Continuous glucose monitoring: quality of hypoglycaemia detection

A Critical Discussion of Alert Evaluations in the Context of Continuous Glucose Monitoring System Performance

Many continuous glucose monitoring (CGM) systems provide functionality which alerts users of potentially unwanted glycemic conditions. These alerts can include glucose threshold alerts to call the user's attention to hypoglycemia or hyperglycemia, predictive alerts warning about impeding hypoglycemia or hyperglycemia, and rate-of-change alerts. A recent review identified 129 articles about CGM performance studies, of which approximately 25% contained alert evaluations. In some studies, real alerts were assessed; however, most of these studies retrospectively determined the timing of CGM alerts because not all CGM systems record alerts which necessitates manual documentation. In contrast to assessment of real alerts, retrospective determination allows assessment of a variety of alert settings for all three types of glycemic condition alerts. Based on the literature and the Clinical and Laboratory Standards Institute's POCT05 guideline, two common approaches to threshold alert evaluation were identified, one value-based and one episode-based approach. In this review, a critical discussion of the two approaches, including a post hoc analysis of clinical study data, indicates that the episode-based approach should be preferred over the value-based approach. For predictive alerts, fewer results were found in the literature, and retrospective determination of CGM alert timing is complicated by the prediction algorithms being proprietary information. Rate-of-change alert evaluations were not reported in the identified literature, and POCT05 does not contain recommendations for assessment. A possible approach is discussed including post hoc analysis of clinical study data. To conclude, CGM systems should record alerts, and the episode-based approach to alert evaluation should be preferred.

Clinical Performance Evaluation of Continuous Glucose Monitoring Systems: A Scoping Review and Recommendations for Reporting

The use of different approaches for design and results presentation of studies for the clinical performance evaluation of continuous glucose monitoring (CGM) systems has long been recognized as a major challenge in comparing their results. However, a comprehensive characterization of the variability in study designs is currently unavailable. This article presents a scoping review of clinical CGM performance evaluations published between 2002 and 2022. Specifically, this review quantifies the prevalence of numerous options associated with various aspects of study design, including subject population, comparator (reference) method selection, testing procedures, and statistical accuracy evaluation. We found that there is a large variability in nearly all of those aspects and, in particular, in the characteristics of the comparator measurements. Furthermore, these characteristics as well as other crucial aspects of study design are often not reported in sufficient detail to allow an informed interpretation of study results. We therefore provide recommendations for reporting the general study design, CGM system use, comparator measurement approach, testing procedures, and data analysis/statistical performance evaluation. Additionally, this review aims to serve as a foundation for the development of a standardized CGM performance evaluation procedure, thereby supporting the goals and objectives of the Working Group on CGM established by the Scientific Division of the International Federation of Clinical Chemistry and Laboratory Medicine.

Use of Continuous Glucose Monitoring in Patients Following Bariatric Surgery: A Scoping Review

The objective of this scoping review was to summarize the emerging literature on the use of continuous glucose monitoring (CGM) in post-bariatric surgery patients, with a focus on its features (e.g., device, mode, and accuracy), as well as purposes and outcomes of utilization. Three databases (PubMed, EMBASE, and Web of Science) were searched to obtain relevant studies. Results suggested that most studies used CGM for 3-7 days under blinded mode. Accuracy data were available in only one study, which reported a mean absolute relative difference of 21.7% for Freestyle Libre. The primary applications of CGM were for elucidating glucose patterns and assessing glycemic treatment outcomes. No study has tested the effect of CGM as an intervention strategy to enhance glucose control.

Hypoglycaemia detection and prediction techniques: A systematic review on the latest developments

The main objective of diabetes control is to correct hyperglycaemia while avoiding hypoglycaemia, especially in insulin-treated patients. Fear of hypoglycaemia is a hurdle to effective correction of hyperglycaemia because it promotes under-dosing of insulin. Strategies to minimise hypoglycaemia include education and training for improved hypoglycaemia awareness and the development of technologies to allow their early detection and thus minimise their occurrence. Patients with impaired hypoglycaemia awareness would benefit the most from these technologies. The purpose of this systematic review is to review currently available or in-development technologies that support detection of hypoglycaemia or hypoglycaemia risk, and identify gaps in the research. Nanomaterial use in sensors is a promising strategy to increase the accuracy of continuous glucose monitoring devices for low glucose values. Hypoglycaemia is associated with changes on vital signs, so electrocardiogram and encephalogram could also be used to detect hypoglycaemia. Accuracy improvements through multivariable measures can make already marketed galvanic skin response devices a good noninvasive alternative. Breath volatile organic compounds can be detected by dogs and devices and alert patients at hypoglycaemia onset, while near-infrared spectroscopy can also be used as a hypoglycaemia alarms. Finally, one of the main directions of research are deep learning algorithms to analyse continuous glucose monitoring data and provide earlier and more accurate prediction of hypoglycaemia. Current developments for early identification of hypoglycaemia risk combine improvements of available 'needle-type' enzymatic glucose sensors and noninvasive alternatives. Patient usability will be essential to demonstrate to allow their implementation for daily use in diabetes management.

Non-invasive and minimally invasive glucose monitoring devices: a systematic review and meta-analysis on diagnostic accuracy of hypoglycaemia detection

BACKGROUND

The use of minimally and non-invasive monitoring systems (including continuous glucose monitoring) has increased rapidly over recent years. Up to now, it remains unclear how accurate devices can detect hypoglycaemic episodes. In this systematic review and meta-analysis, we assessed the diagnostic accuracy of minimally and non-invasive hypoglycaemia detection in comparison to capillary or venous blood glucose in patients with type 1 or type 2 diabetes.

METHODS

Clinical Trials.gov, Cochrane Library, Embase, PubMed, ProQuest, Scopus and Web of Science were systematically searched. Two authors independently screened the articles, extracted data using a standardised extraction form and assessed methodological quality using a review-tailored quality assessment tool for diagnostic accuracy studies (QUADAS-2). The diagnostic accuracy of hypoglycaemia detection was analysed via meta-analysis using a bivariate random effects model and meta-regression with regard to pre-specified covariates.

RESULTS

We identified 3416 nonduplicate articles. Finally, 15 studies with a total of 733 patients were included. Different thresholds for hypoglycaemia detection ranging from 40 to 100 mg/dl were used. Pooled analysis revealed a mean sensitivity of 69.3% [95% CI: 56.8 to 79.4] and a mean specificity of 93.3% [95% CI: 88.2 to 96.3]. Meta-regression analyses showed a better hypoglycaemia detection in studies indicating a higher overall accuracy, whereas year of publication did not significantly influence diagnostic accuracy. An additional analysis shows the absence of evidence for a better performance of the most recent generation of devices.

CONCLUSION

Overall, the present data suggest that minimally and non-invasive monitoring systems are not sufficiently accurate for detecting hypoglycaemia in routine use.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO 2018 CRD42018104812.

Hypoglycemia Prevention via Personalized Glucose-Insulin Models Identified in Free-Living Conditions

BACKGROUND

The objective of this research is to show the effectiveness of individualized hypoglycemia predictive alerts (IHPAs) based on patient-tailored glucose-insulin models (PTMs) for different subjects. Interpatient variability calls for PTMs that have been identified from data collected in free-living conditions during a one-month trial.

METHODS

A new impulse-response (IR) identification technique has been applied to free-living data in order to identify PTMs that are able to predict the future glucose trends and prevent hypoglycemia events. Impulse response has been applied to seven patients with type 1 diabetes (T1D) of the University of Amsterdam Medical Centre. Individualized hypoglycemia predictive alert has been designed for each patient thanks to the good prediction capabilities of PTMs.

RESULTS

The PTMs performance is evaluated in terms of index of fitting (FIT), coefficient of determination, and Pearson's correlation coefficient with a population FIT of 63.74%. The IHPAs are evaluated on seven patients with T1D with the aim of predicting in advance (between 45 and 10 minutes) the unavoidable hypoglycemia events; these systems show better performance in terms of sensitivity, precision, and accuracy with respect to previously published results.

CONCLUSION

The proposed work shows the successful results obtained applying the IR to an entire set of patients, participants of a one-month trial. Individualized hypoglycemia predictive alerts are evaluated in terms of hypoglycemia prevention: the use of a PTM allows to detect 84.67% of the hypoglycemia events occurred during a one-month trial on average with less than 0.4% of false alarms. The promising prediction capabilities of PTMs can be a key ingredient for new generations of individualized model predictive control for artificial pancreas.

