No heterogeneity of treatment effect was observed, suggesting that all patients benefited equally from CGM compared to POC glucose testing regarding glycaemic outcomes.

CONCLUSIONS

From a glycaemic perspective, CGM could be widely recommended for most non-ICU patients with type 2 diabetes, as its glycaemic benefits over POC glucose testing appear consistent regardless of individual characteristics.

Demographic, Clinical, Psychosocial, and Behavioral Predictors of Continuous Glucose Monitor Use in Adults with Type 2 Diabetes

BACKGROUND

Continuous glucose monitor (CGM) use is increasing rapidly among people with type 2 diabetes, although little is known about predictors of CGM use beyond clinical and demographic information available in electronic medical records. Behavioral and psychosocial characteristics may also predict CGM use.

OBJECTIVE

We examined clinical, psychosocial, and behavioral characteristics that may predict CGM use in adults with type 2 diabetes.

DESIGN

This longitudinal observational study comprised a secondary analysis of data collected in a larger trial. Enrollment included HbA1c tests and surveys assessing demographic, clinical, psychosocial, and behavioral characteristics. We queried participants regarding their CGM use during the study on their final self-report surveys, 15 months post-enrollment.

PARTICIPANTS

Participants were 245 community-dwelling adults with type 2 diabetes recruited from primary care.

APPROACH

We used logistic regression to predict CGM use during the 15-month trial period from baseline characteristics.

KEY RESULTS

Around one-third of participants (37.1%; 91/245) started CGM. Predictors of starting CGM in bivariate models included younger age, higher socioeconomic status, insulin use, higher HbA1c, and more diabetes distress. When including all potential predictors in a single multivariable model, only younger age (aOR = 0.95, p = 0.001), insulin use (aOR = 2.33, p = 0.006), and higher socioeconomic status (aOR = 0.44, p = 0.037) were significant predictors. Despite the association between higher HbA1c and CGM use, neither diabetes self-care behaviors nor diabetes self-efficacy significantly predicted CGM use. Of participants who tried a CGM, 14.3% (13/91) had stopped, with cost being the most-cited reason.

CONCLUSIONS

Even when including behavioral and psychological characteristics, younger age, using insulin, and higher socioeconomic status remain key predictors of CGM use. These findings emphasize the importance of access and affordability for people who may benefit from CGM. Providers should not bias their introduction of CGM towards those with (perceived or actual) optimal or sub-optimal self-care behaviors.

Insulin initiation for patients with poorly controlled type 2 diabetes mellitus

BACKGROUND

We examined the initiation of insulin therapy in patients with poorly controlled type 2 diabetes mellitus (T2DM), analyzed their glycemic responses, and compared patient profiles based on glycemic outcomes.

METHODS

Patients with T2DM initiated on insulin therapy were retrospectively analyzed. Data were collected from endocrinology clinic before and 3 and 6 months after insulin initiation. The primary outcome was hemoglobin A1c (HbA1c) level 6 months after commencing insulin treatment. Secondary outcomes included HbA1c levels at 3 months after insulin treatment and fasting blood glucose levels at 3 and 6 months after treatment. We analyzed the effects of insulin initiation and categorized patients based on their 6-month HbA1c levels: below the median of 7.8% (better response) and above 7.8% (worse response). Additionally, we evaluated patients based on HbA1c changes at 6 months, with greater or lesser changes defined by the cohort's median change of -1.4%.

RESULTS

Insulin therapy significantly reduced HbA1c (from 9.8% to 8.2%) and fasting blood glucose levels (from 221.4 to 147.2 mg/dL) within 3 months. After 6 months, HbA1c and fasting blood glucose levels decreased by 2.1% (9.8%-7.7%) and 77.2 mg/dL (221.4-144.2 mg/dL), respectively. Patients who responded better to insulin treatment showed lower fasting blood glucose levels by 6 months after insulin initiation and lower HbA1c levels as soon as 3 months after initiation. Patients with higher baseline glycemic profiles experienced significantly greater HbA1c reductions at 6 months post-treatment.

CONCLUSION

Insulin therapy significantly improved glycemic control in patients with T2DM within 3 months after initiation. Patients with higher baseline glycemic profiles experienced greater responses to insulin therapy.

The use of continuous glucose monitoring in people living with obesity, intermediate hyperglycemia or type 2 diabetes

A global trend towards increased obesity, intermediate hyperglycemia (previously termed prediabetes) and type 2 diabetes, has prompted a range of international initiatives to proactively raise awareness and provide action-driven recommendations to prevent and manage these linked disease states. One approach, that has shown success in managing people already diagnosed with type 2 diabetes mellitus, is to use continuous glucose monitoring (CGM) devices to help them manage their chronic condition through understanding and treating their daily glucose fluctuations, in assocation with glucose-lowering medications, including insulin. However, much of the burden of type 2 diabetes mellitus is founded in the delayed detection both of type 2 diabetes mellitus itself, and the intermediate hyperglycemia that precedes it. In this review, we provide evidence that using CGM technology in people at-risk of intermediate hyperglycemia or type 2 diabetes mellitus can significantly improve the rate and timing of detection of dysglycemia. Earlier detection allows intervention, including through continued use of CGM to guide changes to diet and lifestyle, that can delay or prevent harmful progression of early dysglycemia. Although further research is needed to fully understand the cost-effectiveness of this intervention in people at-risk or with early dysglycemia, the proposition for use of CGM technology is clear.

A pretrained transformer model for decoding individual glucose dynamics from continuous glucose monitoring data

Continuous glucose monitoring (CGM) technology has grown rapidly to track real-time blood glucose levels and trends with improved sensor accuracy. The ease of use and wide availability of CGM will facilitate safe and effective decision making for diabetes management. Here, we developed an attention-based deep learning model, CGMformer, pretrained on a well-controlled and diverse corpus of CGM data to represent individual's intrinsic metabolic state and enable clinical applications. During pretraining, CGMformer encodes glucose dynamics including glucose level, fluctuation, hyperglycemia, and hypoglycemia into latent space with self-supervised learning. It shows generalizability in imputing glucose value across five external datasets with different populations and metabolic states (MAE = 3.7 mg/dL). We then fine-tuned CGMformer towards a diverse panel of downstream tasks in the screening of diabetes and its complications using task-specific data, which demonstrated a consistently boosted predictive accuracy over direct fine-tuning on a single task (AUROC = 0.914 for type 2 diabetes (T2D) screening and 0.741 for complication screening). By learning an intrinsic representation of an individual's glucose dynamics, CGMformer classifies non-diabetic individuals into six clusters with elevated T2D risks, and identifies a specific cluster with lean body-shape but high risk of glucose metabolism disorders, which is overlooked by traditional glucose measurements. Furthermore, CGMformer achieves high accuracy in predicting an individual's postprandial glucose response with dietary modelling (Pearson correlation coefficient = 0.763) and helps personalized dietary recommendations. Overall, CGMformer pretrains a transformer neural network architecture to learn an intrinsic representation by borrowing information from a large amount of daily glucose profiles, and demonstrates predictive capabilities fine-tuned towards a broad range of downstream applications, holding promise for the early warning of T2D and recommendations for lifestyle modification in diabetes management.

Extended use of real-time continuous glucose monitoring in adults with insulin-requiring type 2 diabetes: Results from the first 26 weeks of the 2GO-CGM trial

AIMS

The first 26 weeks of the 2GO-CGM trial assessed the efficacy and safety of real-time continuous glucose monitoring (rtCGM) use within a supported specialist model of care in a cohort of community-based adults with insulin-requiring type 2 diabetes in New Zealand.

