Mitigation of Rebound Hyperglycemia With Real-Time Continuous Glucose Monitoring Data and Predictive Alerts

Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia

Differences in the effectiveness of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) in type 1 diabetes (T1D) are reported. The impact on percent time in range of switching from an isCGM with glucose threshold-based optional alerts only (FreeStyle Libre 2 [FSL2]) to an rtCGM (Dexcom G7) with an urgent low soon predictive alert was assessed, alongside other secondary outcomes including hemoglobin A1c (HbA1c) and other continuous glucose monitoring metrics. Adults with T1D using FSL2 were switched to Dexcom G7 for 12 weeks. HbA1c and continuous glucose data during FSL2 and Dexcom G7 use were compared. Data from 29 participants (aged 44.8 ± 16.5 years, 12 male and 17 female) were analyzed. After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006) and had higher percentage achievement of time below 3.9 mmol/L (70 mg/dL) of <4% (55.2% vs. 82.8%, P = 0.005). Coefficient of variation was lower (39.3 ± 6.6% vs. 37.2 ± 5.6%, P = 0.008). In conclusion, adults with T1D who switched from isCGM to rtCGM may benefit from reduced exposure to hypoglycemia and glycemic variability.

Glycemic variability through the perspective of the glycemia risk index and time in range and their association with glycated hemoglobin A1c in pediatric patients on sensor-augmented pump therapy

Introduction

From the introduction of continuous glucose monitoring (CGM) in treatments of type 1 diabetes, particularly its integration with insulin pumps, there has been a quest for new parameters that describe optimal glycemic control. As of the consensus reached in 2019, the ambulatory glucose profile (AGP) has become the standard, with time in range (TIR) emerging as a fundamental parameter for metabolic control assessment. However, with technological advancements, new parameters, such as the glycemia risk index (GRI), have been introduced and clinically utilized. Therefore, exploring the relationships between traditional and novel parameters to understand metabolic control comprehensively is imperative.

Materials and methods

This study was conducted at the Pediatric Clinic of the University Hospital of the Republic of Srpska Banja Luka between January and July 2023. The participants were randomly selected, with the inclusion criteria specifying an age greater than eight years and a diabetes type 1 duration exceeding two years. All participants were required to use a sensor-augmented insulin pump for the next three months (90 days), irrespective of prior use, with the suspend-before-low option activated.

Results

Of the 35 participants, 30 completed the study, 14 (46.7%) of whom were male. The mean age of the subjects was 14.90 ± 2.88 years, and the mean duration of diabetes was 7.83 ± 4.76 years. Over the 90-day period, HbA1c increased to an average of 7.31%. The analysis revealed significant effects of TIR (β=-0.771) and GRI (β=0.651) on HbA1c. Furthermore, GRI and TIR strongly correlated (β=-0.953).

Discussion and conclusion

New parameters generated from the ambulatory glucose profile (AGP) can help clinicians create a complete picture of a patient's metabolic control in relation to HbA1c levels. Additionally, the GRI is a mathematically tailored parameter that incorporates all components of the ambulatory glucose profile and demonstrates strong correlations with laboratory-measured HbA1c and TIR. The GRI potentially can become a valuable statistical parameter for evaluating and managing patients in routine clinical practice.

Integration of a Safety Module to Prevent Rebound Hypoglycemia in Closed-Loop Artificial Pancreas Systems

BACKGROUND

With automated insulin delivery (AID) systems becoming widely adopted in the management of type 1 diabetes, we have seen an increase in occurrences of rebound hypoglycemia or generated hypoglycemia induced by the controller's response to rapid glucose rises following rescue carbohydrates. Furthermore, as AID systems aim to enable complete automation of prandial control, algorithms are designed to react even more strongly to glycemic rises. This work introduces a rebound hypoglycemia prevention layer (HypoSafe) that can be easily integrated into any AID system.

METHODS

HypoSafe constrains the maximum permissible insulin delivery dose based on the minimum glucose reading from the previous hour and the current glucose level. To demonstrate its efficacy, we integrated HypoSafe into the latest University of Virginia (UVA) AID system and simulated two scenarios using the 100-adult cohort of the UVA/Padova T1D simulator: a nominal case including three unannounced meals, and another case where hypoglycemia was purposely induced by an overestimated manual bolus.