Measures of Accuracy for Continuous Glucose Monitoring and Blood Glucose Monitoring Devices

Currently, patients with diabetes may choose between two major types of system for glucose measurement: blood glucose monitoring (BGM) systems measuring glucose within capillary blood and continuous glucose monitoring (CGM) systems measuring glucose within interstitial fluid. Although BGM and CGM systems offer different functionality, both types of system are intended to help users achieve improved glucose control. Another area in which BGM and CGM systems differ is measurement accuracy. In the literature, BGM system accuracy is assessed mainly according to ISO 15197:2013 accuracy requirements, whereas CGM accuracy has hitherto mainly been assessed by MARD, although often results from additional analyses such as bias analysis or error grid analysis are provided. The intention of this review is to provide a comparison of different approaches used to determine the accuracy of BGM and CGM systems and factors that should be considered when using these different measures of accuracy to make comparisons between the analytical performance (ie, accuracy) of BGM and CGM systems. In addition, real-world implications of accuracy and its relevance are discussed.

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.

Empagliflozin as adjunct to insulin in Japanese participants with type 1 diabetes: Results of a 4-week, double-blind, randomized, placebo-controlled phase 2 trial

AIMS

This phase 2, double-blind, randomized, placebo-controlled trial (ClinicalTrials.gov NCT02702011) with 4 sites in Japan investigated the pharmacodynamics (PD), pharmacokinetics (PK) and safety profile of empagliflozin in Japanese participants with type 1 diabetes mellitus (T1DM) as adjunctive therapy to insulin.

MATERIALS AND METHODS

Participants using multiple daily injections of insulin for ≥12 months, with HbA1c of 7.5%-10.0%, entered a 2-week, open-label, placebo run-in period, followed by a 4-week, double-blind period during which participants were randomized 1:1:1:1 to receive empagliflozin 2.5 mg (n = 13), empagliflozin 10 mg (n = 12), empagliflozin 25 mg (n = 12) or placebo (n = 11). The primary objective was to assess the effect of empagliflozin vs placebo on urinary glucose excretion (UGE) after 7 days of treatment.

RESULTS

PD: Empagliflozin resulted in a dose-dependent significant increase in 24-hour UGE compared with placebo (UGE placebo-corrected mean [95% confidence interval] change from baseline: 2.5 mg, 65.10 [43.29, 86.90] g/24 h; 10 mg, 81.19 [58.80, 103.58] g/24 h; 25 mg, 98.11 [75.91, 120.31] g/24 h). After 4 weeks of treatment, UGE increase was associated with improved glycaemic control, reduced body weight and decreased insulin needs. Empagliflozin treatment also resulted in dose-dependent increases in serum ketone bodies and free fatty acids. PK: Plasma empagliflozin levels increased in a dose-dependent manner and peaked at 1.5 hours. In this short study, empagliflozin was well tolerated, with no increase in rate of hypoglycaemia and no diabetic ketoacidosis events reported.

CONCLUSIONS

Based on this short-duration phase 2 study, the PK/PD profile of empagliflozin in Japanese participants with T1DM is comparable to that of non-Japanese participants.

Continuous glucose monitoring results in lower HbA1c in Malaysian women with insulin-treated gestational diabetes: a randomized controlled trial

AIMS

To determine if therapeutic, retrospective continuous glucose monitoring (CGM) improves HbA_1c with less hypoglycaemia in women with insulin-treated gestational diabetes mellitus (GDM).

METHODS

This prospective, randomized controlled, open-label trial evaluated 50 women with insulin-treated GDM randomized to either retrospective CGM (6-day sensor) at 28, 32 and 36 weeks' gestation (Group 1, CGM, n = 25) or usual antenatal care without CGM (Group 2, control, n = 25). All women performed seven-point capillary blood glucose (CBG) profiles at least 3 days per week and recorded hypoglycaemic events (symptomatic and asymptomatic CBG < 3.5 mmol/l; non-fasting < 4.0 mmol/l). HbA_1c was measured at 28, 33 and 37 weeks. In Group 1, both CGM and CBG data were used to manage diabetes, whereas mothers in Group 2 were managed based on CBG data alone.

RESULTS

Baseline characteristics (age, pre-pregnancy BMI, HbA_1c , total insulin dose) were similar between groups. There was a lower increase in HbA_1c from 28 to 37 weeks' gestation in the CGM group [∆HbA_1c : CGM + 1 mmol/mol (0.09%), control + 3mmol/mol (0.30%); P = 0.024]. Mean HbA_1c remained unchanged throughout the trial in the CGM group, but increased significantly in controls as pregnancy advanced. Mean HbA_1c in the CGM group was lower at 37 weeks compared with controls [33 ± 4 mmol/mol (5.2 ± 0.4%) vs. 38 ± 7 mmol/mol (5.6 ± 0.6%), P < 0.006]. Some 92% of the CGM group achieved an HbA_1c ≤ 39 mmol/mol (≤ 5.8%) at 37 weeks compared with 68% of the control group (P = 0.012). Neither group experienced severe hypoglycaemia.

CONCLUSION

CGM use may be beneficial in insulin-treated GDM because it improves HbA_1c compared with usual antenatal care without increasing severe hypoglycaemia. (Clinical Trials Registry No.: NCT02204657).

Masked hypoglycemia in pregnancy

BACKGROUND

Hypoglycemia is a major hindrance for optimal glycemic control in women with gestational diabetes mellitus (GDM) on insulin. In the present study, masked hypoglycemia (glucose <2.77mmol/L for ≥30 min) was estimated in pregnant women using a continuous glucose monitoring (CGM) system.

METHODS

Twenty pregnant women with GDM on insulin (cases) and 10 age-matched euglycemic pregnant women (controls) between 24 and 36 weeks gestation were recruited. Both groups performed self-monitoring of blood glucose (SMBG) and underwent CGM for 72 h to assess masked hypoglycemia. Masked hypoglycemic episodes were further stratified into two groups based on interstitial glucose (2.28-2.77 and ≤2.22 mmol/L).

RESULTS

Masked hypoglycemia was recorded in 35% (7/20) of cases and 40% (4/10) of controls using CGM, with an average of 1.28 and 1.25 episodes per subject, respectively. Time spent at glucose levels between 2.28 and 2.77 mmol/L did not differ between the two groups (mean 114 vs 90 min; P = 0.617), but cases spent a longer time with glucose ≤2.2 mmol/L. Babies born to women with GDM were significantly lighter than those born to controls (2860 vs 3290 g; P = 0.012). There was no significant difference in birth weight within the groups among babies born to women with or without hypoglycemia.

CONCLUSION

Euglycemic pregnant women and those with GDM on insulin had masked hypoglycemia. Masked hypoglycemia was not associated with adverse maternal or fetal outcomes. Therefore, low glucose levels in the hypoglycemic range may represent a physiologic adaptation in pregnancy. This response is exaggerated in women with GDM on insulin.

A Review of the Current Challenges Associated with the Development of an Artificial Pancreas by a Double Subcutaneous Approach

INTRODUCTION

Patients with diabetes type 1 (DM1) struggle daily to achieve good glucose control. The last decade has seen a rush of research groups working towards an artificial pancreas (AP) through the application of a double subcutaneous approach, i.e., subcutaneous (SC) continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion. Few have focused on the fundamental limitations of this approach, especially regarding outcome measures beyond time in range.

METHODS

Based on insulin physiology, the limitations of CGM, SC insulin absorption, meal challenge, and physical activity in DM1 patients, we discuss the limitations of the double SC approach. Finally, we discuss safety measures and the achievements reported in some recent AP studies that have utilized the double SC approach.

RESULTS

Most studies show that a double SC AP increases the time in range compared to a sensor-augmented insulin pump and shortens the time in hypoglycemia. Despite these achievements, the proportion of time spent in hyperglycemia is still roughly 20-40%, and hypoglycemia is still present 1-4% of the time. The main factors limiting further progress are the latency of SC CGM (at least 5-10 min) and the slow pharmacokinetics of SC-delivered fast-acting insulin. The maximum blood insulin level is reached after 45 min and the maximum glucose-lowering effect is observed after 1.5-2 h, while the glucose-lowering effect lasts for at least 5 h.

CONCLUSIONS

Although using a double SC AP leads to significant improvements in glucose control, the SC approach has severe limitations that hamper further progress towards a robust AP.

Glucose Exposure and Variability with Empagliflozin as Adjunct to Insulin in Patients with Type 1 Diabetes: Continuous Glucose Monitoring Data from a 4-Week, Randomized, Placebo-Controlled Trial (EASE-1)

BACKGROUND

We evaluated the effect of empagliflozin as adjunct to insulin on 24-h glucose exposure and variability in patients with type 1 diabetes.

METHODS

Patients (N = 75) with HbA_1c ≥7.5% to ≤10.5% were randomized to receive empagliflozin 2.5 mg, empagliflozin 10 mg, empagliflozin 25 mg, or placebo once daily as adjunct to insulin for 4 weeks. Insulin dose was to be kept as stable as possible during week 1 of treatment and was freely adjustable thereafter. Markers of glucose exposure and variability were assessed from 7-day blinded continuous glucose monitoring intervals. This study is completed ( ClinicalTrials.gov NCT01969747).