METHODS

A 26-week randomised one-way crossover 'waitlist-controlled' trial comparing rtCGM (Dexcom G6) with self-monitoring of blood glucose (SMBG). All participants completed 2 weeks of SMBG before being randomised to 12 weeks (phase 1) use of SMBG followed by 12 weeks (phase 2) use of rtCGM (Group A) or 24 weeks of rtCGM (Group B). A time-adjusted within-subject analysis was conducted to estimate the overall treatment effect of rtCGM versus SMBG.

RESULTS

Sixty-seven participants were randomised to Group A or B, and all were included in the analysis (53% indigenous Māori, 57% female, median age 53 [range 16-69] years). Baseline-adjusted mean time in range (3.9-10.0 mmol/L) was 15% (95% CI 10-20; p = <0.001) higher with rtCGM use versus SMBG use. There was no evidence of a difference in Hba1c between rtCGM and SMBG use (-3.4 mmol/mol [0.31%], 95% CI -9.4 to 2.7 mmol/mol [-0.86 to 0.24%], p = 0.27). One participant withdrew in phase 2 due to unmanageable skin reactions to the CGM device. There were no severe hypoglycaemia or ketoacidosis events in either group during the study.

CONCLUSIONS

Use of rtCGM demonstrates safe and sustained glycaemic improvement in rtCGM use with insulin-requiring type 2 diabetes during the first 26 weeks of the 2GO-CGM study.

A low-power approach to optical glucose sensing via polarisation switching

High-precision polarimetry is crucial for sensing and imaging applications, particularly for glucose monitoring within the physiological range of 50 to 400 mg/dl. Traditional approaches often rely on polarisation modulation using magneto-optic or liquid crystal modulators, which require high voltages or currents, limiting their practicality for wearable or implantable devices. In this work, we propose a polarisation-switching technique that alternates between two discrete polarisation states, offering a low-power alternative with miniaturisation potential. Using this method, we achieved a Mean Absolute Relative Difference of 7.7% and a Standard Error of Prediction of 9.6 mg/dl across the physiological glucose range, comparable to commercial continuous glucose monitors. Our approach demonstrates a limit of detection of approximately 40 mg/dl, with measurements performed in phosphate-buffered saline spiked with glucose. This work establishes polarisation switching as a viable alternative for glucose sensing, providing a foundation for future development of wearable and implantable glucose monitoring systems. By eliminating power-intensive components, our approach addresses key limitations of traditional polarimetric methods, paving the way for more accessible and energy-efficient diabetes management technologies.

Artificial intelligence tools in supporting healthcare professionals for tailored patient care

Artificial intelligence (AI) tools to support clinicians in providing patient-centered care can contribute to patient empowerment and care efficiency. We aimed to draft potential AI tools for tailored patient support corresponding to patients' needs and assess clinicians' perceptions about the usefulness of those AI tools. To define patients' issues, we analyzed 528,199 patient messages of 11,123 patients with diabetes by harnessing natural language processing and AI. Applying multiple prompt-engineering techniques, we drafted a series of AI tools, and five endocrinologists evaluated them for perceived usefulness and risk. Patient education and administrative support for timely and streamlined interaction were perceived as highly useful, yet deeper integration of AI tools into patient data was perceived as risky. This study proposes assorted AI applications as clinical assistance tailored to patients' needs substantiated by clinicians' evaluations. Findings could offer essential ramifications for developing potential AI tools for precision patient care for diabetes and beyond.

Impact of real-time glucose monitoring using FreeStyle Libre 3 on glycaemia in type 2 diabetes managed with basal insulin plus SGLT2 inhibitor and/or GLP-1 agonist: the FreeDM2 randomised controlled trial protocol

INTRODUCTION

Effective management of type 2 diabetes mellitus (T2DM) consists of lifestyle modification and therapy optimisation. While glycaemic monitoring can be used as a tool to guide these changes, this can be challenging with self-monitoring of blood glucose (SMBG). The FreeStyle Libre 3 (FSL3) is a real-time continuous glucose monitoring (CGM) system designed to replace SMBG. The evidence for the benefit of CGM in people with T2DM on non-intensive insulin regimens is limited. This study aims primarily to assess the glycaemic impact of FSL3 in people with suboptimally controlled T2DM treated with basal-only insulin regimens plus sodium-glucose cotransporter-2 (SGLT-2) inhibitor and/or glucagon-like peptide (GLP)-1 agonist.

METHODS AND ANALYSIS

This is an open-label, multicentre, parallel design, randomised (2:1) controlled trial. Recruitment has been offered across 24 clinical centres in the UK and nationally through self-referral. Adults with T2DM treated with basal-only insulin regimens plus SGLT-2 inhibitor and/or GLP-1 agonist and with screening HbA1c from ≥59 mmol/mol to ≤97 mmol/mol are included. Eligible participants will be randomised to either FSL3 (intervention) for 32 weeks or continuation of SMBG (control). The study is split into two phases, each of 16 weeks duration: phase 1 consisting of self-management with basal-insulin self-titration and phase 2 where additional therapies may be initiated. Control group participants may subsequently enter an optional extension phase to receive FSL3. The primary endpoint is the difference between treatment groups in mean change from baseline in HbA1c at 16 weeks. Secondary outcomes include HbA1c at 32 weeks, CGM-based metrics, therapy changes, physical activity levels and psychosocial measures. An economic evaluation for costs and patient outcomes will be undertaken.

ETHICS AND DISSEMINATION

The study was approved by the Health Research Authority, Health and Care Research Wales and the West Midlands-Edgbaston Research Ethics Committee (reference: 23/WM/0092). Study results will be disseminated in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05944432.

SECONDARY IDENTIFYING NUMBER

Identifier assigned by the sponsor: ADC-UK-PMS-22057.

PROTOCOL VERSION

Revision D. Dated, 13 December 2024.

A Randomized Clinical Trial of a Culturally Tailored Diabetes Education Curriculum With and Without Real-Time Continuous Glucose Monitoring in a Latino Population With Type 2 Diabetes: The CUT-DM With Continuous Glucose Monitoring Study

BACKGROUND

Data on culturally tailored diabetes education with and without real-time continuous glucose monitoring (RT-CGM) in Latinos with type 2 diabetes, who are not on intensive insulin management, is lacking.

RESEARCH DESIGN AND METHODS

This is an open-label randomized control trial of Latinos with uncontrolled (HbA1c > 8.0%) type 2 diabetes conducted in a Federally Qualified Health Center (FQHC). All participants received 12 one-hour culturally tailored education sessions. Patients were randomized (1:1) to education sessions only (blinded CGM) or cyclic (50 days wear: 10 days on, 7 days off) RT-CGM. The primary outcome was a change in HbA1c from baseline to 12 weeks in those with or without CGM. Secondary outcomes included 24-week HbA1c, CGM, and metabolic parameters.

RESULTS

Participants (n = 120) were 46 years old on average, 44% female, 98% preferred Spanish language, 30% with income <$25,000, 68% uninsured and 26% using basal insulin only. Mean 1-hour session attendance and RT-CGM wear was 7.0 (±4.4) and 27.9 (±20.5) days, respectively. Mean baseline HbA1c was 10.5% (±1.8). HbA1c reduced by 1.9% (95% confidence interval [CI]: 1.5-2.3) overall (P < .001). Participants in the RT-CGM group reduced HbA1c at 12 weeks by 2.3% (95% CI: 1.5-3.2) compared to 1.5% (95% CI: 0.6-2.3) in the blinded CGM group (P =.04). At 24 weeks, overall HbA1c reduction was maintained but between-group differences attenuated.