RESULTS

In both simulation scenarios, rebound hypoglycemia events were reduced with HypoSafe (nominal: from 39 to 0, hypo-induced: from 55 to 7) by attenuating the commanded basal (nominal: 0.27U vs. 0.04U, hypo-induced: 0.27U vs. 0.03U) and bolus (nominal: 1.02U vs. 0.05U, hypo-induced: 0.43U vs. 0.02U) within the 30-minute interval after treating a hypoglycemia event. No clinically significant changes resulted for time in the range of 70 to 180 mg/dL or above 180 mg/dL.

CONCLUSION

HypoSafe was shown to be effective in reducing rebound hypoglycemia events without affecting achieved time in range when combined with an advanced AID system.

Pen-administered low-dose dasiglucagon vs usual care for prevention and treatment of non-severe hypoglycaemia in people with type 1 diabetes during free-living conditions: a Phase II, randomised, open-label, two-period crossover trial

AIMS/HYPOTHESIS

Consumption of excess carbohydrates to manage hypoglycaemia can lead to rebound hyperglycaemia and promote weight gain. The objective of this trial was to evaluate the efficacy, safety and feasibility of pen-administered low-dose dasiglucagon for prevention and treatment of non-severe hypoglycaemia in people with type 1 diabetes during free-living conditions.

METHODS

Twenty-four adults with insulin pump-treated type 1 diabetes (HbA1c ≤70 mmol/mol [8.5%]) completed a randomised, open-label, two-period crossover study with 2 week periods. During the usual care and dasiglucagon intervention (DASI) periods, participants managed impending and manifested episodes of hypoglycaemia with regular carbohydrate consumption or pen-administered low-dose (80 μg) s.c. dasiglucagon, respectively. Glycaemic control was evaluated using continuous glucose monitoring (Dexcom G6) and event registration of prevention and treatment episodes.

RESULTS

Compared with usual care, the mean difference (95% CI) in the DASI period for time in (3.9-10.0 mmol/l) and below (<3.9 mmol/l) range was 2.4 %-points (-0.7, 5.5) and -0.5 %-points (-1.2, 0.2), respectively. In the DASI period, recovery rate (time from hypoglycaemia treatment to euglycaemia) was 44% (11, 87) faster while total daily carbohydrate intake was reduced by 11% (-18, -3). Dasiglucagon use was safe and well tolerated with mild nausea being the most frequent adverse effect. Among the participants, 96% (p<0.0001) were likely to include dasiglucagon in their future routine management of hypoglycaemia.

CONCLUSIONS/INTERPRETATION

Use of low-dose dasiglucagon to prevent and treat non-severe hypoglycaemia during free-living conditions was safe, fast and efficacious while significantly reducing the total daily carbohydrate intake and yielding high treatment satisfaction.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04764968 FUNDING: The study was an investigator-initiated trial. Zealand Pharma supplied the investigational drug and device and provided financial support for the conduct of the trial.

Rebound Hypoglycemia and Hyperglycemia in Type 1 Diabetes

AIMS

The aim was to investigate rebound hypoglycemic and hyperglycemic events, and describe their relation to other glycemic metrics.

METHODS

Data from intermittently scanned continuous glucose monitoring were downloaded for 90 days for 159 persons with type 1 diabetes. A hypoglycemic event was defined as glucose <3.9 mmol/l for at least two 15-minute periods. Rebound hypoglycemia (Rhypo) was a hypoglycemic event preceded by glucose >10.0 mmol/l within 120 minutes and rebound hyperglycemia (Rhyper) was hypoglycemia followed by glucose >10.0 mmol/l within 120 minutes.

RESULTS

A total of 10 977 hypoglycemic events were identified of which 3232 (29%) were Rhypo and 3653 (33%) were Rhyper, corresponding to a median frequency of 10.1, 2.5, and 3.0 events per person/14 days. For 1267 (12%) of the cases, Rhypo and Rhyper coexisted. The mean peak glucose was 13.0 ± 1.6 mmol/l before Rhypo; 12.8 ± 1.1 mmol/l in Rhyper. The frequency of Rhyper was significantly (P < .001) correlated with Rhypo (Spearman's rho 0.84), glucose coefficient of variation (0.78), and time below range (0.69) but not with time above range (0.12, P = .13).