RESULTS

Empagliflozin reduced hourly mean glucose area under the median curve over 24 h versus placebo within week 1 (adjusted mean differences: -12.2 mg/dL·h [95% confidence interval -23.9 to -0.5], -30.2 mg/dL·h [-42.2 to -18.2], and -33.0 mg/dL·h [-44.8 to -21.1] with empagliflozin 2.5, 10, and 25 mg, respectively; all P < 0.05) and increased time in glucose target range (>70 to ≤180 mg/dL). Results were sustained to week 4 with empagliflozin 25 mg. All empagliflozin doses significantly reduced glucose variability (interquartile range and mean amplitude of glucose excursions) versus placebo at weeks 1 and 4. Except for small increases in hours per day with glucose ≤70 mg/dL during the stable insulin period, empagliflozin did not increase time in hypoglycemia compared with placebo.

CONCLUSIONS

In patients with type 1 diabetes, empagliflozin as adjunct to insulin decreased glucose exposure and variability and increased time in glucose target range.

Sensor-Augmented Insulin Pumps and Hypoglycemia Prevention in Type 1 Diabetes

Hypoglycemia can lead to seizures, unconsciousness, or death. Insulin pump treatment reduces the frequency of severe hypoglycemia compared with multiple daily injections treatment. The addition of a continuous glucose monitor, so-called sensor-augmented pump (SAP) treatment, has the potential to further limit the duration and severity of hypoglycemia as the system can detect and in some systems act on impending and prevailing low blood glucose levels. In this narrative review we summarize the available knowledge on SAPs with and without automated insulin suspension, in relation to hypoglycemia prevention. We present evidence from randomized trials, observational studies, and meta-analyses including nonpregnant individuals with type 1 diabetes mellitus. We also outline concerns regarding SAPs with and without automated insulin suspension. There is evidence that SAP treatment reduces episodes of moderate and severe hypoglycemia compared with multiple daily injections plus self-monitoring of blood glucose. There is some evidence that SAPs both with and without automated suspension reduces the frequency of severe hypoglycemic events compared with insulin pumps without continuous glucose monitoring.

Continuous Subcutaneous Insulin Infusion in Children: A Pilot Study Validating a Protocol to Avoid Hypoglycemia at Initiation

BACKGROUND

The occurrence of hypoglycemia and hyperglycemia during the first days after transition to continuous subcutaneous insulin infusion (CSII) in patients with type 1 diabetes has not been systematically studied in children. The aim of this prospective study was to demonstrate that the protocol applied in our diabetes clinic is safe at CSII initiation in children.

METHODS

We assessed 22 pediatric patients with type 1 diabetes, using continuous glucose monitoring (CGM) before and after CSII initiation (±3 days).

RESULTS

After CSII initiation, there was no difference in the rates of hypoglycemic events expressed as relative rates (RRs) per person-reading (RR = 0.85, p = 0.52, 95% CI 0.52-1.39), as well as in the number of prolonged hypoglycemic events (>1 h) per day (RR = 1.12, p = 0.56, 95% CI 0.75-1.68). We observed only a trend toward prolonged episodes of hyperglycemia after pump initiation (RR = 1.52, p = 0.06, 95% CI 0.97-2.35).

CONCLUSION

Our study is the first to assess, through CGM and in a prospective way, the impact of a CSII initiation protocol on glycemic values. Our protocol provides a safe model to avoid hypoglycemia at CSII initiation in children.

CLINICAL TRIAL REGISTRATION

www.ClinicalTrials.gov, identifier NCT01840358.

Continuous glucose monitoring in patients with type 2 diabetes treated with glucagon-like peptide-1 receptor agonist dulaglutide in combination with prandial insulin lispro: an AWARD-4 substudy

AIM

To conduct a substudy, using 24-hour continuous glucose monitoring (CGM), of the AWARD-4 trial, which was designed to compare insulin + glucagon-like peptide-1 receptor agonist treatment with an insulin-only regimen.

METHODS

The AWARD-4 trial randomized 884 conventional insulin regimen-treated patients to dulaglutide 1.5 mg, dulaglutide 0.75 mg and glargine, all in combination with prandial insulin lispro. The CGM substudy included 144 patients inserted with a Medtronic CGMS iPro CGM device to enable 3-day glucose monitoring. CGM sessions were completed at weeks 0, 13, 26 and 52. CGM measures included mean 24-hour glucose, percentage time in target glucose ranges, hyper- and hypoglycaemia and glucose variability. The primary objective was treatment comparison for percentage time spent with CGM glucose values in the 3.9-7.8 mmol/L range after 26 weeks.

RESULTS

At week 26, mean CGM values decreased in all treatment groups (change from baseline -2.8 ± 0.3, -2.4 ± 0.3 and -2.5 ± 0.3 mmol/L for dulaglutide 1.5 mg, dulaglutide 0.75 mg and glargine, respectively); between-group differences were not statistically significant. Treatment groups were similar for percentage time in the 3.9-7.8 mmol/L range. Percentage time in the 3.9-10.0 mmol/L range was greater for dulaglutide 1.5 mg than for glargine (p < 0.05). Dulaglutide and glargine were associated with decreased glucose variability for all CGM variability indices. The overall within-patient standard deviation (s.d.) was significantly reduced with dulaglutide 1.5 mg versus glargine (p < 0.05). At week 52, there were no significant differences among the groups with regard to measures of normoglycaemia or near-normoglycaemia and for the overall within-patient s.d. Treatment with glargine was associated with greater increases in percentage time spent with glucose values ≤3.9 mmol/L, with statistically significant differences between the groups at 52 weeks (p < 0.05).

CONCLUSIONS

In combination with prandial lispro, treatment with dulaglutide and glargine resulted in similar proportions of glucose values in the normoglycaemic range, but dulaglutide provided an improved balance between the proportion of values within the near-normoglycaemia range and values within the hypoglycaemic range.

AP@home: The Artificial Pancreas Is Now at Home

In the past years the development of an artificial pancreas (AP) has made great progress and many activities are ongoing in this area of research. The major step forward made in the last years was moving the evaluation of AP systems from highly controlled experimental conditions to daily life conditions at the home of patients with diabetes; this was also the aim of the European Union-funded AP@home project. Over a time period of 5 years a series of clinical studies were performed that culminated in 2 "final studies" during which an AP system was used by patients in their home environment for 2 or 3 months without supervision by a physician, living their normal lives. Two different versions of the AP system developed within this project were evaluated. A significant improvement in glycated hemoglobin was observed during closed-loop conditions despite the fact that during the control period the patients used the best currently available therapeutic option. In addition, a "single-port AP system" was developed within the project that combines continuous glucose monitoring and insulin infusion at a single tissue site. By using such a combined device the patients not only have to carry one less device around, the number of access points through the skin is also reduced from 2 to 1. In summary, close cooperation of 12 European partners, both academic centers and industry, enabled the development and evaluation of AP systems under daily life conditions. The next step is to develop these into products in cooperation with commercial partners.

The Hypoglycaemia-Hyperglycaemia Minimizer System in the Management of Type 1 Diabetes

Living with type 1 diabetes (T1D) presents many challenges in terms of daily living. Insulin users need to frequently monitor their blood glucose levels and take multiple injections per day and/or multiple boluses through an insulin infusion pump, with the consequences of failing to match the insulin dose to the body's needs resulting in hypoglycaemia and hyperglycaemia. The former can result in seizures, coma and even death; the latter can have both acute and long-term health implications. Many patients with T1D also fail to meet their treatment goals. In order to reduce the burdens of self-administering insulin, and improve efficacy and safety, there is a need to at least partially remove the patient from the loop via a closed-loop 'artificial pancreas’ system. The Hypoglycaemia-Hyperglycaemia Minimizer (HHM) System, comprising a continuous, subcutaneous insulin infusion pump, continuous glucose monitor (CGM) and closed-loop insulin dosing algorithm, is able to predict changes in blood glucose and adjust insulin delivery accordingly to help keep the patient at normal glucose levels. Early clinical data indicate that this system is feasible, effective and safe, and has the potential to dramatically improve the therapeutic outcomes and quality of life for people with T1D.

Glycemic variability during algorithmic titration of insulin among hospitalized patients with type 2 diabetes and heart failure

AIMS

The objective of this study is to assess hypoglycemia and glycemic variability (GV) in hospitalized patients with and without heart failure (HF) exacerbation.

METHODS

Hospitalized patients with type 2 diabetes (T2D) with (N=35) or without (N=16) HF who had hyperglycemia or significant insulin use were included. Subjects underwent continuous glucose monitoring during algorithmic titration of basal bolus insulin.

