Effectiveness of 3-day continuous glucose monitoring for improving glucose control in type 2 diabetic patients in clinical practice

Professional continuous glucose monitoring in patients with diabetes mellitus: A systematic review and meta-analysis

AIM

To evaluate the effect on glucose control of professional continuous glucose monitoring (p-CGM)-based care as compared with standard care in the management of patients with type 1 and type 2 diabetes.

MATERIALS AND METHODS

The PubMed database was searched comprehensively to identify prospective or retrospective studies evaluating p-CGM as a diagnostic tool for subsequent implementation of lifestyle and/or medication changes and reporting glycated haemoglobin (HbA1c) as an outcome measure.

RESULTS

We found 872 articles, 22 of which were included in the meta-analysis. Overall, the use of p-CGM was associated with greater HbA1c reduction from baseline (-0.28%, 95% confidence interval [CI] -0.36% to -0.21%, I²  = 0%, P < 0.00001) than usual care, irrespective of type of diabetes, length of follow-up, frequency of continuous glucose monitoring (CGM) use and duration of CGM recording. In the few studies describing CGM-derived glucose metrics, p-CGM showed a beneficial effect on change in time in range from baseline (5.59%, 95% CI 0.12 to 11.06, I²  = 0%, P = 0.05) and a neutral effect on change in time below the target range from baseline (-0.11%, 95% CI -1.76% to 1.55%, I²  = 33%, P = 0.90).

CONCLUSIONS

In patients with type 1 and type 2 diabetes, p-CGM-driven care is superior to usual care in improving glucose control without increasing hypoglycaemia.

Biological and Clinical Impacts of Glucose Metabolism in Pancreatic Ductal Adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer type as it is prone to metastases and is difficult to diagnose at an early stage. Despite advances in molecular detection, its clinical prognosis remains poor and it is expected to become the second leading cause of cancer-related deaths. Approximately 85% of patients develop glucose metabolism disorders, most commonly diabetes mellitus, within three years prior to their pancreatic cancer diagnosis. Diabetes, or glucose metabolism disorders related to PDAC, are typically associated with insulin resistance, and beta cell damage, among other factors. From the perspective of molecular regulatory mechanisms, glucose metabolism disorders are closely related to PDAC initiation and development and to late invasion and metastasis. In particular, abnormal glucose metabolism impacts the nutritional status and prognosis of patients with PDAC. Meanwhile, preliminary research has shown that metformin and statins are effective for the prevention or treatment of malignancies; however, no such effect has been shown in clinical trials. Hence, the causes underlying these conflicting results require further exploration. This review focuses on the clinical significance of glucose metabolism disorders in PDAC and the mechanisms behind this relationship, while also summarizing therapeutic approaches that target glycolysis.

Lack of Acceptance of Digital Healthcare in the Medical Market: Addressing Old Problems Raised by Various Clinical Professionals and Developing Possible Solutions

Various digital healthcare devices and apps, such as blood glucose meters, blood pressure monitors, and step-trackers are commonly used by patients; however, digital healthcare devices have not been widely accepted in the medical market as of yet. Despite the various legal and privacy issues involved in their use, the main reason for its poor acceptance is that users do not use such devices voluntarily and continuously. Digital healthcare devices generally do not provide valuable information to users except for tracking self-checked glucose or walking. To increase the use of these devices, users must first understand the health data produced in the context of their personal health, and the devices must be easy to use and integrated into everyday life. Thus, users need to know how to manage their own data. Medical staff must teach and encourage users to analyze and manage their patient-generated healthcare data, and users should be able to find medical values from these digital devices. Eventually, a single customized service that can comprehensively analyze various medical data to provide valuable customized services to users, and which can be linked to various heterogeneous digital healthcare devices based on the integration of various health data should be developed. Digital healthcare professionals should have detailed knowledge about a variety of digital healthcare devices and fully understand the advantages and disadvantages of digital healthcare to help patients understand and embrace the use of such devices.

American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus

OBJECTIVE

To provide evidence-based recommendations regarding the use of advanced technology in the management of persons with diabetes mellitus to clinicians, diabetes-care teams, health care professionals, and other stakeholders.

METHODS

The American Association of Clinical Endocrinology (AACE) conducted literature searches for relevant articles published from 2012 to 2021. A task force of medical experts developed evidence-based guideline recommendations based on a review of clinical evidence, expertise, and informal consensus, according to established AACE protocol for guideline development.