CONCLUSIONS

The strong correlation between Rhyper and Rhypo suggests an individual behavioral characteristic toward intensive correction of glucose excursions.

Glycaemic control in people with diabetes following acute myocardial infarction

Diabetes is a highly prevalent disease associated with considerable cardiovascular end organ damage and mortality. Despite significant changes to the management of acute myocardial infarction over the last two decades, people with diabetes remain at risk of complications and mortality following a myocardial infarct for a multitude of reasons, including increased coronary atherosclerosis, associated coronary microvascular dysfunction, and diabetic cardiomyopathy. Dysglycaemia causes significant endothelial dysfunction and upregulation of inflammation within the vasculature and epigenetic changes mean that these deleterious effects may persist despite subsequent efforts to tighten glycaemic control. Whilst clinical guidelines advocate for the avoidance of both hyper- and hypoglcyaemia in the peri-infarct period, the evidence base is lacking, and currently there is no consensus on the benefits of glycaemic control beyond this period. Glycaemic variability contributes to the glycaemic milieu and may have prognostic importance following myocardial infarct. The use of continuous glucose monitoring means that glucose trends and parameters can now be captured and interrogated, and its use, along with newer medicines, may provide novel opportunities for intervention after myocardial infarction in people with diabetes.

G6 continuous glucose monitoring system feature use and its associations with glycaemia in Europe

AIMS

Current continuous glucose monitoring (CGM) devices provide features that alert individuals with diabetes about their current and impending adverse glycaemic events. The use of these features has been associated with glycaemic improvements. However, how these features are utilised under real-world conditions has not been well studied. We queried a large database to quantify utilisation of the Dexcom G6 system features and how utilisation impacted glycaemic outcomes within a cohort of European users.

METHODS

This 6-month retrospective, observational, large database analysis utilised anonymised data from a sample of 47,784 Europe-based G6 users. Primary outcome measures were associations between utilisation and customisation of High/Low threshold alerts, 'urgent low soon' (ULS) alert, and established CGM metrics.

RESULTS

Users in the Germany, Austria, Switzerland region (n = 20,257), the Nordic countries (n = 10,314), United Kingdom (n = 9006), Italy (n = 4747), France (n = 2130) and Spain (1330) were included. All alert features were utilised by >75% of the cohort across all regions/countries and age groups. Enabling the Low alert and ULS alert was associated with lower percentage of time below range compared to disabling the Low alert (p < 0.001). Enabling the High alert was associated with higher percentage of time in range (%TIR) and lower percentage of time above range (%TAR) %TAR compared to disabling the High alert (p < 0.001). Paediatric patients and older adults tended to set a higher threshold for High/Low alerts, while younger adults tended to use lower threshold values for High/Low alerts.

CONCLUSIONS

Individuals who utilised the Dexcom G6 features showed better glycaemic control, particularly among those who utilised more sensitive High alert and Low alert settings, than users who did not utilise the system features.

Sustained heart rate-corrected QT prolongation during recovery from hypoglycaemia in people with type 1 diabetes, independently of recovery to hyperglycaemia or euglycaemia

AIM

To investigate changes in cardiac repolarization abnormalities (heart rate-corrected QT [QT_c ] [primary endpoint], T-wave abnormalities) and heart-rate variability measures in people with type 1 diabetes during insulin-induced hypoglycaemia followed by recovery hyperglycaemia versus euglycaemia.

METHODS

In a randomized crossover study, 24 individuals with type 1 diabetes underwent two experimental clamps with three steady-state phases during electrocardiographic monitoring: (1) a 45-minute euglycaemic phase (5-8 mmol/L), (2) a 60-minute insulin-induced hypoglycaemic phase (2.5 mmol/L), and (3) 60-minute recovery in either hyperglycaemia (20 mmol/L) or euglycaemia (5-8 mmol/L).

RESULTS

All measured markers of arrhythmic risk indicated increased risk during hypoglycaemia. These findings were accompanied by a decrease in vagal tone during both hyperglycaemia and euglycaemia clamps. Compared with baseline, the QT_c interval increased during hypoglycaemia, and 63% of the participants exhibited a peak QT_c of more than 500 ms. The prolonged QT_c interval was sustained during both recovery phases with no difference between recovery hyperglycaemia versus euglycaemia. During recovery, no change from baseline was observed in heart-rate variability measures.