RESULTS

HF subjects had lower glucose coefficient of variation ([CV], 31±12 vs. 22±8.2, p=0.02), lower Low Blood Glucose Index (LBGI) and less hypoglycemia (25% vs. 2.6%, p=0.02), but similar mean glucose and glycemic lability index as non-HF subjects on day 1, but not on day 2. Sensor CV was correlated with hypoglycemia (ρ 0.32, p=0.02), HF status (ρ -0.35, p=0.013), T2D duration (ρ 0.29, p=0.04), insulin use prior to admission (ρ 0.42, p=0.002) and catecholamine levels. After controlling for differences in age, HbA1c, hypoglycemia, catecholamine levels, QT interval, and beta blocker use, only HF and diabetes duration or insulin use prior to admission were independent predictors of CV. HF had less robust associations with LBGI in multivariable models.

CONCLUSIONS

HF is not associated with increased GV or hypoglycemia risk during initial titration of insulin. Further research is needed to determine prognostic implications.

Use of continuous glucose monitoring to identify glucose dysregulation in growth hormone insensitivity syndrome

BACKGROUND/AIMS

Monogenic forms of growth hormone insensitivity (GHI) and its treatment with recombinant insulin-like growth factor-1 (rIGF-1) are both associated with glucose dysregulation. We used the information provided by continuous glucose monitoring systems (CGMS) for the clinical management of two children with monogenic GHI prior to the commencement of therapy as well as during the years when they received rIGF-1 treatment and continued to do so after the cessation of therapy.

METHODS

We evaluated the extent of hyper- and hypoglycaemia with CGMS.

RESULTS

In one patient, before treatment CGMS identified self-limiting nocturnal hypoglycaemia. Initiation of rIGF-1 treatment resulted in severe and persistent hypoglycaemia with an absence of spontaneous recovery. Corrective dietary measures were instituted. In a second patient, who had a poor growth response to rIGF-1 therapy, CGMS identified significant fluctuations in daytime glucose levels whilst on treatment with evidence of postprandial hyperglycaemia and both rebound and nocturnal hypoglycaemia. Given the lack of improved growth and the documented glucose dysregulation, treatment was stopped and repeat measurements with CGMS 1 month afterwards showed complete resolution.

CONCLUSIONS

We have demonstrated that CGMS is an effective tool to assess glucose dysregulation in patients with GHI and alters clinical management.

Taking a Closer Look--Continuous Glucose Monitoring in Non-Critically Ill Hospitalized Patients with Type 2 Diabetes Mellitus Under Basal-Bolus Insulin Therapy

BACKGROUND

Inpatient glucose management is based on four daily capillary blood glucose (BG) measurements. The aim was to test the capability of continuous glucose monitoring (CGM) for assessing the clinical impact and safety of basal-bolus insulin therapy in non-critically ill hospitalized patients with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

Eighty-four patients with T2DM (age, 68±10 years; glycosylated hemoglobin, 72±28 mmol/mol; body mass index, 31±7 kg/m(2)) were treated with basal-bolus insulin. CGM was performed with the iPro(®)2 system (Medtronic MiniMed, Northridge, CA) and calibrated retrospectively.

RESULTS

A remarkable consistency between CGM and BG measurements and therapy improvement was shown over the study period of 501 patient-days. The number of CGM and BG measurements (CGM/BG) in the range from 3.9-10 mmol/L increased from 67.7%/67.2% (on Day 1) to 77.5%/78.6% (on the last day) (P<0.04). The number of low glycemic episodes (3.3 to <3.9 mmol/L) during nighttime detected by CGM was 15-fold higher, and the number of episodes >13.9 mmol/L detected by CGM during night was 12.5-fold higher than the values from the BG measurements. Ninety-nine percent of data points were in the clinically accurate or acceptable Clarke Error Grid Zones A+B, and the relative numbers of correctly identified episodes of <3.9 and >13.9 mmol/L detected by CGM (sensitivity) were 47.3% and 81.5%, respectively.

CONCLUSIONS

Our data exhibit a good agreement between overall CGM and BG measurements, but there were a high number of missed hypo- and hyperglycemic episodes with BG measurements, particularly during nighttime. Overall assessment of glycemic control using CGM is feasible, whereas the use of CGM for individualized therapy decisions needs further improvement.

Hypoglycemic Accuracy and Improved Low Glucose Alerts of the Latest Dexcom G4 Platinum Continuous Glucose Monitoring System

OBJECTIVE

Accuracy of continuous glucose monitoring (CGM) devices in hypoglycemia has been a widely reported shortcoming of this technology. We report the accuracy in hypoglycemia of a new version of the Dexcom (San Diego, CA) G4 Platinum CGM system (software 505) and present results regarding the optimum setting of CGM hypoglycemic alerts.

MATERIALS AND METHODS

CGM values were compared with YSI analyzer (YSI Life Sciences, Yellow Springs, OH) measurements every 15 min. We reviewed the accuracy of the CGM system in the hypoglycemic range using standard metrics. We analyzed the time required for the CGM system to detect biochemical hypoglycemia (70 mg/dL) compared with the YSI with alert settings at 70 mg/dL and 80 mg/dL. We also analyzed the time between the YSI value crossing 55 mg/dL, defined as the threshold for cognitive impairment due to hypoglycemia, and when the CGM system alerted for hypoglycemia.

RESULTS

The mean absolute difference for a glucose level of less than 70 mg/dL was 6 mg/dL. Ninety-six percent of CGM values were within 20 mg/dL of the YSI values between 40 and 80 mg/dL. When the CGM hypoglycemic alert was set at 80 mg/dL, the device provided an alert for biochemical hypoglycemia within 10 min in 95% of instances and at least a 10-min advance warning before the cognitive impairment threshold in 91% of instances in the study.

CONCLUSIONS

Use of an 80 mg/dL threshold setting for hypoglycemic alerts on the G4 Platinum (software 505) may provide patients with timely warning of hypoglycemia before the onset of cognitive impairment, enabling them to treat themselves for hypoglycemia with fast-acting carbohydrates and prevent neuroglycopenia associated with very low glucose levels.

Optimization of insulin pump therapy based on high order run-to-run control scheme

BACKGROUND AND OBJECTIVES

Continuous subcutaneous insulin infusion (CSII) pump is widely considered a convenience and promising way for type 1 diabetes mellitus (T1DM) subjects, who need exogenous insulin infusion. In the standard insulin pump therapy, there are two modes for insulin infusion: basal and bolus insulin. The basal-bolus therapy should be individualized and optimized in order to keep one subject's blood glucose (BG) level within the normal range; however, the optimization procedure is troublesome and it perturb the patients a lot. Therefore, an automatic adjustment method is needed to reduce the burden of the patients, and run-to-run (R2R) control algorithm can be used to handle this significant task.

METHODS

In this study, two kinds of high order R2R control methods are presented to adjust the basal and bolus insulin simultaneously. For clarity, a second order R2R control algorithm is first derived and studied. Furthermore, considering the differences between weekdays and weekends, a seventh order R2R control algorithm is also proposed and tested.

RESULTS

In order to simulate real situation, the proposed method has been tested with uncertainties on measurement noise, drifts, meal size, meal time and snack. The proposed method can converge even when there are ±60 min random variations in meal timing or ±50% random variations in meal size.

CONCLUSIONS

According to the robustness analysis, one can see that the proposed high order R2R has excellent robustness and could be a promising candidate to optimize insulin pump therapy.

Effect of Continuous Glucose Monitoring Accuracy on Clinicians' Retrospective Decision Making in Diabetes: A Pilot Study

BACKGROUND

The use of continuous glucose monitoring (CGM) in clinical decision making in diabetes could be limited by the inaccuracy of CGM data when compared to plasma glucose measurements. The aim of the present study is to investigate the impact of CGM numerical accuracy on the precision of diabetes treatment adjustments.

METHOD

CGM profiles with maximum 5-day duration from 12 patients with type 1 diabetes treated with a basal-bolus insulin regimen were processed by 2 CGM algorithms, with the accuracy of algorithm 2 being higher than the accuracy of algorithm 1, using the median absolute relative difference (MARD) as the measure of accuracy. During 2 separate and similar occasions over a 1-month interval, 3 clinicians reviewed the processed CGM profiles, and adjusted the dose level of basal and prandial insulin. The precision of the dosage adjustments were defined in terms of the interclinician agreement and the intraclinician reproducibility of the decisions. The Cohen's kappa coefficient was used to assess the precision of the decisions. The study was based on retrospective and blind CGM data.

RESULTS

For the interclinician agreement, in the first occasion, the kappa of algorithm 1 was .32, and that of algorithm 2 was .36. For the interclinician agreement, in the second occasion, the kappas of algorithms 1 and 2 were .17 and .22, respectively. For the intraclinician reproducibility of the decisions, the kappas of algorithm 1 were .35, .22, and .80 and the kappas of algorithm 2 were .44, .52, and .32, for the 3 clinicians, respectively. For the interclinician agreement, the relative kappa change from algorithm 1 to algorithm 2 was 86.06%, and for the intraclinician reproducibility, the relative kappa change from algorithm 1 to algorithm 2 was 53.99%.