CONCLUSIONS

In a Latino type 2 diabetes population that was primarily noninsulin-requiring, virtually delivered, culturally tailored education improved HbA1c, with RT-CGM conferring greater improvement. RT-CGM should be an adjunctive therapy to diabetes education, irrespective of insulin use but continued cyclic CGM use may be needed for sustained effect.

Clinical outcomes of a real-world prospective study using Dexcom ONE continuous glucose monitoring in people with diabetes treated with two or more insulin injections per day

AIMS

This study assessed real-world glycaemic outcomes associated with the use of Dexcom ONE in adults with suboptimally controlled diabetes.

METHODS

In this single-site prospective study, adults with type 1 (T1D) or type 2 diabetes (T2D) taking two or more insulin injections per day initiated Dexcom ONE CGM use and attended follow-up data collection visits after 3 and 6 months. During the study, participants received usual diabetes care. Primary outcome was a change in HbA1c at 6 months. Additional outcomes included change in participant-reported outcomes and CGM-derived time in glucose range 3.9-10 mmol/L (TIR), time above range >10 mmol/L (TAR), and time below range <3.9 mmol/L (TBR).

RESULTS

There were 110 adults enrolled [T1D (n = 34): mean age 36.6 years, 55.9% female; T2D (n = 76): mean age 54.9 years, 38.2% female]. Mean HbA1c significantly decreased from 90 mmol/mol (10.3%) to 79 mmol/mol (9.4%) at 6 months (∆-12 mmol/mol, p < 0.001) in T1D users and from 86 mmol/mol (10.1%) to 67 mmol/mol (8.3%) in T2D users (∆-18 mmol/mol, p < 0.001). Perception of health and diabetes distress improved at 6 months for both groups. T1D users had modest improvement in TBR. T2D users exhibited a clinically meaningful increase in TIR (∆ + 9.0%).

CONCLUSION

Real-world Dexcom ONE use was associated with clinically significant reductions in mean HbA1c after 6 months, along with meaningful improvements in participant-reported outcomes. CGM-derived outcomes also improved, with the possibility of there being greater improvement than could be captured in this study. These findings support expanding access to this real-time CGM system.

A Randomized Controlled Trial Using Continuous Glucose Monitoring to Guide Food Choices and Diabetes Self-Care in People with Type 2 Diabetes not Taking Insulin

Objective: Continuous glucose monitoring (CGM) is an effective tool for individuals with type 2 diabetes (T2D) on insulin. This study evaluated the effect of using CGM to reduce hyperglycemia, by focusing on food and lifestyle choices, in people with T2D not taking insulin. Methods: A 6-month randomized, prospective four-center study was conducted. The primary end point was a within-group reduction in time above range >180 mg/dL (TAR180) at 3 months. Participants were asked not to make diabetes medication changes in the first 3 months. Seventy-two adults not on insulin or sulfonylurea therapy, with glycated hemoglobin (HbA1c) 7.5%-12%, were randomized to use CGM alone (n = 31) or CGM plus a food logging app (n = 41) to aid diabetes management. Participants attended guided education visits. Differences in CGM metrics, HbA1c, and body weight were compared. Results: The CGM alone group decreased TAR180 from 55% at baseline to 27% at 3 months (P < 0.001) and 21% at 6 months (P < 0.001); the CGM plus food logging app group decreased TAR180 from 53% at baseline to 30% at both 3 and 6 months (P < 0.001 for both). For all participants, time in range (70-180 mg/dL) increased from 46% at baseline to 71% at 3 months (P < 0.001) and to 72% at 6 months (P < 0.001). HbA1c and weight were reduced by 1.3% (P < 0.001) and 7 pounds (lbs.) (P < 0.001) for all participants at 6 months. Conclusion: People with T2D not taking insulin showed large, clinically significant improvements in CGM metrics and HbA1c when using either CGM alone or with a food logging app. This occurred with a near absence of medication changes in the first 3 months and were therefore likely due to changes in food and/or lifestyle choices.

A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring

The complex relationships between continuously monitored health signals and therapeutic regimens can be modelled via machine learning. However, the clinical implementation of the models will require changes to clinical workflows. Here we outline ClinAIOps ('clinical artificial-intelligence operations'), a framework that integrates continuous therapeutic monitoring and the development of artificial intelligence (AI) for clinical care. ClinAIOps leverages three feedback loops to enable the patient to make treatment adjustments using AI outputs, the clinician to oversee patient progress with AI assistance, and the AI developer to receive continuous feedback from both the patient and the clinician. We lay out the central challenges and opportunities in the deployment of ClinAIOps by means of examples of its application in the management of blood pressure, diabetes and Parkinson's disease. By enabling more frequent and accurate measurements of a patient's health and more timely adjustments to their treatment, ClinAIOps may substantially improve patient outcomes.

Continuous glucose monitoring among nurse practitioners in primary care: Characteristics associated with prescribing and resources needed to support use

BACKGROUND

Continuous glucose monitoring (CGM) can improve health for people with diabetes but is limited in primary care (PC). Nurse Practitioners (NPs) in PC can improve diabetes management through CGM, but NPs' interest in CGM and support needed are unclear.

PURPOSE

We describe behaviors and attitudes related to CGM for diabetes management among NPs in PC.

METHODOLOGY

This cross-sectional web-based survey of NPs practicing in PC settings used descriptive statistics to describe CGM experience and identify resources to support prescribing. We used multivariable regression to explore characteristics predicting prescribing and confidence using CGM for diabetes.

RESULTS

Nurse practitioners in hospital-owned settings were twice as likely to have prescribed CGM (odds ratio [OR] = 2.320, 95% CI [1.097, 4.903]; p = .002) than private practice; those in academic medical centers were less likely (OR = 0.098, 95% CI [0.012, 0.799]; p = .002). Past prescribing was associated with favorability toward future prescribing (coef. = 0.7284, SE = 0.1255, p < .001) and confidence using CGM to manage diabetes (type 1: coef. = 3.57, SE = 0.51, p < .001; type 2: coef. = 3.49, SE = 0.51, p < .001). Resources to prescribe CGM included consultation with an endocrinologist (62%), educational website (61%), and endocrinological e-consultations (59%).

CONCLUSIONS

Nurse practitioners are open to prescribing CGM and can improve diabetes management and health outcomes for PC patients.

IMPLICATIONS

Research should explore mechanisms behind associations with CGM experience and attitudes. Efforts to advance CGM should include educational websites and endocrinology consultations for NPs in PC.

Assessment of Quality of Life of Children and Adolescents with Type 1 Diabetes in Bahrain Using PedsQL 3.2 Diabetes Module

Background/Objectives: Living with type 1 diabetes (T1D) significantly impacts children and adolescents, affecting their physical, emotional, and social well-being. Poor glycemic control (HbA1c > 7.5%) is linked to lower health-related quality of life (HRQoL), highlighting the need for effective management. This study aimed to assess the HRQoL and evaluate the associations between various factors and domains of HRQoL among children and adolescents with T1D in Bahrain. Methods: This cross-sectional study enrolled 182 children and adolescents from 5 to 16 years with T1D from a tertiary care hospital. Participants had T1D for at least six months and were interviewed during regular follow-ups. Participants Outside the target age group and those with any comorbidity were excluded. Data collection involved demographic and diabetes-related information. The PedsQL 3.2 Diabetes Module was used to assess HRQoL. Results: The mean age at diagnosis was 6.83 ± 3.11 years, with 57.7% diagnosed between 6 and 11 years. The sample was gender-balanced (52.2% male, 47.8% female). Treatment adherence had the highest median score (80.0), while worry was the lowest (58.33). Diabetes symptoms were associated with family income, school performance, HbA1c, and emergencies. Treatment barriers were linked to age, education, insulin regimen, and glucometer type. Adherence correlated with age, age at diagnosis, sex, BMI, education, and comorbidities, with family income (β = 4.69, p = 0.032) and school performance (β = -22.986, p < 0.001) being significant predictors. Treatment adherence was negatively impacted by younger age (β = -20.651 for 6-8 years, β = -12.002 for 9-12 years, both p < 0.01) and comorbidities (β = -12.286, p = 0.021). Conclusions: This study highlights the significant impact of various factors on the HRQoL of children and adolescents with T1D in Bahrain, emphasizing the need for targeted interventions to improve their overall well-being.