MAIN OUTCOME MEASURES

Primary outcomes of interest included hemoglobin A1C, rates and severity of hypoglycemia, time in range, time above range, and time below range.

RESULTS

This guideline includes 37 evidence-based clinical practice recommendations for advanced diabetes technology and contains 357 citations that inform the evidence base.

RECOMMENDATIONS

Evidence-based recommendations were developed regarding the efficacy and safety of devices for the management of persons with diabetes mellitus, metrics used to aide with the assessment of advanced diabetes technology, and standards for the implementation of this technology.

CONCLUSIONS

Advanced diabetes technology can assist persons with diabetes to safely and effectively achieve glycemic targets, improve quality of life, add greater convenience, potentially reduce burden of care, and offer a personalized approach to self-management. Furthermore, diabetes technology can improve the efficiency and effectiveness of clinical decision-making. Successful integration of these technologies into care requires knowledge about the functionality of devices in this rapidly changing field. This information will allow health care professionals to provide necessary education and training to persons accessing these treatments and have the required expertise to interpret data and make appropriate treatment adjustments.

A head-to-head comparison of personal and professional continuous glucose monitoring systems in people with type 1 diabetes: Hypoglycaemia remains the weak spot

To compare the performance of a professional continuous glucose monitoring (proCGM) and a personal continuous glucose monitoring (persCGM) system worn in parallel under standardized conditions in individuals with type 1 diabetes (T1D), two CGM systems (iPro2 - proCGM; Minimed 640G - persCGM) worn in parallel using the same sensor (Enlite 2) were compared. Ten people with T1D were included in this single-centre, open-label study in which CGM performance was evaluated. The study consisted of a 24-hours inpatient phase (meals, exercise, glycaemic challenges) and a 4-day home phase. Analyses included fulfilment of ISO 15197:2013 criteria, mean absolute relative difference (MARD), Parkes Error Grid and Bland-Altman plots. During the inpatient stay, ISO 15197:2013 criteria fulfilment was 58.4% (proCGM) and 57.8% (persCGM). At home, the systems met ISO 15197:2013 criteria by 66.5% (proCGM) and 65.3% (persCGM). No difference of MARD in inpatient phase (19.1 ± 16.7% vs. 19.0 ± 19.6; P = 0.83) and home phase (18.6 ± 26.8% vs. 17.4 ± 21.3%, P = 0.87) was observed. All sensors performed less accurately during hypoglycaemia. ProCGM and persCGM showed similar performance during daytime and night-time for the inpatient and the home phase. However, sensor performance was reduced during hypoglycaemia for both systems.

Effects of Dapagliflozin on 24-Hour Glycemic Control in Patients with Type 2 Diabetes: A Randomized Controlled Trial

BACKGROUND

Glycated hemoglobin (HbA1c) and measures of short-term glycemia do not fully capture daily patterns in plasma glucose dynamics. This study evaluated 24-h glycemic profiles in patients with type 2 diabetes (T2D) initiated on dapagliflozin treatment using continuous glucose monitoring (CGM).

METHODS

This randomized double-blind placebo-controlled multicenter parallel-design 4-week study compared dapagliflozin (10 mg/d; n = 50) with placebo (n = 50) in adult patients with T2D uncontrolled (HbA1c 7.5%-10.5%) on either stable doses of metformin monotherapy (≥1500 mg/d) or insulin (≥30 U/d with or without up to two oral antidiabetes drugs). CGM was used to measure 24-h glycemic profiles for 7 days pretreatment and during week 4 of treatment. The primary outcome was change from baseline in 24-h mean glucose (MG) at week 4.

RESULTS

The 24-h MG decreased 18.2 mg/dL with dapagliflozin and increased 5.8 mg/dL with placebo (P < 0.001). The proportion of time spent in the target glucose range (70-180 mg/dL) increased significantly with dapagliflozin versus placebo (69.6% vs. 52.9%; P < 0.001), with a small (0.3%) increase in time spent in the hypoglycemic range (<70 mg/dL), driven by those on background insulin therapy. Dapagliflozin reduced postprandial glucose and significantly decreased overall glucose variability. Few events of symptomatic hypoglycemia occurred. The most common adverse event was urinary tract infection (6% in each treatment arm).

CONCLUSIONS

Compared with placebo, dapagliflozin improved measures of glycemic control and variability as assessed by CGM. Glycemic improvements were more pronounced in the group on background metformin than those receiving basal insulin.