CONCLUSIONS

Results indicated that the accuracy of CGM algorithms might potentially affect the precision of the CGM-based insulin adjustments for type 1 diabetes patients. However, a larger study with several clinical centers, with higher number of clinicians and patients is required to validate the impact of CGM accuracy on decisions precision.

HypoDE: Research Design and Methods of a Randomized Controlled Study Evaluating the Impact of Real-Time CGM Usage on the Frequency of CGM Glucose Values <55 mg/dl in Patients With Type 1 Diabetes and Problematic Hypoglycemia Treated With Multiple Daily Injections

Systems for continuous glucose monitoring (CGM) have been available for a number of years, and numerous clinical studies have been performed with them. Interestingly, in many of these studies patients with an increased risk of hypoglycemic events were excluded. In addition, in most studies subjects were using a pump for insulin delivery. Therefore our knowledge about the benefit of CGM in patients employing multiple daily injections (MDI) of insulin is limited, especially when it comes to a reduction in the risk of low glucose events in high-risk individuals. We are planning to run a 26-week randomized controlled study in Germany (HypoDE, Hypoglycemia in Deutschland) that is focused on evaluating if such a reduction can be observed in patients on MDI with an increased risk of low glucose events. In all, 160 patients will participate in the study, randomized into the intervention group and control group. Ideally one would study if the frequency of severe hypoglycemic events is different between both groups. However, this would require such a large sample size and study duration, so for pragmatic reasons we will use low glucose levels <55 mg/dl (measured by CGM) for at least 20 minutes as a risk marker for severe hypoglycemic events. The results from the HypoDE study shall help determine the advantage of using CGM in subjects with type 1 diabetes with an increased risk of low glucose events treated with MDI.

Accuracy of two continuous glucose monitoring systems: a head-to-head comparison under clinical research centre and daily life conditions

AIMS

To assess the accuracy and reliability of the two most widely used continuous glucose monitoring (CGM) systems.

METHODS

We studied the Dexcom®G4 Platinum (DG4P; Dexcom, San Diego, CA, USA) and Medtronic Paradigm Veo Enlite system (ENL; Medtronic, Northridge, CA, USA) CGM systems, in 24 patients with type 1 diabetes. The CGM systems were tested during 6-day home use and a nested 6-h clinical research centre (CRC) visit. During the CRC visit, frequent venous blood glucose samples were used as reference while patients received a meal with an increased insulin bolus to induce an aggravated postprandial glucose nadir. At home, patients performed at least six reference capillary blood measurements per day. A Wilcoxon signed-rank test was performed using all data points ≥15 min apart.

RESULTS

The overall mean absolute relative difference (MARD) value [standard deviation (s.d.)] measured at the CRC was 13.6 (11.0)% for the DG4P and 16.6 (13.5)% for the ENL [p < 0.0002, confidence interval of difference (CI Δ) 1.7-4.3%, n = 530]. The overall MARD assessed at home was 12.2 (12.0)% for the DG4P and 19.9 (20.5)% for the ENL (p < 0.0001, CI Δ = 5.8-8.7%, n = 839). During the CRC visit, the MARD in the hypoglycaemic range [≤3.9 mmol/l (70 mg/dl)], was 17.6 (12.2)% for the DG4P and 24.6 (18.8)% for the ENL (p = 0.005, CI Δ 3.1-10.7%, n = 117). Both sensors showed higher MARD values during hypoglycaemia than during euglycaemia [3.9-10 mmol/l (70-180 mg/dl)]: for the DG4P 17.6 versus 13.0% and for the ENL 24.6 versus 14.2%.

CONCLUSIONS

During circumstances of intended use, including both a CRC and home phase, the ENL was noticeably less accurate than the DG4P sensor. Both sensors showed lower accuracy in the hypoglycaemic range. The DG4P was less affected by this negative effect of hypoglycaemia on sensor accuracy than was the ENL.

A comparison of continuous intravenous insulin and subcutaneous insulin among patients with type 2 diabetes and congestive heart failure exacerbation

BACKGROUND

The study aims to determine whether the route of insulin administration influences glycaemic variability and inflammatory or neurohormonal markers in patients with type 2 diabetes and congestive heart failure (CHF) exacerbation.

METHODS

Patients (n = 65) were randomized to intravenous (IV) insulin (duration 48 h) or subcutaneous (SQ) insulin. Inflammatory cytokines and markers of lipid oxidation, high-frequency heart rate variability (n = 27) and cardiac impedance (pre-ejection period, n = 28) were used to estimate parasympathetic and sympathetic tone in patients with valid cardiac data. Glycaemic variability was measured using a continuous glucose monitor.

RESULTS

Mean glucose was lower (7.7 ± 1.2 vs 9.4 ± 2.7 mmol/L, p = 0.004), coefficient of variation was higher (p = 0.03) and glycaemic lability index was similar on day 1 in the IV group compared with the SQ group, but groups were similar by day 2. The IV group had more confirmed hypoglycaemia (p = 0.005). There were no differences in hospital readmission or hospital length of stay between groups. There were no differences in CHF biomarkers, heart rate variability or pre-ejection period between groups. Increasing log glycaemic lability index was associated with lower on-treatment pre-ejection period (p = 0.03) while increasing coefficient of variation was associated with increasing brain natriuretic peptide (p = 0.004) and paroxonase-1 (p = 0.02). Other univariable analyses were not significant.

CONCLUSIONS

There were modest, transient differences in glucose control between IV and SQ insulin in hospitalized CHF patients. However, the analyses do not support a link between insulin route and inflammatory markers or autonomic tone. Further study is needed to assess outcomes in hospitalized CHF patients.

Association between post-dinner dietary intakes and nocturnal hypoglycemic risk in adult patients with type 1 diabetes

AIMS

To describe (i) current bedtime nutritional practices and (ii) the association between post-dinner dietary intake and the occurrence of non-severe nocturnal hypoglycemia (NH) in real-life conditions among adult patients with type 1 diabetes using insulin analogs.

METHODS

One hundred adults (median [interquartile range]: age 46.4 [36.0-55.8] years, HbA1c 7.9 [7.3-8.6] % (63 [56-70] mmol/mol)) using multiple daily injections (n=67) or insulin pump (n=33) wore a blinded continuous glucose monitoring system and completed a food diary for 72-h.

RESULTS

NH occurred on 28% of 282 nights analyzed. (i) Patients reported post-dinner dietary intakes on 63% of the evenings. They injected rapid-acting insulin boluses on 64 occasions (23% of 282 evenings). These insulin boluses were mostly injected with (n=37) dietary intakes. (ii) Post-dinner dietary intake was not associated with NH occurrence in univariate analyses. In multivariate analyses, the injection of rapid-acting insulin modulated the association between post-dinner dietary intake and NH: with insulin, post-dinner carbohydrate intake was positively associated with NH (odds ratio (OR): 1.16 [95% confidence interval, CI: 1.04-1.29] per 5g increase, p=0.008); without insulin, post-dinner protein intake was inversely associated with NH occurrence (OR [95% CI]: 0.88 [0.78-1.00] per 2g increase, p=0.048).

CONCLUSIONS

NH remains frequent in adults with type 1 diabetes. There is a complex relationship between post-dinner dietary intake and NH occurrence, including the significant role of nutrient content and rapid-acting insulin injection that requires further investigation.

Accuracy evaluation of a new real-time continuous glucose monitoring algorithm in hypoglycemia

BACKGROUND

The purpose of this study was to evaluate the performance of a new continuous glucose monitoring (CGM) calibration algorithm and to compare it with the Guardian(®) REAL-Time (RT) (Medtronic Diabetes, Northridge, CA) calibration algorithm in hypoglycemia.

SUBJECTS AND METHODS

CGM data were obtained from 10 type 1 diabetes patients undergoing insulin-induced hypoglycemia. Data were obtained in two separate sessions using the Guardian RT CGM device. Data from the same CGM sensor were calibrated by two different algorithms: the Guardian RT algorithm and a new calibration algorithm. The accuracy of the two algorithms was compared using four performance metrics.

RESULTS

The median (mean) of absolute relative deviation in the whole range of plasma glucose was 20.2% (32.1%) for the Guardian RT calibration and 17.4% (25.9%) for the new calibration algorithm. The mean (SD) sample-based sensitivity for the hypoglycemic threshold of 70 mg/dL was 31% (33%) for the Guardian RT algorithm and 70% (33%) for the new algorithm. The mean (SD) sample-based specificity at the same hypoglycemic threshold was 95% (8%) for the Guardian RT algorithm and 90% (16%) for the new calibration algorithm. The sensitivity of the event-based hypoglycemia detection for the hypoglycemic threshold of 70 mg/dL was 61% for the Guardian RT calibration and 89% for the new calibration algorithm. Application of the new calibration caused one false-positive instance for the event-based hypoglycemia detection, whereas the Guardian RT caused no false-positive instances. The overestimation of plasma glucose by CGM was corrected from 33.2 mg/dL in the Guardian RT algorithm to 21.9 mg/dL in the new calibration algorithm.

