Continuous glucose monitoring and type 1 diabetes

Integrated insulin pump therapy with continuous glucose monitoring for improved adherence: technology update

Insulin pump therapy combined with real-time continuous glucose monitoring, known as sensor-augmented pump (SAP) therapy, has been shown to improve metabolic control and to reduce the rate of hypoglycemia in adults with type 1 diabetes compared to multiple daily injections or standard continuous subcutaneous insulin infusion. Glycemic variability is also reduced in patients on SAP therapy. This approach allows patients to monitor their glucose levels being informed of glycemic concentration and trend. Trained diabetic patients, therefore, can appropriately modify insulin infusion and/or carbohydrate intake in order to prevent hypo- or hyperglycemia. For these reasons, SAP therapy is now considered the gold standard for type 1 diabetes treatment. To be clinically effective, however, devices and techniques using advanced technology should not only have the potential to theoretically ameliorate metabolic control, but also be well accepted by patients in terms of satisfaction and health-related quality of life, because these factors will improve treatment adherence and consequently overall outcome. SAP therapy is generally well tolerated by patients; however, many clinical trials have identified significant noncompliance in the use of this device, most notably in the pediatric and adolescent populations. In this review we aim to analyze the main reasons for good or poor adherence to SAP therapy and to provide useful tips in order to fully benefit from this kind of novel therapeutic approach.

Evaluating the clinical accuracy of GlucoMen®Day: a novel microdialysis-based continuous glucose monitor

BACKGROUND

The objective of this work was to determine the clinical accuracy of GlucoMen®Day, a new microdialysis-based continuous glucose monitoring system (CGMS) from A. Menarini Diagnostics (Florence, Italy). Accuracy evaluation was performed using continuous glucose-error grid analysis (CG-EGA), as recommended by the Performance Metrics for Continuous Interstitial Glucose Monitoring; Approved Guideline (POCT05-A).

METHODS

Two independent clinical trials were carried out on patients with types 1 and 2 diabetes mellitus, the glycemic levels of whom were monitored in an in-home setting for 100-hour periods. A new multiparametric algorithm was developed and used to compensate in real-time the GlucoMen®Day signal. The time lag between continuous glucose monitoring (CGM) and reference data was first estimated using the Poincaré plot method. The entire set of CGM/reference data pairs was then evaluated following the CG-EGA criteria, which allowed an estimation of the combined point and rate accuracy stratified by glycemic ranges.

RESULTS

With an estimated time lag of 11 minutes, the linear regression analysis of the CGM/reference glucose values yielded r = 0.92. The mean absolute error (MAE) was 11.4 mg/dl. The calculated mean absolute rate deviation (MARD) was 0.63 mg/dl/min. The data points falling within the A+B zones of CG-EGA were 100% in hypoglycemia, 95.7% in euglycemia, and 95.2% in hyperglycemia.

CONCLUSIONS

The GlucoMen®Day system provided reliable, real-time measurement of subcutaneous glucose levels in patients with diabetes for up to 100 hours. The device showed the ability to follow rapid glycemic excursions and detect severe hypoglycemic events accurately. Its accuracy parameters fitted the criteria of the state-of-the-art consensus guideline for CGMS, with highly consistent results from two independent studies.

Glucose biosensors: an overview of use in clinical practice

Blood glucose monitoring has been established as a valuable tool in the management of diabetes. Since maintaining normal blood glucose levels is recommended, a series of suitable glucose biosensors have been developed. During the last 50 years, glucose biosensor technology including point-of-care devices, continuous glucose monitoring systems and noninvasive glucose monitoring systems has been significantly improved. However, there continues to be several challenges related to the achievement of accurate and reliable glucose monitoring. Further technical improvements in glucose biosensors, standardization of the analytical goals for their performance, and continuously assessing and training lay users are required. This article reviews the brief history, basic principles, analytical performance, and the present status of glucose biosensors in the clinical practice.

Reducing glycaemic variability in type 1 diabetes self-management with a continuous glucose monitoring system based on wired enzyme technology

AIMS/HYPOTHESIS

This study was designed to investigate the use and impact of a continuous glucose monitoring system (the FreeStyle Navigator) under home-use conditions in the self-management of type 1 diabetes.