The Effectiveness of Continuous Glucose Monitoring in Patients with Type 2 Diabetes: A Systematic Review of Literature and Meta-analysis

BACKGROUND

Continuous glucose monitoring (CGM) provides glucose trend information that can be used to guide treatment and motivate patients with diabetes. Currently, the evidence on effectiveness of CGM in patients with type 2 diabetes is debatable. We aim to provide a systematic review and meta-analysis to synthesize current evidence of effectiveness of CGM in adults with type 2 diabetes.

MATERIALS AND METHODS

Cochrane, Embase, PubMed, and Web of Science were searched to include all studies that reported effectiveness of CGM in terms of HbA1c in adults aged 18 and older, with type 2 diabetes, on any treatment for diabetes. Heterogeneity (I²) was used to determine the variability between studies. All data were analyzed using Review Manager 5.3 software.

RESULTS

Seven randomized controlled trials and three cohort studies, involving 1384 patients for real-time CGM (RT-CGM) and professional CGM (P-CGM) and 4902 patients for flash glucose monitoring (FGM), were included. RT-CGM and P-CGM were associated with a modest but statistically significant reduction in HbA1c of 0.20% (95% confidence interval [CI] -0.31 to -0.09) compared with control. Patients who received FGM had a nonsignificant reduction of 0.02% (95% CI -0.07 to 0.04) compared with control. The meta-analysis indicated a low heterogeneity between studies.

CONCLUSION

Our analysis of current evidence suggests that RT-CGM and P-CGM are effective in improving HbA1c in adults with type 2 diabetes. Due to insufficient evidence, it is premature to form conclusions on the effectiveness of FGM. Future multicenter trials accessing the effectiveness of CGM as well as safety and cost-effectiveness may be necessary.

Clinical and economic benefits of professional CGM among people with type 2 diabetes in the United States: analysis of claims and lab data

BACKGROUND

It is estimated that one in 10 people in the US have a diagnosis of diabetes. Type 2 diabetes accounts for 95% of all cases in the US, with annual costs estimated to be $246 billion per year. This study investigated the impact of a glucose-measuring intervention to the burden of type 2 diabetes.

OBJECTIVE

This analysis seeks to understand how professional continuous glucose monitoring (professional CGM) impacts clinical and economic outcomes when compared to patients who are not prescribed professional CGM.

METHODS

This study utilized a large healthcare claims and lab dataset from the US, and identified a cohort of patients who were prescribed professional CGM as identified by CPT codes 95250 and 95251. It calculated economic and clinical outcomes 1 year before and 1 year after the use of professional CGM, using a generalized linear model.

RESULTS

Patients who utilized professional CGM saw an improvement in hemoglobin A1C. The "difference-in-difference" calculation for A1C was shown to be -0.44%. There was no statistically significant difference in growth of total annual costs for people who used professional CGM compared to those who did not ($1,270, p = .08). Patients using professional CGM more than once per year had a -$3,376 difference in the growth of total costs (p = .05). Patients who used professional CGM while changing their diabetes treatment regimen also had a difference of -$3,327 in growth of total costs (p = .0023).

CONCLUSION

Significant clinical benefits were observed for patients who used professional CGM. Economic benefits were observed for patients who utilized professional CGM more than once within a 1-year period or who used it during a change of diabetes therapy. This suggests that professional CGM may help decrease rising trends in healthcare costs for people with type 2 diabetes, while also improving clinical outcomes.

Use of Continuous Glucose Monitoring in Youth-Onset Type 2 Diabetes

PURPOSE OF REVIEW

Continuous glucose monitoring (CGM) technology has long been accepted as a tool for managing glycemia in type 1 diabetes (T1D) and is receiving increased attention as a tool for monitoring glucose patterns in patients with other forms of diabetes, in particular type 2 diabetes (T2D). Recent studies in adults with T2D have shown benefits of CGM in the investigation of glycemic variability, as well as utility as a tool for improving glycemic control. The literature on CGM use in youth-onset T2D, however, is sparse. This paper reviews the various roles for CGM in T2D, with a focus on published reports of CGM use in youth-onset T2D. The gaps in knowledge are highlighted, along with a discussion regarding need for future studies of potential applications for CGM in this younger population.