CONCLUSIONS

The results suggest that the new algorithm may reduce the inaccuracy of Guardian RT CGM system within the hypoglycemic range; however, data from a larger number of patients are required to compare the clinical reliability of the two algorithms.

A toolbox to improve algorithms for insulin-dosing decision support

BACKGROUND

Standardized insulin order sets for subcutaneous basal-bolus insulin therapy are recommended by clinical guidelines for the inpatient management of diabetes. The algorithm based GlucoTab system electronically assists health care personnel by supporting clinical workflow and providing insulin-dose suggestions.

OBJECTIVE

To develop a toolbox for improving clinical decision-support algorithms.

METHODS

The toolbox has three main components. 1) Data preparation: Data from several heterogeneous sources is extracted, cleaned and stored in a uniform data format. 2) Simulation: The effects of algorithm modifications are estimated by simulating treatment workflows based on real data from clinical trials. 3) ANALYSIS: Algorithm performance is measured, analyzed and simulated by using data from three clinical trials with a total of 166 patients.

RESULTS

Use of the toolbox led to algorithm improvements as well as the detection of potential individualized subgroup-specific algorithms.

CONCLUSION

These results are a first step towards individualized algorithm modifications for specific patient subgroups.

Accuracy and acceptability of the 6-day Enlite continuous subcutaneous glucose sensor

OBJECTIVE

This study evaluated the performance and acceptability of the Enlite(®) glucose sensor (Medtronic MiniMed, Inc., Northridge, CA).

SUBJECTS AND METHODS

Ninety adults with type 1 or type 2 diabetes wore two Enlite sensors on the abdomen and/or buttock for 6 days and calibrated them at different frequencies. On Days 1, 3, and 6, accuracy was evaluated by comparison of sensor glucose values with frequently sampled plasma glucose values collected over a 12-h period. Accuracy was assessed at different reference glucose concentrations and during times when absolute glucose concentration rates of change were <1, 1-2, and >2 mg/dL/min. The sensor's ability to detect hypoglycemia or hyperglycemia was evaluated with simulated alerts. Subject satisfaction was evaluated with a 7-point Likert-type questionnaire, with a score of 7 indicating strong agreement.

RESULTS

With abdomen sensors under actual-use calibration (mean, 2.8 ± 0.9 times/day), the overall mean (median) absolute relative difference (ARD) values between sensor and reference values were 13.6% (10.1%); the corresponding buttock sensor ARD values were 15.5% (10.5%). With abdomen sensors under minimal calibration (mean, 1.2 ± 0.9 times/day), the mean (median) ARD values were 14.7% (10.8%). Mean ARD values of abdomen sensors at rates of change of <1, 1-2, and >2 mg/dL/min were 13.6%, 12.9%, and 16.3%, respectively. With abdomen sensors, 79.5% and 94.1% of hypoglycemic and hyperglycemic events, respectively, were correctly detected; 81.9% and 94.9% of hypoglycemic and hyperglycemic alerts, respectively, were confirmed. The failure rates for abdomen and buttock sensors were 19.7% and 13.9%, respectively. Mean responses to survey questions for all subjects related to comfort and ease of use were favorable.

CONCLUSIONS

The Enlite sensor provided accurate data at different glucose concentrations and rates of change. Subjects found the sensor comfortable and easy to use.

The impact of continuous glucose monitoring on low interstitial glucose values and low blood glucose values assessed by point-of-care blood glucose meters: results of a crossover trial

In a randomized crossover trial the impact of continuous glucose monitoring (CGM) was tested on the occurrence of low blood glucose values measured by point of care (POC) measurement and on low glucose values measured by CGM in the interstitial fluid. A total of 41 type 1 diabetic patients (age 42.0 ± 11.4 years, diabetes duration 15.3 ± 10.1 years, A1c 8.2 ± 1.4%) used a CGM system (Dexcom SEVEN PLUS system) twice. In first study phase (CGM blind), patients were blind regarding the CGM current glucose levels and were not alerted when critical glucose values were reached. In the second phase (CGM real time), patients had access to current glucose levels and were alerted if critical glucose values were reached. During CGM real time the proportion of hypoglycemic POC blood glucose values were significantly reduced (7.5 ± 5.6% vs 10.1 ± 7.5%; P = .04), whereas the proportion of euglycemic blood glucose values were significantly enhanced (73.7 ± 18.3% vs 68.3 ± 12.1%; P = .01). The duration of low glucose periods in the interstitial fluid was significantly lower in the CGM real time phase (125 ± 89 vs 181 ± 125 minutes per day; P = .005). The time until a low blood glucose was detected by POC measurement was shortened by 33.2 ± 76.1 minutes (P = .03). The study demonstrated that CGM is able to not only reduce duration of hypoglycemia measured by CGM in interstitial fluid, but also reduce the proportion of low POC blood glucose measurements. In addition, hypoglycemia can be detected earlier.

The Impact of Nocturnal Hypoglycemia on Clinical and Cost-Related Issues in Patients With Type 1 and Type 2 Diabetes

PURPOSE

This article provides an overview of the clinical and economic issues associated with hypoglycemia in patients with type 1 and type 2 diabetes mellitus. Current research regarding hypoglycemia is comprehensively reviewed, with special emphasis on nocturnal hypoglycemia, as almost 50% of all severe hypoglycemic episodes occur at nighttime during sleep. Current findings on the economic and human burden of hypoglycemia are presented.

CONCLUSIONS

Poor diabetes self-management leads to an increased risk for hypoglycemia and the development of long-term complications associated with poor glycemic control. Hypoglycemia is also associated with increased health care costs and resources required to treat hypoglycemic events, as well as personal financial costs and loss of productivity at school or work. In addition, fear, anxiety, and worry about hypoglycemic episodes are shown to interfere with patients' quality of life. Nocturnal hypoglycemia can cause a number of immediate clinical consequences, including convulsions, coma, and even death. Repeated long-term exposure to nocturnal hypoglycemia can blunt counterregulatory mechanisms that maintain glucose levels, leading to reduced cognitive function, impaired awareness of hypoglycemia, and hypoglycemia-associated autonomic failure. Clinicians must be aware of the impact of hypoglycemia, particularly nocturnal hypoglycemia, so that they can prescribe appropriate glucose-lowering therapy and educate patients about the prevention and management of hypoglycemic events to reduce anxiety and improve quality of life.

When hypoglycemia is not obvious: diagnosing and treating under-recognized and undisclosed hypoglycemia

Hypoglycemia continues to be a significant problem for patients with diabetes. The incidence remains high but patients may also be under-reporting hypoglycemic events for various reasons, including hypoglycemia unawareness and deliberate non-reporting. This restricts the ability of healthcare professionals to manage treatment effectively. The aim of this article is to focus specifically on the issues associated with hypoglycemia unawareness and undisclosed hypoglycemia. The article provides general practice teams with an overview of these problems and, through patient narratives, suggests ways to mitigate them.

Poincaré plot quantification for assessing glucose variability from continuous glucose monitoring systems and a new risk marker for hypoglycemia: application to type 1 diabetes patients switching to continuous subcutaneous insulin infusion

BACKGROUND

The Poincaré plot (PCP) is a valuable tool for describing glucose variability (GV) from continuous glucose monitoring (CGM) but remains only visual and qualitative. The aim of this work was to validate metrics for the geometry of the PCP in type 1 diabetes and to apply them to the study of a series of patients switching to continuous subcutaneous insulin infusion (CSII).

PATIENTS AND METHODS

We reviewed the CGM profiles of 44 patients with type 1 diabetes. A subgroup (n=13) used CGM before and after 6 months on CSII. Additionally, we prospectively collected seven recordings from healthy controls. The new PCP metrics were correlated with hypoglycemia and classical GV indices and were compared between groups.

RESULTS

SDs related to the PCP fitting ellipse (SD1, SD2) and area and shape of the fitting ellipse (SFE) were all higher in diabetes patients than in the controls and decreased significantly on CSII. SD1 represented short-term GV and was equivalent to continuous overlapping net glycemic action (CONGA). SD2 represented long-term GV and correlated with the SD of glucose levels (r ≥ 0.98), mean of daily differences (r ≥ 0.91), and mean amplitude of glycemic excursions (r ≥ 0.88). SFE correlated positively with CONGA at 1 h but not with the other indices and was inversely correlated with hypoglycemic episodes (Spearman's ρ=-0.42), independently of the coefficient of variation and the Low Blood Glucose Index in a multivariate analysis (partial r=-0.34).

CONCLUSIONS

PCP metrics are correlated with known GV indices and may be used for the study of CGM recording series in type 1 diabetes. SFE is a new risk marker for hypoglycemia.