Accuracy of the 15.5-Day G7 iCGM in Adults with Diabetes

Background: Continuous glucose monitors (CGM) are increasingly being used to manage diabetes. We evaluated the performance and safety of an investigational 15-day G7 integrated CGM (iCGM; Dexcom) in adults with diabetes. Methods: This prospective, multicenter study enrolled adults (age ≥18 years) with type 1 diabetes (T1D) or type 2 diabetes (T2D) at six clinical sites in the United States. Four in-clinic visits were conducted on days 1-3, 4-7, 9-12, and 13-15.5, with frequent arterialized venous blood draws for comparator measurements using a Yellow Springs Instrument (YSI) 2300 Stat Plus glucose analyzer. Participants with T1D or T2D using intensive insulin therapy participated in clinic sessions with deliberate, closely monitored glucose manipulations. Accuracy evaluations included the mean absolute relative difference (MARD), proportion of CGM values within 15 mg/dL of YSI values <70 mg/dL or within 15% of YSI values ≥70 mg/dL (%15/15), as well as %20/20, %30/30, and %40/40 agreement rates. Performance related to iCGM special controls, user experience, and device safety were also assessed. Results: The study enrolled 130 adults with diabetes (mean ± standard deviation age 43.0 ± 14.4 years, 53.1% female, 86.9% with T1D) and analyzed 20,310 CGM-YSI matched pairs from 130 15-day G7 CGM devices. The overall MARD was 8.0% and the %15/15, %20/20, %30/30, and %40/40 agreement rates were 87.7%, 94.2%, 98.9%, and 99.8%, respectively. The device exceeded iCGM performance goals, and user experiences were broadly positive. No serious adverse events were reported. Conclusions: The 15-day G7 iCGM was accurate and safe in adults with diabetes throughout the 15.5-day wear period. Clinicaltrials.gov: NCT05263258.

Continuous Glucose Monitoring Use in Youth with Type 2 Diabetes: A Pilot Randomized Study

Objective: Continuous glucose monitoring (CGM) enhances diabetes self-management in insulin-treated individuals. However, the feasibility, acceptability, and benefits/burdens in youth-onset type 2 diabetes (Y-T2D) who are on infrequent self-monitoring of blood glucose (SMBG) regimens remain unclear. Research Design and Methods: In Y-T2D prescribed SMBG less than or equal to twice daily, we conducted a 12-week randomized 2:1 parallel pilot trial of CGM versus fingerstick monitoring (Control). Control participants had an optional 4-week extension period to use CGM (Control-CGM). Feasibility was defined as recruitment, study participation, and retention >60% of individuals. Acceptability was defined as an individual CGM wear time of ≥60% at the end of the study. Diabetes distress and the benefits/burdens of CGM scores, hemoglobin A1c (HbA1c), and CGM-derived glycemic variables were compared at baseline and at the end of the intervention. Results: The recruitment rate was 54% (52 screened eligible, 18 CGM, 10 Control; 82% female, 68% Black, 14.9 ± 3.8 years, body mass index: 36.2 ± 7.7 kg/m2, HbA1c: 7.4 ± 2.4% (mean ± standard deviation [SD]), and 8 entered the optional Control-CGM group. The most commonly cited reason for declining study participation was reluctance to wear the device (50%). The participation rate was 91% and 75%, and retention was 100% and 75% for CGM and Control-CGM, respectively. A majority of Y-T2D had ≥60% wear time at the end of the study (CGM: 56% and Control-CGM: 83%). Wear time declined during the study (1st month: 71 ± 31% vs. 2nd month: 55 ± 32% vs. 3rd month: 38 ± 34%, P = 0.003). There were no significant changes in glycemia, CGM burden/benefits, or diabetes distress scores (P > 0.05). Minor sensor adhesion adverse events were common (75%) causes of reduced wear time. Conclusion: CGM was a feasible and acceptable adjunct to diabetes self-care among >50% of Y-T2D prescribed infrequent SMBG monitoring. Unwillingness to wear a device and social stigma impeded device use. Additional research is needed to mitigate the high rates of skin adhesion-related adverse events in this population.

Impact of Hybrid Care in Pharmacist-Led Diabetes Clinics on Hemoglobin A1c

Background: During the coronavirus disease 2019 (COVID-19) pandemic, many clinical practices shifted to using virtual platforms to care for patients. After in-person visits resumed, many patients continued to participate in virtual care. Objective: This study evaluated the impact of hybrid care (virtual and in-person visits) on diabetes control in patients seen by clinical pharmacists operating under collaborative drug therapy management (CDTM). Methods: A retrospective chart review was completed for adult (18+) patients with type 2 diabetes (T2D) managed under CDTM protocols in clinical pharmacy ambulatory care clinics. Patients were included if they were discharged between January 2018 to December 2019 (pre-video) or January 2022 to December 2023 (post-video) and had documented baseline and post-intervention hemoglobin A1c (HgbA1c) values. Results: Of the 528 patients that met the inclusion/exclusion criteria, 290 were in the pre-video group and 238 were in the post-video group. There was a non-statistically significant trend toward a greater average decline in HgbA1c in the post-video period (-1.7) compared with the pre-video period (-1.5) (P = 0.239). Secondary outcomes showed the percentage of no-show appointments to be less in the post-video group (7.1 vs 5.2; P = 0.0178) and the mean number of visits to be similar (6.4 vs 6.3; P = 0.5753). Conclusions: A hybrid visit-type model that incorporates video appointments into clinical pharmacy practice provided similar outcomes to traditional in-office/telephone visits. These results demonstrate the importance of ambulatory care pharmacists continuing to offer virtual visit types despite no longer being in a state of emergency.

Pharmacist Integration to Support Continuous Glucose Monitoring Initiation: A Collaborative, Patient-Centered Approach

Objective: The development of continuous glucose monitoring (CGM) has allowed for improved glycemic control among patients with diabetes. Clinical pharmacists possess medication expertise and can provide support for increased CGM utilization through device education and affordability assistance, but there is limited evidence evaluating the effectiveness of clinical pharmacist-assisted CGM initiation. The objective of this study was to examine how clinical pharmacist-assisted CGM implementation can impact glycemic control for patients with diabetes. Methods: This is a retrospective pre-post study that evaluated change in A1c among patients who were assisted with CGM device implementation by a clinical pharmacist between January 1, 2019, and December 31, 2023. The primary outcome of this study was change in A1c from baseline (prior to CGM initiation) to the next subsequent A1c following CGM initiation. The study team also investigated change in A1c among a subgroup of patients followed independently by clinical pharmacists practicing under a collaborative drug therapy management (CDTM) agreement. Results: Pharmacist-assisted CGM initiation led to a statically significant decrease in mean A1c of -0.71 (CI 95% 0.41-1.00, P < 0.001) across all patients. Within the CDTM subgroup, the mean A1c difference was -1.60 (CI 95% 0.64-2.55, P = 0.002) while in the non-CDTM subgroup, the mean A1c difference was -0.50 (CI 95% 0.22-0.78, P < 0.001). Conclusions: Clinical pharmacists are effective at helping patients with diabetes reduce their A1c through assisting with CGM initiation, education, and follow-up. Among patients included in this study, those followed by pharmacists practicing under CDTM agreements saw the greatest amount of A1c reduction.