METHODS

A 20 day masked phase, when real-time data and alarms were not available, was compared with a subsequent 40 day unmasked phase for a number of specified measures of glycaemic variability. HbA(1c) (measured by DCA 2000) and a hypoglycaemia fear survey were recorded at the start and end of the study.

RESULTS

The study included 48 patients with type 1 diabetes (mean age 35.7 +/- 10.9, range 18-61 years; diabetes duration 17.0 +/- 9.5 years). Two patients did not complete the study for personal reasons. Comparing masked (all 20 days) and unmasked (last 20 days) phases, the following reductions were seen: time outside euglycaemia from 11.0 to 9.5 h/day (p = 0.002); glucose SD from 3.5 to 3.2 mmol/l (p < 0.001); hyperglycaemic time (>10.0 mmol/l) from 10.3 to 8.9 h/day (p = 0.0035); mean amplitude of glycaemic excursions (peak to nadir) down by 10% (p < 0.001); high blood glucose index down by 18% (p = 0.0014); and glycaemic risk assessment diabetes equation score down by 12% (p = 0.0013). Hypoglycaemic time (<3.9 mmol/l) decreased from 0.70 to 0.64 h/day without statistical significance (p > 0.05). Mean HbA(1c) fell from 7.6 +/- 1.1% at baseline to 7.1 +/- 1.1% (p < 0.001). In the hypoglycaemia fear survey, the patients tended to take less snacks at night-time after wearing the sensor.

CONCLUSIONS/INTERPRETATION

Home use of a continuous glucose monitoring system has a positive effect on the self-management of diabetes. Thus, continuous glucose monitoring may be a useful tool to decrease glycaemic variability.

Clinical review: Realistic expectations and practical use of continuous glucose monitoring for the endocrinologist

CONTEXT

Real-time continuous glucose monitoring (CGM) has been available for type 1 diabetes for several years. This paper is a status report on our early experiences with this next technology.

EVIDENCE ACQUISITION

The two major sources of data acquisition included PubMed search strategies and personal experience of the author from clinical experience.

EVIDENCE SYNTHESIS

Data assessing CGM accuracy, short-term outcomes (12 wk), and longer term outcomes (6 months) are reported. Potential strategies for successful and efficient use in an office or clinic setting are also discussed. Practical aspects of CGM use (alarm settings, using glycemic trending information) are also reviewed.

CONCLUSIONS

Accuracy of this technology has improved in the short amount of time it has been available. Six-month data suggest that patient selection is a key for success. Patients who do not understand or practice the basics of intensive insulin therapy have the greatest challenges. Those who do best watch the receiver frequently, continue with frequent home blood glucose monitoring, use the trending information to make insulin adjustments, and understand the limitations of the technology. With insurance reimbursement improving, CGM is gaining acceptance as an important tool for the management of type 1 diabetes. Like home blood glucose monitoring and insulin pump therapy, this technology by itself is not a panacea for diabetes control. However, it further adds to our ability to improve the lives of people with diabetes. Long-term, the hope is that this technology will pave the way for a "closed-loop" device.

Overview on self-monitoring of blood glucose

The self-monitoring of blood glucose (SMBG), traditionally performed by "point-of-care" (POC) devices called portable glucose monitors (PGM) is now considered an integral part of managed care of diabetic patients, especially type 1 diabetics and those on insulin therapy. In patients with type 2 diabetes, SMBG can help to achieve a better glycaemic control, although there is not sufficient evidence to attest that strict monitoring in these patients is associated with an improved outcome. The outcome of several clinical studies, especially in diabetics on insulin therapy, has shown that SMBG plays a key role in preventing complications in the short, medium and long term. According to the current recommendations, SMBG is aimed to achieve and maintain glycaemic control, prevent and identify hypoglycaemia, prevent severe hyperglycaemia, adjust lifestyle changes and establish the need to begin treatment with insulin in gestational diabetes mellitus. However, as clearly highlighted by the American Diabetes Association (ADA) and the National Academy of Clinical Biochemistry (NACB), patients and healthcare personnel should be trained on the appropriate use of the device, as well as on the correct interpretation of data. Moreover, definite analytical targets and appropriate acceptance criteria for performance should be fulfilled before a new device is introduced in the hospital environment, or recommended to the patients. Performance limitations such as hematocrit extremes and analytical interferences should be clearly acknowledged by the operators, before taking test results for granted. The current article aims to review the current indications for SMGB and highlight the most important criteria for the appropriate use of PGMs.