RECENT FINDINGS

CGM systems provide insight into glycemic abnormalities in obese youth with and at risk for T2D. This technology has enabled examination of the relationship between free-living glycemic profiles and traditional diabetes screening tests, as well as markers of cardiometabolic risk in this high-risk population. Investigators are incorporating CGM technology into the study of T2D in youth, but interventional studies of CGM as a tool for glycemic control in youth-onset T2D are limited. Youth with T2D face a more aggressive disease than adults with T2D, and further studies utilizing advances in glucose monitoring technology to improve outcomes in this population are needed.

Assessing the Therapeutic Utility of Professional Continuous Glucose Monitoring in Type 2 Diabetes Across Various Therapies: A Retrospective Evaluation

BACKGROUND

There have been few large studies that have analyzed the effect of professional (masked) continuous glucose monitoring (P-CGM) on glycemic control in patients with type 2 diabetes (T2DM) who were on a broad spectrum of baseline therapies.

METHODS

We performed a retrospective, blinded evaluation of glycemic control in 296 T2DM adults for 6 months following a 6- to 7-day study of their glycemic profile using masked P-CGM. At baseline, 91% of the patients were on some form of insulin treatment with oral hypoglycemic agents (OHA), while 7% were on one or more OHAs without insulin, and the remaining 2% were on GLP-1RAs. On the basis of the masked CGM profile, patients were counselled on diet and exercise change(s) in their baseline diabetes therapy by our professionally trained diabetes team. They also continued to receive regular treatment advice and dose titrations through our Diabetes Tele-Management System (DTMS^®). The baseline changes in hemoglobin A1C (A1C) observed in these patients after 6 months of undergoing P-CGM was compared to a matched control group.

RESULTS

P-CGM revealed that the predominant pattern of hyperglycemia was postprandial while previously unknown hypoglycemia was found in 38% of the patients; over half of the cases of hypoglycemia were nocturnal. The mean A1C of the P-CGM group dropped from 7.5 ± 1.4% at baseline vs. 7.0 ± 0.9% at 6 months (p < 0.0001). The frequency of performing self-monitoring of blood glucose (SMBG) was also found to be significantly increased in these patients from the baseline. Meanwhile, no significant improvement in A1C was noted in the control group during the same time frame (7.7 ± 1.1% at baseline vs. 7.4 ± 1.1% at 6 months; p = 0.0663) and frequency of SMBG remained almost unchanged.

CONCLUSIONS

P-CGM can provide actionable data and motivate patients for diabetes self-care practices, resulting in an improvement in glycemic control over a wide range of baseline therapies.

The efficacy and safety of adding either vildagliptin or glimepiride to ongoing metformin therapy in patients with type 2 diabetes mellitus

OBJECTIVE

To compare the effects of either vildagliptin or glimepiride on glycemic variability, oxidative stress, and endothelial parameters in patients with type 2 diabetes mellitus (T2DM) inadequately controlled with metformin alone.

METHODS

In this randomized, open-label, parallel study, 34 patients with T2DM being treated with metformin having an HbA1c of 7.0-10.0% were allocated into either the vildagliptin or glimepiride group. A mixed-meal tolerance test and 72-hour continuous glucose monitoring were conducted, and urinary 8-iso-prostaglandinF_2α (PGF_2α) and endothelial-dependent flow-mediated dilatation (FMD) were evaluated at baseline and after 12 weeks of treatment.

RESULTS

Similar significant improvements in HbA1c level were shown in both vildagliptin (-0.8%) and glimepiride (-0.9%) groups after treatment (Ps<0.001). The mean amplitude of glycemic excursions (MAGE) and the mean of daily differences (MODD) were significantly decreased by vildagliptin (P = 0.044 and P = 0.031, respectively) but not by glimepiride. Glimepiride was significantly associated with a higher incidence of hypoglycemia than vildagliptin (P = 0.005). There were no significant differences in urinary 8-iso-PGF_2α or FMD between the two groups.

CONCLUSIONS

Vildagliptin effectively improved glucose level with a significantly greater reduction in glycemic variability and hypoglycemia than glimepiride in patients with T2DM ongoing metformin therapy. The two drugs showed no significant differences in urinary 8-iso-PGF_2α and FMD.

TRIAL REGISTRATION

NCT01404676.