Determinants of implementation of continuous glucose monitoring for patients with Insulin-Treated type 2 diabetes: a national survey of primary care providers

OBJECTIVES

To identify determinants of continuous glucose monitoring (CGM) implementation from primary care providers' (PCPs') perspectives and examine the associations of these determinants with both PCP intent to discuss CGM with eligible patients and facility-level uptake of CGM.

STUDY DESIGN

Cross-sectional survey.

METHODS

A survey about CGM implementation for patients with type 2 diabetes on insulin was distributed to all PCPs in the Department of Veterans Affairs (VA) health system from October 2023-April 2024. Multi-item scales measured perceived clinical benefits of CGM, workload capacity, knowledge about CGM, access to CGM resources, and support from leadership and other services. Responses were on a 5-point Likert scale from "Strongly Disagree" to "Strongly Agree". An item asked about likelihood of initiating discussions about starting CGM. Facility-level uptake was measured using VA administrative data. Multivariable regression models assessed the relationship between determinants of CGM implementation and both PCP intent to discuss CGM and facility-level uptake.

RESULTS

Of 1373 respondents, most perceived clinical benefits of CGM (79% "Agree" + "Strongly Agree"). Very few indicated sufficient access to resources (8%) and support from leadership & other services (5%). After adjustment for respondent characteristics, the scale most strongly associated with PCP intent to discuss CGM was PCP Knowledge About CGM (B = 0.54, P <.001). Facility uptake of CGM was associated with Clinical Benefits of CGM (B = 0.10, P =.026) and Support from Leadership & Other Services (B = 0.18, P <.001).

CONCLUSIONS

PCPs perceive benefits to CGM but lack sufficient knowledge, resources, and workload capacity to manage it alone. PCP education about CGM use and interprofessional support for uptake may increase the likelihood that eligible patients use CGM.

Adapting the NIMHD Research Framework for Type 2 Diabetes-Related Disparities

PURPOSE OF REVIEW

Type 2 diabetes (T2D) disproportionately impacts minority populations. The National Institute on Minority Health and Health Disparities (NIMHD) developed a research framework to encourage health disparities research that considers a multi-level, multi-domain perspective. The purpose of this review was to describe evidence on the levels and domains that influence T2D disparities among minority populations and use this information to adapt the NIMHD Research Framework for T2D.

RECENT FINDINGS

Screening identified 108 articles published between 2017 and 2023 covering 74,354,597 participants. Articles were classified under the following domains, Biological (18), Behavioral (22), Physical/Built Environment (19), Sociocultural Environment (42), and Health Care System (31). Article levels of influence included Individual (73), Interpersonal (18), Community (36), and Societal (10). Findings were used to adapt the NIMHD Research Framework with an eye towards advancing T2D-related health equity. The results of this review confirm the complex nature of T2D-related disparities and support the notion that drivers operate within and between multiple levels and multiple domains to influence T2D-related outcomes across the lifespan.

Expanding Access to Continuous Glucose Monitoring Through Empowering Primary Care: A Joint Endocrinology-Primary Care Quality Improvement Project

BACKGROUND

Despite guideline recommendations to offer continuous glucose monitoring (CGM) to all patients with diabetes using insulin, prescription rates for CGM remain low in primary care.

OBJECTIVE

This quality improvement project aimed to improve access to CGM in primary care for patients with type 2 diabetes on insulin.

DESIGN

This was a quality improvement project conducted by a joint endocrinology/primary care team at a single primary care community health clinic. After defining the problem through process mapping, driver diagrams, and Pareto charts, several interventions were trialed through Plan-Do-Study-Act (PDSA) cycles.

PARTICIPANTS

The study team consisted of four endocrinologists, two primary care providers (MD/NP), the lead primary care nurse, and the primary care population health specialist.

INTERVENTIONS

Interventions included a directory for durable medical equipment (DME) suppliers, nursing education with device company representatives, a new electronic ordering system for DME, and a nursing outreach program to patients eligible for CGM.

MAIN MEASURES

The primary outcome was percentage of eligible patients using CGM. Process measures included the number of CGM orders started weekly. Nursing comfort with CGM, knowledge of CGM, and perceptions of communication with DME suppliers were also measured.

KEY RESULTS

The percentage of eligible patients using CGM increased from 28 to 42%, and the percentage of patients using CGM started in primary care increased from 8 to 14%. Weekly orders increased from 0.3 per week to 2.3 per week. Nursing reported feeling more comfortable and knowledgeable about CGM after the interventions and reported improved communication with DME suppliers.

CONCLUSIONS

CGM is known to improve outcomes for patients with diabetes but is an underutilized tool in primary care. Collaborative quality improvement projects between endocrinology and primary care can rapidly build capacity within primary care to prescribe CGM and expand access for patients with diabetes who do not have endocrinologists.

Removing barriers to management of adults with type 2 diabetes on insulin using continuous glucose monitoring in UK primary care practice: An expert consensus

AIMS

This expert consensus reviews the reality of primary care clinical management of people with type 2 diabetes (T2D) on non-intensive insulin therapy, with an emphasis on the use of continuous glucose monitoring (CGM) technology for effective care in this participant group. Here, we identify key unmet needs for skills and systems development within this frontline healthcare setting, along with major challenges and opportunities associated with managing these changes effectively.

METHODS

The authors participated in two primary care consensus panels held on 28 November 2023 and on 21 May 2024. The focus for these expert panels was to understand the unmet needs within primary care to manage adults with T2D treated with non-intensive insulin therapy and incorporating the use of CGM systems. A Delphi Survey was undertaken among a wider group of Primary Care Diabetes Technology Network members in the United Kingdom, to understand prevalent attitudes to management of adults with T2D on insulin and using CGM in primary care. Based on these activities, a series of consensus statements were tested in a second Delphi Survey.

RESULTS

The activities described, involving primary care healthcare professionals (HCPs) with expertise in diabetes management, identified a series of training and educational needs within UK general practice that are central to skills development for the care of adults with T2D on insulin therapy and the application of CGM technology. Potential barriers to effective primary care management of people with T2D using CGM devices were identified. Areas of concern included confidence in national and local guidelines for the management of T2D using CGM systems, lack of experience on the part both of HCPs and people with T2D, clinical workflows and systems, as well as inbuilt resistance to change among primary care teams. However, the expert group were clear that the goal of providing care for people with T2D on non-intensive insulin therapy using CGM technology as standard of care could be met (94.3%, n = 33). This will deliver clinical benefits for people with T2D, and improvements to clinical workflows in primary care. Cost-savings to the health service were also identified as an outcome.

CONCLUSIONS

The need to adapt to the management of people with T2D on insulin therapy puts significant pressure on current workflows and skills for primary care teams. Steps in overcoming these immediate pressures, to ensure effective clinical management of people with T2D, are discussed, along with a series of consensus statements that identify the key areas of change to manage. Ultimately, the great majority of expert primary care HCPs were confident or very confident that using CGM technology will become the standard of care for people with T2D treated with insulin in primary care.

Travel patterns, pretravel preparation, and travel-associated morbidity in travelers with diabetes in Taiwan

BACKGROUND

International travel poses unique health risks for individuals with diabetes. This study explored their travel patterns, preparations, and morbidity, as well as identify factors influencing pre-travel health-seeking behavior from primary healthcare providers.