Current Trends in Continuous Glucose Monitoring

The market introduction of systems for continuous glucose monitoring (CGM) some 15 years ago did not immediately revolutionize the treatment of diabetes; however, for a given group of patients, it would almost be inconceivable nowadays to imagine life without CGM. One day the development of insulin pumps together with CGM could culminate in an artificial pancreas system. The performance of the glucose sensors used for glucose measurement in the interstitial fluid in the subcutaneous tissue and the algorithms employed to analyze these data have improved so much over the past decade that current CGM systems by far outperform those of the first generations. This commentary discusses a number of aspects about what we have learned since CGM systems entered the market and what current trends exist in their usage. Some of these are major hurdles facing a more widespread usage of CGM.

Efficacy, usability and sequence of operations of a workflow-integrated algorithm for basal-bolus insulin therapy in hospitalized type 2 diabetes patients

AIMS

To evaluate glycaemic control and usability of a workflow-integrated algorithm for basal-bolus insulin therapy in a proof-of-concept study to develop a decision support system in hospitalized patients with type 2 diabetes.

METHODS

In this ward-controlled study, 74 type 2 diabetes patients (24 female, age 68 ± 11 years, HbA1c 8.7 ± 2.4% and body mass index 30 ± 7) were assigned to either algorithm-based treatment with a basal-bolus insulin therapy or to standard glycaemic management. Algorithm performance was assessed by continuous glucose monitoring and staff's adherence to algorithm-calculated insulin dose.

RESULTS

Average blood glucose levels (mmol/l) in the algorithm group were significantly reduced from 11.3 ± 3.6 (baseline) to 8.2 ± 1.8 (last 24 h) over a period of 7.5 ± 4.6 days (p < 0.001). The algorithm group had a significantly higher percentage of glucose levels in the ranges from 5.6 to 7.8 mmol/l (target range) and 3.9 to 10.0 mmol/l compared with the standard group (33 vs. 23% and 73 vs. 53%, both p < 0.001). Physicians' adherence to the algorithm-calculated total daily insulin dose was 95% and nurses' adherence to inject the algorithm-calculated basal and bolus insulin doses was high (98 and 93%, respectively). In the algorithm group, significantly more glucose values <3.9 mmol/l were detected in the afternoon relative to other times (p < 0.05), a finding mainly related to pronounced morning glucose excursions and requirements for corrective bolus insulin at lunch.

CONCLUSIONS

The workflow-integrated algorithm for basal-bolus therapy was effective in establishing glycaemic control and was well accepted by medical staff. Our findings support the implementation of the algorithm in an electronic decision support system.

Reduced Glycemic Variability in Diazoxide-Responsive Children with Congenital Hyperinsulinism Using Supplemental Omega-3-Polyunsaturated Fatty Acids; A Pilot Trial with MaxEPA(R.)

OBJECTIVE

Congenital hyperinsulinism (CHI) is a rare condition of hypoglycemia where therapeutic options are limited and often complicated by side-effects. Omega-3-polyunsaturated fatty acids (PUFA), which can suppress cardiac myocyte electrical activity, may also reduce ion channel activity in insulin-secreting cells. PUFA supplements in combination with standard medical treatment may improve glucose profile and may reduce glycemic variability in diazoxide-responsive CHI.

DESIGN

Open label pilot trial with MaxEPA(R) liquid (eicosapentaenoic and docosahexaenoic acid) PUFA (3 ml/day for 21 days) in diazoxide-responsive CHI patients (https://eudract.ema.europa.eu/, EudraCT number 201100363333).

METHODS

Glucose levels were monitored pre-treatment, end of treatment, and at follow-up by subcutaneous continuous glucose monitoring systems (CGMS) in 13 patients (7 girls) who received PUFA. Outcome measures were an improved glucose profile, reduced glycemic variability quantified by a reduction in the frequency of glucose levels <4 and >10 mmol/l, and safety of PUFA. All children were analyzed either as intention to treat (n = 13) or as per protocol (n = 7).

RESULTS

Mean (%) CGMS glucose levels increased by 0.1 mmol/l (2%) in intention to treat and by 0.4 mmol/l (8%) in per protocol analysis (n = 7). The frequency of CGMS <4 mmol/l was significantly less at the end of treatment than in the pre-treatment period [556 (7%) vs. 749 (10%)]. Similarly, the frequency of CGMS >10 mmol/l, was also less at the end of treatment [27 (0.3%) vs. 49 (0.7%)]. Except for one child with increased LDL cholesterol, all safety parameters were normal.

CONCLUSION

MaxEPA(R) was safe and reduced glycemic variability, but did not increase glucose profiles significantly in diazoxide-responsive CHI. The supplemental value of PUFA should be evaluated in a comprehensive clinical trial.

Accuracy of a Novel Noninvasive Multisensor Technology to Estimate Glucose in Diabetic Subjects During Dynamic Conditions

The purpose of this study was to determine whether an approach of multisensor technology with integrated data analysis in an armband system (SenseWear® Pro Armband, SWA) can provide estimates of plasma glucose concentration in diabetes. In all, 41 subjects with diabetes participated. On day 1 subjects underwent an oral glucose tolerance test (OGTT) and on day 2 a 60-minute treadmill test (TT). SWA plasma glucose estimates were compared against reference peripheral venous glucose concentrations. A continuous glucose monitoring device (CGM) was also placed on each subject to serve as a reference for clinical comparison. Pearson coefficient, Clarke error grid (CEG), and mean absolute relative difference (MARD) analyses were used to compare the performance of plasma glucose estimation. There were significant correlations between plasma glucose concentrations estimated by the SWA and the reference plasma glucose concentration during the OGTT (r = .65, P < .05) and the TT (r = .91, P < .05). CEG analysis revealed that during the OGTT, 93% of plasma glucose concentration readings were in the clinically acceptable zone A+B for the SWA and 95% for the CGM. During the TT, the SWA had 96% of readings in zone A+B, compared to 97% for the CGM. During OGTTs, MARDs for the SWA and CGM were 26% and 18%, respectively. During TTs, MARDs were 16% and 12%, respectively. Plasma glucose concentration estimation by the SWA's noninvasive multisensor approach appears to be feasible and its performance in estimating glucose approaches that of a CGM. The success of this pilot study suggests that multisensor technology holds promising potential for the development of a wearable, noninvasive, painless glucose monitor.

Evaluation of the performance of a novel system for continuous glucose monitoring

BACKGROUND

The performance of a continuous glucose monitoring (CGM) system in the early stage of development was assessed in an inpatient setting that simulates daily life conditions of people with diabetes. Performance was evaluated at low glycemic, euglycemic, and high glycemic ranges as well as during phases with rapid glucose excursions.

METHODS

Each of the 30 participants with type 1 diabetes (15 female, age 47 ± 12 years, hemoglobin A1c 7.7% ± 1.3%) wore two sensors of the prototype system in parallel for 7 days. Capillary blood samples were measured at least 16 times per day (at least 15 times per daytime and at least once per night). On two subsequent study days, glucose excursions were induced. For performance evaluation, the mean absolute relative difference (MARD) between CGM readings and paired capillary blood glucose readings and precision absolute relative difference (PARD), i.e., differences between paired CGM readings were calculated.

RESULTS

Overall aggregated MARD was 9.2% and overall aggregated PARD was 7.5%. During induced glucose excursions, MARD was 10.9% and PARD was 7.8%. Lowest MARD (8.5%) and lowest PARD (6.4%) were observed in the high glycemic range (euglycemic range, MARD 9.1% and PARD 7.4%; low glycemic range, MARD 12.3% and PARD 12.4%).

CONCLUSIONS

The performance of this prototype CGM system was, particularly in the hypoglycemic range and during phases with rapid glucose fluctuations, better than performance data reported for other commercially available systems. In addition, performance of this prototype sensor was noticeably constant over the whole study period. This prototype system is not yet approved, and performance of this CGM system needs to be further assessed in clinical studies.

Performance evaluation of a continuous glucose monitoring system under conditions similar to daily life

BACKGROUND

This study aimed at evaluating and comparing the performance of a new generation of continuous glucose monitoring (CGM) system versus other CGM systems, under daily lifelike conditions.

METHODS

A total of 10 subjects (7 female) were enrolled in this study. Each subject wore two Dexcom G4™ CGM systems in parallel for the sensor lifetime specified by the manufacturer (7 days) to allow assessment of sensor-to-sensor precision. Capillary blood glucose (BG) measurements were performed at least once per hour during daytime and once at night. Glucose excursions were induced on two occasions. Performance was assessed by calculating the mean absolute relative difference (MARD) between CGM readings and paired capillary BG readings and precision absolute relative difference (PARD), i.e., differences between paired CGM readings.

RESULTS

Overall aggregate MARD was 11.0% (n = 2392). Aggregate MARD for BG &lt;70 mg/dl was 13.7%; for BG between 70 and 180 mg/dl, MARD was 11.4%; and for BG &gt;180 mg/dl, MARD was 8.5%. Aggregate PARD was 7.3%, improving from 11.6% on day 1 to 5.2% on day 7.