CONCLUSIONS

In people with type 1 diabetes, insulin-induced hypoglycaemia prolongs cardiac repolarization, which is sustained during a 60-minute recovery period independently of recovery to hyperglycaemia or euglycaemia. Thus, vulnerability to serious cardiac arrhythmias and sudden cardiac death may extend beyond a hypoglycaemic event, regardless of hyperglycaemic or euglycaemic recovery.

Expertenaustausch zum Einsatz von kontinuierlichem Glukosemonitoring (CGM) im Diabetesmanagement: Eine aktuelle Bestandsaufnahme und Blick in die Zukunft

CGM mit Darstellung der aktuellen Glukosewerte (rtCGM) ist aktuell einer der wichtigsten diagnostischen Optionen in der Diabetologie. Es ermöglicht eine umfangreiche und unmittelbare Unterstützung und Erleichterung des Diabetesmanagements, besonders wenn eine Insulintherapie angewendet wird. Weiterhin stellt rtCGM den notwendigen Systempartner für die Steuerung der automatisierten Insulinabgabe in AID-Systemen dar. In Verbindung mit Smart-Pens unterstützt ein rtCGM die korrekte Durchführung des Insulinmanagements und erinnert an Bolusinjektionen.

RtCGM-Daten sind heute das Fundament des personalisierten Datenmanagements und Alltagscoachings und stellen die Basis der Digitalisierung und telemedizinischen Intervention dar. Die Möglichkeit der interoperablen Nutzung ist aus therapeutischer Sicht eine zentrale Eigenschaft eines rtCGMs und kann zur Erweiterung der Indikationen, unabhängig von Diabetestyp oder Therapieform führen. Dies könnte auch den vorübergehenden oder intermittierenden Einsatz bei Menschen mit Typ-2-Diabetes ohne Insulinbehandlung betreffen. Kürzlich veröffentlichte internationale Leitlinien, z.B. der Amerikanischen Gesellschaft für klinische Endokrinologie (AACE) fordern auf der Basis umfangreicher Evidenz, dass die Glukosemessung mit einem rtCGM für alle Menschen mit Diabetes nutzbar und verfügbar sein sollte. Bereits in der Phase gestörter Glukosetoleranz kann ein rtCGM-System als Alltagscoaching oder Biofeedback bei Einbettung in ein Gesamtbehandlungskonzept unterstützen, mit dem Ziel aktiver und fundierter Handlungen des Anwenders im Diabetesalltag.

Die Vielfalt der Nutzungsoptionen und die immer schnelleren technischen Innovationszyklen von rtCGM-Systemen wurden mit Blick auf aktuelle Anforderungen und die notwendigen Strukturanpassungen des Gesundheitssystems von einer rtCGM-erfahrenen Expertengruppe diskutiert. Ziel war es, konkrete Lücken in der Versorgungsstruktur sowie potenzielle Handlungsfelder in der Diabetologie zu identifizierten und mögliche Indikationserweiterungen für den Einsatz von rtCGM darzustellen. Dieses, sowie die Erkenntnisse und Schlussfolgerungen der Diskussionen werden in diesem Artikel dargestellt.

Characterization of Post-Hypoglycemic Hyperglycemia in Children and Adolescents With Type 1 Diabetes: The EPHICA Study

BACKGROUND

In patients with diabetes, the dynamics in which hypoglycemia recovers impacts cardiovascular disease risk. Our study investigated the extents of "post-hypoglycemic hyperglycemia (PHH)" (i.e. hypoglycemia that recover to hyperglycemia in any circumstance) and factors likely to influence PHH characteristics in a pediatric cohort of patients with type 1 diabetes (T1D).

METHODS

We collected retrospective continuous glucose monitoring (CGM) data from 142 pediatric patients with T1D to characterize episodes of PHH during a two-month follow-up period. Factors influencing PHH were determined using univariate and multivariate analyses.