Role of continuous glucose monitoring for type 2 in diabetes management and research

The advent of continuous glucose monitoring (CGM) is a significant stride forward in our ability to better understand the glycemic status of our patients. Current clinical practice employs two forms of CGM: professional (retrospective or "masked") and personal (real-time) to evaluate and/or monitor glycemic control. Most studies using professional and personal CGM have been done in those with type 1 diabetes (T1D). However, this technology is agnostic to the type of diabetes and can also be used in those with type 2 diabetes (T2D). The value of professional CGM in T2D for physicians, patients, and researchers is derived from its ability to: (1) to discover previously unknown hyper- and hypoglycemia (silent and symptomatic); (2) measure glycemic control directly rather than through the surrogate metric of hemoglobin A1C (HbA1C) permitting the observation of a wide variety of metrics that include glycemic variability, the percent of time within, below and above target glucose levels, the severity of hypo- and hyperglycemia throughout the day and night; (3) provide actionable information for healthcare providers derived by the CGM report; (4) better manage patients on hemodialysis; and (5) effectively and efficiently analyze glycemic effects of new interventions whether they be pharmaceuticals (duration of action, pharmacodynamics, safety, and efficacy), devices, or psycho-educational. Personal CGM has also been successfully used in a small number of studies as a behavior modification tool in those with T2D. This comprehensive review describes the differences between professional and personal CGM and the evidence for the use of each form of CGM in T2D. Finally, the opinions of key professional societies on the use of CGM in T2D are presented.

Morning Spot Urine Glucose-to-Creatinine Ratios Predict Overnight Urinary Glucose Excretion in Patients With Type 2 Diabetes

BACKGROUND

With the advent of sodium glucose co-transporter 2 inhibitors to control glucose and treat diabetes, laboratory data aided by either timed or spot glucose levels in the urine could be used as an alternative marker of drug response. The aim of this study was to assess the agreement between overnight urinary glucose excretion (UGE) and morning spot urinary glucose-to-creatinine ratio (UGCR).

METHODS

In this prospective cross-sectional study, we enrolled a total of 215 participants with either normal glucose tolerance (NGT), pre-diabetes, or type 2 diabetes mellitus (T2DM). To exclude external factors such as food intake and physical activity, urine samples collected overnight at an 8-hr interval and the first-voided morning spot urine were collected and compared.

RESULTS

The median values of overnight 8-hr UGE in participants with NGT (N=14), pre-diabetes (N=41), and T2DM (N=160) were 35.0 mg, 35.6 mg, and 653.4 mg, respectively. In participants with T2DM, the median values of overnight 8-hr UGCR and first-voided morning spot UGCR (M-UGCR) were 1.37 mg/mg and 0.16 mg/mg, respectively. Quantitative analyses using an intraclass correlation coefficient (ICC) demonstrated a good reliability of measurement of the overnight 8-hr UGCR and M-UGCR (ICC=0.943, P<0.001). The M-UGCR was also significantly related to the overnight 8-hr UGE (r=0.828, P<0.001).

CONCLUSIONS

M-UGCR and overnight 8-hr UGCR showed good agreement, suggesting that M-UGCR be used as a simple index for estimating overnight amounts of UGE in patients with T2DM.

The Contemporary Role of Masked Continuous Glucose Monitoring in a Real-Time World

Real-time continuous glucose monitoring (RT-CGM) has, in the span of just a few years, established an essential role in the contemporary management of type 1 diabetes. Nonetheless, masked CGM retains an important place in the management of diabetes including assisting with hypoglycemia detection and avoidance, optimizing glycemic control, and acting as a teaching tool for people living with diabetes.

Glycemic Variability: How Do We Measure It and Why Is It Important?

Chronic hyperglycemia is the primary risk factor for the development of complications in diabetes mellitus (DM); however, it is believed that frequent or large glucose fluctuations may independently contribute to diabetes-related complications. Postprandial spikes in blood glucose, as well as hypoglycemic events, are blamed for increased cardiovascular events in DM. Glycemic variability (GV) includes both of these events; hence, minimizing GV can prevent future cardiovascular events. Correcting GV emerges as a target to be pursued in clinical practice to safely reduce the mean blood glucose and to determine its direct effects on vascular complications in diabetes. Modern diabetes management modalities, including glucagon-related peptide-1-based therapy, newer insulins, modern insulin pumps and bariatric surgery, significantly reduce GV. However, defining GV remains a challenge primarily due to the difficulty of measuring it and the lack of consensus regarding the optimal approach for its management. The purpose of this manuscript was not only to review the most recent evidence on GV but also to help readers better understand the available measurement options and how the various definitions relate differently to the development of diabetic complications.