METHODS

This cross-sectional, questionnaire-based study recruited adults with diabetes who had traveled internationally within the past 12 months. Data on sociodemographic and clinical characteristics, travel patterns, preparations, and travel-associated morbidity were collected via questionnaires and electronic medical records. Multivariate logistic regression analyses were conducted to identify predictors of patients informing physicians about travel plans.

RESULTS

Among 250 participants (median age: 65 years [57-69]; median HbA1c: 7.1 % [6.6-7.9]), 16.4 % were on insulin therapy. The median travel duration was 6 days (5-10), with a median of one time zone crossed. Insulin-treated individuals tended to plan shorter trips to closer destinations than their non-insulin-treated counterparts. While 70.8 % of participants carried medicines for acute illness, only 10.8 % informed their primary care physicians about travel plans, and 11.2 % experienced travel-associated morbidity, including acute illness, falls, and hypoglycemia. Predictors of informing physicians about travel plans included travel duration exceeding ten days (OR: 4.87, 95 % CI: 1.34-17.63), insulin therapy (OR: 4.37, 95 % CI: 1.21-15.80), taking preventive measures against hypoglycemia during travel (OR: 3.40, 95 % CI: 1.26-9.14), and good antidiabetic medication adherence (OR: 2.96, 95 % CI: 1.10-7.96).

CONCLUSIONS

This study underscored the impact of diabetes self-care practices on pre-travel health-seeking behavior and demonstrated how insulin therapy shapes travel patterns, highlighting the need for reinforced self-management skills and targeted pre-travel guidance, especially for insulin-treated patients.

Diabetes remission in newly diagnosed type 2 diabetes mellitus through short-term continuous subcutaneous insulin infusion intensive therapy combined with low-carbohydrate diet treatment

AIM/INTRODUCTION

To evaluate the therapeutic efficacy short-term continuous subcutaneous insulin infusion (CSII) intensive therapy combined with a low-carbohydrate diet (LCD) for diabetes remission in patients with newly diagnosed type 2 diabetes mellitus.

MATERIALS AND METHODS

This study included patients newly diagnosed with type 2 diabetes mellitus, who were randomly divided into two groups: conventional (conventional CSII + traditional lifestyle guidance); and intensive (intensive CSII + LCD lifestyle guidance). CSII was used for blood glucose control, with continuous glucose monitoring (CGM) used to monitor blood glucose levels. The primary outcome measure was hemoglobin A1c (HbA1c) level; secondary outcomes included body weight, body mass index (BMI), waist circumference, glycemic control, and biochemical indices.

RESULTS

The time in range (TIR) in the intensive treatment group was greater than that in the conventional treatment group (P < 0.05). There was no significant difference in the incidence of hypoglycemia between the two groups (P > 0.05). Compared with the conventional treatment group, diabetes remission rates were significantly greater in the intensive treatment group (P < 0.05). In the intensive treatment group, fasting plasma glucose (FPG), HbA1c, Homeostasis Model assessment of Insulin Resistance (HOMA-IR), triglycerides (TG), low-density lipoprotein cholesterol (LDL-c), and changes in body weight, BMI, visceral fat area (VFA), and subcutaneous fat area (SFA) decreased significantly (P < 0.05). FPG, HOMA-IR, TG, LDL-c, and changes in body weight, BMI, waist circumference, and VFA were significantly correlated with HbA1c levels (P < 0.05).

CONCLUSIONS

The combination of intensive CSII and LCD lifestyle guidance had been improved the remission rate in patients with newly diagnosed type 2 diabetes mellitus.

Effectiveness of Physical Activity Support Combined With Continuous Glucose Monitoring by a Physical Therapist in Preconception Care for a Woman With Type 2 Diabetes Mellitus: A Case Study

Diabetes mellitus represents a major public health challenge worldwide, with type 2 diabetes mellitus (T2DM) accounting for the majority of cases. Urbanization and lifestyle changes are reportedly contributing to the increasing incidence of T2DM worldwide. The prevalence of T2DM is also increasing among women who wish to become pregnant, owing to the growing overall proportion of women with T2DM, the increasing prevalence of obesity, and the rising average age of childbirth. Preconception care is warranted in this demographic to optimize glycemic control, improve pregnancy outcomes, and reduce the risk of congenital anomalies and perinatal complications. Educational support that includes not only glycemic control but also increased physical activity (PA) and lifestyle modifications is important to delivering effective preconception care. Herein, we report the case of a woman in her 30s with T2DM, hypertension, and dyslipidemia. Her early glycemic control was suboptimal (glycated hemoglobin: 8.9%, time in range (TIR): 36.6%), her pregnancy preparation was delayed, and a personalized PA program was eventually introduced that included continuous glucose monitoring (CGM) reviewed by a physical therapist. The intervention lasted four months and included continuous feedback and adjustments to the timing, intensity, and activity goals of the patient's exercise regimen based on her CGM trends. A specific PA target of 8,000-10,000 steps per day was established to promote increased daily movement. The intervention also incorporated a combination of aerobic exercise (walking) and resistance training tailored to the patient's condition and lifestyle. This intervention led to improvements in her blood glucose markers, treatment satisfaction related to diabetes, health-related quality of life, and independence. The patient's TIR increased from 36.6% to 77%, and her PA increased from 2500 to 9500 steps/day. This case study highlights the potential of CGM to promote real-time feedback and behavior modification in patients with T2DM, particularly those attempting pregnancy. PA support combined with CGM can effectively manage blood glucose levels, increase motivation, and improve overall health in ways that are highly beneficial to integrate into preconception care regimens. This study emphasizes that PA support combined with CGM is effective for increasing glycemic control and PA levels, thus improving lifestyle habits and preparing women with T2DM for pregnancy. We advocate for the wider adoption of PA support interventions combined with CGM by physical therapists as a standard practice in preconception care and emphasize the role of this approach in terms of improving long-term metabolic health prior to conception. Further research is warranted to validate these findings and optimize intervention protocols.

Evaluation of the Effectiveness of Continuous Glucose Monitors on Glycemic Control in Patients With Type 2 Diabetes Receiving Institutional Financial Assistance

BACKGROUND

Current guidelines suggest utilizing continuous glucose monitoring (CGM) to improve hemoglobin A1c (HbA1c) in patients with diabetes. Financial cost remains a barrier to implementation. Medicare coverage criteria include all patients with diabetes treated with at least one injection of insulin per day, while Washington Medicaid is more restrictive. There remains a paucity of literature examining effectiveness of CGMs on clinical outcomes among patients with type 2 diabetes with lower incomes.

METHODS

This is a single-center, retrospective, observational study including adults with type 2 diabetes receiving institutional financial assistance for CGMs. A cohort with no CGM use is included for comparison. The primary outcome is change in HbA1c approximately three months after CGM implementation from baseline. Secondary outcomes include mean differences in number of antidiabetic agents and changes in insulin dose prior to and after CGM implementation.

RESULTS

Among the CGM cohort, most patients were of Hispanic ethnicity (77%) and a majority had no insurance (77%). The average HbA1c prior to CGM implementation was 8.3% and three months post-CGM was 7.7%, with a mean difference of -0.6% (P = .004). There were no statistically significant differences in the average number of antidiabetic agents, total daily dosages of insulin, or mean differences in the number of emergency room visits or hospitalizations prior to and post-implementation of a CGM.

CONCLUSION

Overall, there is a statistical and clinical improvement in HbA1c before and after implementation of CGMs in patients with type 2 diabetes who meet Medicaid criteria for CGM coverage receiving financial assistance.

Continuous Glucose Monitoring for Hyperglycemia in Critically Ill Patients: A Randomized Controlled Trial

BACKGROUND

Continuous glucose monitors (CGMs) could potentially improve management of hyperglycemia compared with standard point-of-care glucose monitoring for critically ill patients. However, there is limited evidence to support routine use of CGMs in the ICU.