CONCLUSIONS

The Dexcom G4 CGM system showed good overall MARD compared with results reported for other commercially available CGM systems. In the hypoglycemic range, where CGM performance is often reported to be low, the Dexcom G4 CGM system achieved better MARD than that reported for other CGM systems in the hypoglycemic range. In the hyperglycemic range, the MARD was comparable to that reported for other CGM systems, whereas during induced glucose excursions, the MARD was similar or slightly worse than that reported for other CGM systems. Overall PARD was 7.3%, improving markedly with sensor life time.

Performance evaluation of three continuous glucose monitoring systems: comparison of six sensors per subject in parallel

BACKGROUND

This study is aimed at comparing the performance of three continuous glucose monitoring (CGM) systems following the Clinical and Laboratory Standards Institute's POCT05-A guideline, which provides recommendations for performance evaluation of CGM systems.

METHODS

A total of 12 subjects with type 1 diabetes were enrolled in this study. Each subject wore six CGM systems in parallel, two sensors of each CGM system [FreeStyle Navigator™ (Navigator), MiniMed Guardian® REAL-Time with Enlite sensor (Guardian), DexCom™ Seven® Plus 3rd generation (Seven Plus)]. Each sensor was used for the lifetime specified by the manufacturer. To follow POCT05-A recommendations, glucose excursions were induced on two separate occasions, and venous and capillary blood glucose (BG) concentrations were obtained every 15 min for five consecutive hours. Capillary BG concentrations were measured at least once per hour during the day and once at night. Parameters investigated were CGM-to-BG differences [mean absolute relative difference (MARD)] and sensor-to-sensor differences [precision absolute relative difference (PARD)].

RESULTS

Compared with capillary BG reference readings, the Navigator showed the lowest MARD, with 12.1% overall and 24.6% in the hypoglycemic range; for the Guardian and the Seven Plus, MARD was 16.2%/34.9% and 16.3%/32.7%, respectively. PARD also was lowest for the Navigator (9.6%/9.8%), followed by the Seven Plus (16.7%/25.5%) and the Guardian (18.1%/20.2%). During induced glucose excursions, MARD between CGM and BG was, again, lowest for the Navigator (14.3%), followed by the Seven Plus (15.8%) and the Guardian (19.2%).

CONCLUSIONS

In this study, two sensors of each of the three CGM systems were compared in a setting following POCT05-A recommendations. The Navigator CGM system achieved more accurate results than the Guardian or the Seven Plus with respect to MARD and PARD. Performance in the hypoglycemic range was markedly worse for all CGM systems when compared with BG results.

Effect of the approach to insulin therapy on glycaemic fluctuations and autonomic tone in hospitalized patients with diabetes

AIMS

Glycaemic variability (GV) is associated with mortality in acutely ill patients, but the mechanism is unknown. The objective of this study is to determine whether common approaches to insulin therapy have distinct effects on GV and autonomic tone.

METHODS

Hospitalized patients with diabetes were randomized to short-term intravenous (IV) or physiologic subcutaneous (SQ) insulin. Heart rate variability (HRV) and cardiac impedance (pre-ejection period, PEP) were used to estimate parasympathetic and sympathetic tone, respectively. GV was measured using a continuous glucose monitor.

RESULTS

Mean glucose tended to be lower initially in the SQ group (N = 16) compared with the IV group (N = 17) on day 1 (10.5 vs. 8.6 mmol/l, p = 0.05), but became non-significant during the transition off of the infusion. There was no difference in glycaemic lability index (GLI), continuous overlapping net glycaemic action (CONGA) or coefficient of variation (CV) on day 1, but by day 2, these measures were higher in the IV group (p < 0.05 for all). PEP was higher in the SQ group during (110 vs. 123 ms, p = 0.02) and after the intervention (104 vs. 126 ms, p = 0.004). Hypoglycaemia was similar in both groups. There were only small differences in HRV. Post-treatment PEP was inversely correlated with log GLI (r = -0.41, p = 0.03) but not other measures.

CONCLUSIONS

Short-term IV insulin is associated with an increase in multiple GV measures compared with optimal SQ insulin. However, GLI was the only predictor of PEP. Further research is needed to determine if interventions that minimize GV improve outcomes in the hospital.

"Turn it off!": diabetes device alarm fatigue considerations for the present and the future

Safe and widespread use of diabetes technology is constrained by alarm fatigue: when someone receives so many alarms that he or she becomes less likely to respond appropriately. Alarm fatigue and related usability issues deserve consideration at every stage of alarm system design, especially as new technologies expand the potential number and complexity of alarms. The guiding principle should be patient wellbeing, while taking into consideration the regulatory and liability issues that sometimes contribute to building excessive alarms. With examples from diabetes devices, we illustrate two complementary frameworks for alarm design: a "patient safety first" perspective and a focus on human factors. We also describe opportunities and challenges that will come with new technologies such as remote monitoring, adaptive alarms, and ever-closer integration of glucose sensing with insulin delivery.

The role of continuous glucose monitoring in the care of children with type 1 diabetes

Continuous glucose monitoring (CGM), while a relatively new technology, has the potential to transform care for children with type 1 diabetes. Some, but not all studies, have shown that CGM can significantly improve hemoglobin A1c levels and reduce time spent in the hypoglycemic range in children, particularly when used as part of sensor-augmented pump (SAP) therapy. Despite the publication of recent clinical practice guidelines suggesting CGM be offered to all children 8 years of age or older who are likely to benefit, and studies showing that younger children can also benefit, this technology is not yet commonly used by children with type 1 diabetes. Effects of CGM are enhanced when used on a near-daily basis (a use-dependent effect) and with insulin pump therapy. Therefore, coordinated strategies are needed to help children and their families initiate and continue to use this resource for diabetes care. This review introduces CGM to pediatric endocrinologists who are not yet familiar with the finer details of this technology, summarizes current data showing the benefits and limitations of CGM use in children, reviews specific case examples demonstrating when CGM can be helpful, and shows the value of both retrospective and real-time CGM. It is hoped that this information leads to discussion of this technology in pediatric endocrinology clinics as an important next step in improving the care of children with type 1 diabetes.

A standard approach to continuous glucose monitor data in pregnancy for the study of fetal growth and infant outcomes

The power of continuous glucose monitoring system (CGMS) technology to profile glycemic patterns throughout a 24-h period has benefited the care of individuals with diabetes mellitus for over 10 years. Recently, this technology has been utilized to better understand glucose patterns in pregnancy, especially as they relate to abnormal fetal growth given that adiposity at birth is associated with increased risks for childhood obesity and metabolic syndrome. However, the lack of a standardized approach to defining glucose measures associated with maternal outcomes and fetal growth has greatly limited comparison and pooling of CGMS data among pregnancy trials, hindering our ability to take advantage of the enormous amount of data available to explore these relationships. The purpose of this article is to offer a methodical approach to the identification and extraction of CGMS-derived glucose variables for the characterization of glycemic profiles in pregnant women, particularly focusing on women with gestational diabetes or obesity who are at risk for abnormal fetal growth. A review of the properties of CGMS data and examples of how CGMS data in pregnancy have been reported to date are included. We further define several pregnancy-relevant, CGMS-derived glucose variables and directly apply them to unpublished data to illustrate how these measures might be utilized. This approach offers one possible standardized method to define and analyze these time-sensitive glucose measures to facilitate comparisons among studies and to increase our understanding of how glycemic profiles contribute to excess infant adiposity in pregnant women with and without diabetes.

Professional continuous glucose monitoring in subjects with type 1 diabetes: retrospective hypoglycemia detection

BACKGROUND

An important task in diabetes management is detection of hypoglycemia. Professional continuous glucose monitoring (CGM), which produces a glucose reading every 5 min, is a powerful tool for retrospective identification of unrecognized hypoglycemia. Unfortunately, CGM devices tend to be inaccurate, especially in the hypoglycemic range, which limits their applicability for hypoglycemia detection. The objective of this study was to develop an automated pattern recognition algorithm to detect hypoglycemic events in retrospective, professional CGM.

METHOD

Continuous glucose monitoring and plasma glucose (PG) readings were obtained from 17 data sets of 10 type 1 diabetes patients undergoing insulin-induced hypoglycemia. The CGM readings were automatically classified into a hypoglycemic group and a nonhypoglycemic group on the basis of different features from CGM readings and insulin injection. The classification was evaluated by comparing the automated classification with PG using sample-based and event-based sensitivity and specificity measures.

RESULTS

With an event-based sensitivity of 100%, the algorithm produced only one false hypoglycemia detection. The sample-based sensitivity and specificity levels were 78% and 96%, respectively.

CONCLUSIONS

The automated pattern recognition algorithm provides a new approach for detecting unrecognized hypoglycemic events in professional CGM data. The tool may assist physicians and diabetologists in conducting a more thorough evaluation of the diabetes patient's glycemic control and in initiating necessary measures for improving glycemic control.