RESULTS

In our EPHICA cohort, PHH rate was 0.6 ± 0.3 episode/day and correlated (r=0.33; p<0.0001) with hyperglycemia rate (2.6 ± 0.5 episodes/day). The global proportion of hyperglycemia corresponding to PHH was 0.22 ± 0.1, yet 14.8% of patients had more than 1/3 of hyperglycemia related to PHH. Episodes of PHH lasted 239.6 ± 124.8 minutes with a hyperglycemic peak of 258.8 ± 47.1 mg/dL. Only 12.2% of PHH occurred at night. While a younger age (<12 years) and lower body mass index (BMI) (SDS: -2 to 1.6) were associated with higher daily PHH rates, teenagers (≥12 years) and obese patients experienced longer PHH and higher hyperglycemic peaks. Parameters of glycemic variability (i.e. HbA_1C, IDAA_1C and GTAA_1C) moderately correlated with PHH duration and related hyperglycemic peak. Multivariate analysis confirmed these results, as factors likely to influence PHH rate were phenotype (age and BMI) and glycemic variability parameters (time in range, mean glycemia, HbA_1C and GTAA_1C).

CONCLUSION

Our EPHICA study highlights the importance of PHH as a prominent component of hyperglycemia in some children and adolescents with T1D. Factors associated with PHH features are age, BMI and parameters of glycemic control. Young and lean children are more prone to experience hypoglycemia that recover with hyperglycemia, but adolescents and obese children tend to experience hyperglycemia of longer duration.

Integrating Continuous Glucose Monitoring Into Clinical Practices and Patients' Lives

Numerous studies have demonstrated the clinical benefits of continuous glucose monitoring (CGM) in individuals with diabetes. Within ongoing innovations in CGM technology, individuals now have an expanding array of options that allow them to select the device that meets their individual needs and preferences. Although demand for CGM in primary care continues to grow, many clinicians are reluctant to prescribe this technology due to their unfamiliarity with the various devices, uncertainty about which devices are best suited to each patient and the feasibility of using CGM. This article reviews the features and functionality of the most recent commercially available CGM devices and provides guidance for integrating CGM use into clinical practices.

Sustainable Use of a Real-Time Continuous Glucose Monitoring System from 2018 to 2020

We aimed to describe patterns of continuous glucose monitoring (CGM) system use and glycemic outcomes from 2018 to 2020 in a large real-world cohort by analyzing anonymized data from US-based CGM users who transitioned from the G5 to the G6 System (Dexcom) in 2018. The main end points were persistent use, within-day and between-day utilization, hypoglycemia, time in range (TIR, 70-180 mg/dL [3.9-10 mmol/L]), and use of the optional calibration feature in 2019 and 2020. In a cohort of 31,034 individuals, rates of persistent use were high, with 27,932 (90.0%) and 26,861 (86.6%) continuing to upload data in 2019 and 2020, respectively. Compared with G5 use, G6 use was associated with higher device utilization, less hypoglycemia, higher TIR (in 2020), and >80% fewer calibrations in both 2019 and 2020 (P's < 0.001). High persistence and utilization of the G6 system may contribute to sustainable glycemic outcomes and decreased user burden.

Real-World Evidence and Glycemic Improvement Using Dexcom G6 Features

Background: Optional features of continuous glucose monitoring (CGM) systems empower patients and caregivers to understand and manage diabetes in new ways. We examined associations between use of optional features, demographics, and glycemic outcomes. Methods: Retrospective cohort studies were performed with data from US-based users of the G6 CGM System (Dexcom, Inc.). For all cohorts, data included sensor glucose values (SGVs). In separate cohorts, use of alert features (for hyperglycemia, existing hypoglycemia, and impending hypoglycemia), remote data sharing feature (Share), software for retrospective pattern analysis (CLARITY), "virtual assistant" feature that announces the current SGV and trend in response to a spoken request were assessed. Descriptive statistics were used to summarize feature set utilization patterns and relate them to glycemic outcomes. Results: Most individual features were consistently adopted by high proportions of G6 users. Threshold SGVs chosen for activating hyperglycemia and hypoglycemia alerts varied with age and were higher among the youngest and oldest patients. Use of the Share feature was more common among young patients and those with type 1 diabetes. Individuals who used more of the alert and notification features had more favorable glycemic outcomes, including time in range (TIR), than those who used fewer. More extensive engagement with CLARITY notifications was associated with higher TIR. Frequent use of the virtual assistant feature was associated with higher TIR and lower mean SGV. Conclusions: Optional features of the G6 CGM system are acceptable to and appear to benefit patients who use them. Different levels of engagement suggest that demographics and personal circumstances play a role in how patients and caregivers use CGM features to help manage diabetes.