RESEARCH QUESTION

In critically ill patients with hyperglycemia, do CGMs improve time within target glucose range compared with standard of care?

STUDY DESIGN AND METHODS

This was an investigator-initiated, single-center, parallel-group, open-label, randomized controlled trial. Adult patients admitted to a medical or surgical ICU who had diabetes mellitus or hyperglycemia and were treated with insulin were eligible for enrollment. Participants were randomly assigned to have glucose monitoring performed with a CGM (intervention group) or standard of care (control group). Groups were compared for glycemic control and other relevant outcomes. The primary outcome for the study was percentage of time within the normoglycemic range, defined as 70 to 180 mg/dL (3.9-10 mmol/L).

RESULTS

Eighty-five participants were enrolled and randomized to study groups, with 43 participants in the intervention (CGM) group and 42 patients in the control (standard of care) group. For the primary outcome, there was no statistically significant difference between the intervention group (mean ± SD, 60.5% ± 30.5%) and the control group (mean ± SD, 61.4% ± 28.3%) in time within the goal glucose range (mean difference, -0.9%; 95% CI, -13.6 to 11.8; P = .9). Except for patient satisfaction, there were no statistically significant differences between groups for secondary and exploratory outcomes.

INTERPRETATION

The results of this study do not support CGMs as a superior method for routine glucose monitoring in the ICU compared with standard of care.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT05442853; URL: www.

CLINICALTRIALS

gov.

Fruit Carbohydrates and Their Impact on the Glycemic Index: A Study of Key Determinants

Background: Fruits are a convenient and natural source of carbohydrates that can rapidly affect blood sugar levels and the glycemic index (GI). The GI plays a crucial role in the management of chronic diseases, including diabetes, obesity, hyperglycemia, and diet-related illnesses. Despite there being several health benefits linked with consuming fruits, it remains unclear which specific components of fruits are the key determinants that significantly influence the GI. Methods: This study retrospectively examined the relationship between different types of carbohydrates and the GI of various fruits to determine their correlation. The fruits' sugar and fiber contents were identified from available public databases, the U.S. Department of Agriculture (USDA), FooDB, PubMed, and published sources. Results: Previously, the GI was determined by the available carbohydrates, which include different types of sugar. In this study, individual hexose sugars, along with the total carbohydrates and dietary fiber, were examined. The results indicated a strong correlation between fructose and the GI, whereas glucose and total glucose did not exhibit such a correlation. The total carbohydrate-to-fiber ratio displayed a stronger correlation (R = 0.57 and p > 0.0001) with the GI compared to glucose alone (R = 0.37; p = 0.01) or the total glucose (R = 0.45; p = 0.0009) with the consideration of fiber, while the scattering of data points around the regression line suggested that factors beyond the total carbohydrate and fiber also contribute to determining the GI. Conclusions: This study demonstrated that individual hexose sugars, especially fructose, significantly influence the GI. These findings suggest that the carbohydrate-to-fiber ratio may offer a more accurate and reliable metric for determining the GI than traditional methods. Further research is warranted to investigate the specific contribution of dietary fiber components, fruit texture, micronutrients, vitamins, genetic predispositions, gut microbiota, and the body's physiological status to gain a deeper understanding of GI regulation.

The Utility of Smart Multiple Daily Injection Systems in Intensive Insulin-Treated People With Diabetes: An Italian Expert Consensus

BACKGROUND

Smart systems for multiple daily injections (Smart MDI) integrate continuous glucose monitoring, connected insulin pens, smartphone apps, and cloud-based data storage to provide bolus and corrective dose suggestions, reminders/alerts, automatic tracking and sharing of insulin therapy, and glycemic data to users, caregivers, and providers. This is an expert consensus on the clinical value of Smart MDI and critical points for implementation in adults and children/adolescents with diabetes.

METHODS

A nominal group technique combined with the estimate-talk-estimate approach was employed to achieve consensus among panel members from the Italian Intersociety Technology and Diabetes Study Group with expertise in pediatric and adult diabetes care.

RESULTS

The expert consensus indicated that glycemic profiles can be improved by using bolus dose suggestions based on glucose values, planned meals, the insulin-to-carbohydrate ratio, correction factors, and consideration of insulin-on-board. Automatic remote sharing of patient data on glycemia and insulin therapy allows clinicians to make more appropriate and timely therapeutic recommendations based on objective data. Dose tracking, bolus reminders/alerts, and reduced hypoglycemia and associated anxiety achieved through Smart MDI may improve adherence.

CONCLUSIONS

Smart MDI can reduce treatment burden while improving the daily experiences and glycemic outcomes for adults and children/adolescents with type 1 or type 2 diabetes. However, high-quality clinical data are lacking, and more evidence is needed to compare the effects of Smart MDI and other advanced insulin delivery systems on glycemic and patient-reported outcomes.

Time in tight range: A key metric for optimal glucose control in the era of advanced diabetes technologies and therapeutics

Compared to glycated haemoglobin A1c (HbA1c), the rapidly developing continuous glucose monitoring (CGM) technology provides more detailed information about glycemic control. Amongst the new glucose metrics derived from CGM, time in target range of 3.9-10.0 mmol/L (time in range, TIR) has been widely used for the assessment of glucose control. In recent years, the rise of new technologies and therapies including advanced hybrid closed-loop automated insulin delivery systems and new hypoglycemic drugs has made it possible to achieve better glycemic control. In this context, the concept of time in tight range (TITR), defined as the percentage of time spent in target glucose range of 3.9-7.8 mmol/L, has gained increasing attention. Whilst TITR is highly correlated with TIR, there are still differences between the two metrics. These differences make TITR a more appropriate indicator in certain situations, such as when glucose levels are close to normal or when tighter glycemic control is required. This review summarizes recent studies related to TITR.

Continuous glucose monitoring guides glucagon-like peptide 1-based therapy use and optimization in people with type 2 diabetes

Type 2 diabetes (T2D) is a large and growing epidemic. Importantly, new technologies and pharmaceutical options are improving the management of T2D. Continuous glucose monitoring (CGM) systems have advanced glucose-sensing technology, which has made it easier for users to monitor their glucose levels. Glucagon-like peptide 1-based therapies and dual agonists have similarly revolutionized the treatment of T2D. In this article, we present four cases of individuals with T2D who, in collaboration with their healthcare provider, used the data from their CGM systems to inform therapy changes, including the initiation and titration of glucagon-like peptide 1-based therapies. Combined use of CGM systems and glucagon-like peptide 1-based therapies could improve people's diabetes as well as their overall health.

Insulin Pen Administration Efficacy and Safety in an Older Patient

Objective To describe a successful pharmacist-led intervention to effectively and safely provide education and pharmacotherapy management for an older patient with uncontrolled type 2 diabetes mellitus (T2DM) who failed to remove the needle shield on insulin pens for injection. Setting: Family medicine residency clinic. Practice Description: The clinic, part of a major urban health system, consists of 27 medical residents, 15 attending physicians, and 1 ambulatory care pharmacist managing chronic diseases collaboratively. It primarily serves low-income patients in a Midwest city. Practice Innovation: A 93-year-old White female with T2DM, receiving insulin therapy, was referred to the ambulatory care pharmacist by her physician for diabetes management. The patient had been hospitalized recently for hyperosmolar hyperglycemic state with a hemoglobin A1c of 15.9%. The pharmacist identified a failure to remove the needle shield on the insulin pen resulting in ineffective insulin administration, which caused persistent hyperglycemia and subsequent hospitalizations. This also posed a safety concern for severe hypoglycemia if proper administration resumed without adjusting the inflated dosing. The pharmacist used demonstration devices and the teach-back method to provide education and implement pharmacotherapy adjustments, resulting in effective and safe insulin administration. Main Outcome Measurements: Change in diabetes medication regimen, home blood glucose readings including continuous glucose monitor data, hemoglobin A1c results, frequency of hypoglycemic episodes, and number of hospitalizations for T2DM. Results: Over seven months, dose adjustments to basal insulin, combined with proper administration technique and the addition of empagliflozin, resulted in a hemoglobin A1c below 7%, with no severe hypoglycemia or diabetes-related hospitalizations. Conclusion: Medication errors, including insulin administration errors, highlight the need for thorough education in insulin therapy management. Education and monitoring empower older patients to self-manage diabetes safely and effectively, aligning with guidelines. Further research is required to identify optimal strategies for educating older patients on self-managing T2DM with insulin therapy.

Dulce Digital-Me: results of a randomized comparative trial of static versus adaptive digital interventions for Latine adults with diabetes

OBJECTIVE

To compare the effectiveness of a static, text-based diabetes education and support intervention (Dulce Digital, DD) versus a dynamic approach with personalized feedback and goal setting (Dulce Digital-Me, DD-Me) in improving diabetes outcomes.

DESIGN AND METHODS

Comparative effectiveness trial in 310 Latine adults with poorly managed type 2 diabetes in a Federally Qualified Health Center in Southern California, randomized to DD, DD-Me-Auto (algorithm-driven text-based personalized feedback), or DD-Me-Tel (coach delivered personalized feedback). Changes in HbA1c (primary outcome), low-density lipoprotein-cholesterol, systolic blood pressure, and patient-reported outcomes were examined across 6 and 12 months, with the primary comparison being DD versus DD-Me (combined automated and telephonic).

RESULTS

Participants were 52.1 (±10.2) years old, 69.7% female, with HbA1c 9.3% (±1.6) at baseline. Across groups, there was a statistically significant improvement in HbA1c at 6 months (mean∆ per month = -0.17, 95% CI -0.20, -0.14; P < .001) and 12 months (mean∆ per month = -0.07, 95% CI -0.09, -0.05; P < .001). However, there were no time-by-group interaction effects indicating group differences in clinical outcomes across 6 or 12 months. The DD-Me groups showed greater improvements across time than the DD group for diabetes self-management behaviors.

CONCLUSIONS

Static and adaptive digital interventions for Latine adults with type 2 diabetes had similar and clinically significant effects on HbA1c across 12 months. Simple digital approaches can be integrated within primary care-based chronic care models to reduce diabetes disparities.

CLINICALTRIALS.GOV REGISTRATION

NCT03130699, Initial Release 04/24/2017, https://clinicaltrials.gov/ct2/show/NCT03130699?term=NCT03130699&draw=2&rank=1.

Improved Glycemic Control in Insulin-Treated Individuals With Poorly Controlled Type 2 Diabetes Through Combined Structured Education With Real-Time Continuous Glucose Monitoring

BACKGROUND

We evaluated the efficacy of structured individualized education combined with real-time continuous glucose monitoring (rt-CGM, Dexcom G6) in improving glycemic outcomes in insulin-treated adults with poorly controlled type 2 diabetes (T2D).

METHODS

This multicenter, 16-week, single-arm study included 66 adults with T2D (multiple daily insulin [MDI]: 33; basal insulin: 33) with a ≥7.8%. Each cohort comprised 15 participants aged ≥60 years. The participants attended four educational sessions. The primary outcome was a change in glycated hemoglobin (HbA1c) levels between baseline and week 16.

RESULTS

Sixty-four individuals were included in this study, with a mean age of 58.3 ± 12.4 years. The mean HbA1c levels decreased from 9.0% at baseline to 7.1% at 16 weeks in the MDI group (difference: -1.8%, 95% confidence interval [CI] = -2.3 to -1.3) and from 8.8% to 7.0% in the basal insulin group (difference: -1.8%, 95% CI = -2.1 to -1.4). In the total population, the mean time in range 70 to 180 mg/dL increased by 25.2% (6 hours 4 minutes, 95% CI = 20.6 to 29.8), whereas the time in tight range 70 to 140 mg/dL increased by 17.3% (4 hours 10 minutes, 95% CI = 14.0 to 20.7). Both groups maintained a target of <1% of the time below the range of <54 mg/dL. Improvements in HbA1c and CGM metrics were comparable between individuals aged ≥60 years and those aged <60 years (all P-values for interaction >.1).

CONCLUSIONS

In adults with poorly controlled insulin-treated T2D, rt-CGM use with structured education significantly improved the HbA1c and CGM metrics, primarily by reducing hyperglycemia, regardless of age.

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.

"Life with Diabetes": A Pilot Study on an Experiential Continuous Glucose Monitoring Curriculum for Resident Physicians

BACKGROUND

The use of technology in diabetes mellitus (DM) management has been growing. The indications and coverage for continuous glucose monitoring (CGM) have increased. Primary care (PC) clinics, including resident continuity clinics, are the frontline for DM management; however, they struggle to adopt CGM.

AIM

To implement a CGM curriculum to resident physicians to improve knowledge and confidence.

SETTING

An internal medicine (IM) resident PC clinic in an urban academic medical institution.

PARTICIPANTS

Twenty-four IM residents.

DESCRIPTION

We designed a curriculum that included a lecture about CGM indications, interpretation, ordering, and insurance consideration; and a voluntary, experiential learning module in which the residents wore a CGM.

EVALUATION

We conducted a retrospective pre-post survey with a 4-point Likert scale. Average self-reported scores in knowledge increased for CGM (1) indications from 1.85 to 3.45, (2) ordering from 1.35 to 3.05, (3) functioning from 2.20 to 3.50, and (4) data interpretation from 1.85 to 3.25 (all p < 0.0001). Confidence for "describing CGM monitoring" and "fielding questions about CGM" increased from 2.25 to 3.65 (p < 0.0001) and 1.90 to 3.30 (p < 0.0001).

DISCUSSION

Given the demand for DM management in the PC setting, this targeted CGM curriculum has promise to help residents adopt CGM into their practice.

Consensus Report on the Use of Continuous Glucose Monitoring in Chronic Kidney Disease and Diabetes

This report represents the conclusions of 15 experts in nephrology and endocrinology, based on their knowledge of key studies and evidence in the field, on the role of continuous glucose monitors (CGMs) in patients with diabetes and chronic kidney disease (CKD), including those receiving dialysis. The experts discussed issues related to CGM accuracy, indications, education, clinical outcomes, quality of life, research gaps, and barriers to dissemination. Three main goals of management for patients with CKD and diabetes were identified: (1) greater use of CGMs for better glycemic monitoring and management, (2) further research evaluating the accuracy, feasibility, outcomes, and potential value of CGMs in patients with end-stage kidney disease (ESKD) on hemodialysis, and (3) equitable access to CGM technology for patients with CKD. The experts also developed 15 conclusions regarding the use of CGMs in this population related to CGMs' unique delivery of both real-time information that can guide monitoring and management of glycemia and continuous and predictive data in this population, which is at higher risk for hypoglycemia and hyperglycemia. The group noted three major clinical gaps: (1) CGMs are not routinely prescribed for patients with diabetes and CKD; (2) CGMs are not approved by the United States Food and Drug Administration (FDA) for patients with diabetes who are on dialysis; and (3) CGMs are not routinely available to all of those who need them because of structural barriers in the health care system. These gaps can be improved with greater stakeholder collaboration, education, and awareness brought to the use of CGM technology in CKD.