Basal-IQ technology in the real world: satisfaction and reduction of diabetes burden in individuals with type 1 diabetes

Association between sleep variability and time in range of glucose levels in patients with type 1 diabetes: Cross-sectional study

OBJECTIVE

Sleep and circadian disturbances emerge as novel factors influencing glycemic control in type 1 diabetes (T1D). We aimed to explore the associations among sleep, behavioral circadian parameters, self-care, and glycemic parameters in T1D.

METHODS

Seventy-six non-shift-working adult T1D patients participated. Blinded 7-day continuous glucose monitoring (CGM) and hemoglobin A1C (A1C) were collected. Percentages of time-in-range (glucose levels 70-180 mg/dL) and glycemic variability (measured by the coefficient of variation [%CV]) were calculated from CGM. Sleep (duration and efficiency) was recorded using 7-day actigraphy. Variability (standard deviation) of midsleep time was used to represent sleep variability. Nonparametric behavioral circadian variables were derived from actigraphy activity recordings. Self-care was measured by diabetes self-management questionnaire-revised. Multiple regression analyses were performed to identify independent predictors of glycemic parameters.

RESULTS

Median (interquartile range) age was 34.0 (27.2, 43.1) years, 48 (63.2%) were female, and median (interquartile range) A1C was 6.8% (6.2, 7.4). Sleep duration, efficiency, and nonparametric behavioral circadian variables were not associated with glycemic parameters. After adjusting for age, sex, insulin delivery mode/CGM use, and ethnicity, each hour increase in sleep variability was associated with 9.64% less time-in-range (B = -9.64, 95% confidence interval [-16.29, -2.99], p ≤ .001). A higher diabetes self-management questionnaire score was an independent predictor of lower A1C (B = -0.18, 95% confidence interval [-0.32, -0.04]).

CONCLUSION

Greater sleep timing variability is independently associated with less time spent in the desirable glucose range in this T1D cohort. Reducing sleep timing variability could potentially lead to improved metabolic control and should be explored in future research.

DATA AVAILABILITY STATEMENT

Data are available upon a reasonable request to the corresponding author.

Satisfaction with continuous glucose monitoring is positively correlated with time in range in children with type 1 diabetes

AIMS

Continuous glucose monitoring (CGM) can improve glucometrics in children with type 1 diabetes (T1D), and its efficacy is positively related to glucose sensor use for at least 60% of the time. We therefore investigated the relationship between CGM satisfaction as assessed by a robust questionnaire and glucose control in pediatric T1D patients.

METHODS

This was a cross-sectional study of children and adolescents with T1D using CGM. The CGM Satisfaction (CGM-SAT) questionnaire was administered to patients and demographic, clinical, and glucometrics data were recorded.

RESULTS

Two hundred and ten consecutively enrolled patients attending 14 Italian pediatric diabetes clinics completed the CGM-SAT questionnaire. CGM-SAT scores were not associated with age, gender, annual HbA1c, % of time with an active sensor, time above range (TAR), time below range (TBR), and coefficient of variation (CV). However, CGM satisfaction was positively correlated with time in range (TIR, p < 0.05) and negatively correlated with glycemia risk index (GRI, p < 0.05).

CONCLUSIONS

CGM seems to have a positive effect on glucose control in patients with T1D. CGM satisfaction is therefore an important patient-reported outcome to assess and it is associated with increased TIR and reduced GRI.

The Tandem Control-IQ advanced hybrid system improves glycemic control in children under 18 years of age with type 1 diabetes and night rest in caregivers

OBJECTIVE

To determine the impact of switching from the predictive low glucose suspend (PLGS) system to the advanced hybrid Tandem Control-IQ system on glucometrics and glycosylated haemoglobin (HbA1c) at one year. To assess the impact on the quality of life perceived by parents.

METHOD

Prospective study in 71 patients aged 6-18 years with type 1 diabetes (DM1), in treatment with PLGS, who switched to an advanced hybrid system. Glucometric data were collected before the change, at 4 and 8 weeks, and at one year of use; HbA1c before the change and after one year. The Diabetes Impact and Devices Satisfaction (DIDS) questionnaire was used at weeks 4 and 8.

RESULTS

An increase in time in range (TIR) was observed with a median of 76% (P<.001) at 4 weeks, which was maintained after one year (+8% in the total group). Overall, 73.24% of patients achieved a TIR above 70%. The subgroup with an initial TIR of less than 56% increased it by 14.4%. After one year there was a 0.3% reduction in HbA1c. Level 1 hypoglycaemia, level 1 and level 2 hyperglycaemia, mean glucose (GM) and coefficient of variation (CV) decreased. Auto mode stayed on 97% of the time and no dropouts occurred. Caregivers had a perception of better glycaemic control and less need to monitor blood glucose variations during the night. None of them would switch back to the previous system and they feel safe with the new system.

CONCLUSIONS

The Tandem Control-IQ advanced hybrid system was shown to be effective one year after its implementation with improvement in all glucometric parameters and HbA1c, as well as night-time rest in caregivers.

Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases

Over the past decade there have been many advances in diabetes technologies, such as continuous glucose monitors (CGM s), insulin-delivery devices, and hybrid closed loop systems . Now most CGMs (Medtronic-Guardian, Dexcom-G6, and Abbott-Libre-2) have MARD values of < 10%, in contrast to two decades ago when the MARD used to be > 20%. In addition, the majority of the new CGMs do not require calibrations, and the latest CGMs last for 10-14 days. An implantable 6-months CGM by Eversense-3 is now approved in the USA and Europe. Recently, the FDA approved Libre 3 which provides real-time glucose values every minute. Even though it is approved as an iCGM it is not interoperable with automatic-insulin-delivery (AID) systems. The newer CGMs that are likely to be launched in the next few months in the USA include the 10-11 days Dexcom G7 (60% smaller than the existing G6), and the 7-days Medtronic Guardian 4. Most of the newer CGM have several features like automatic initialization, easy insertion, predictive alarms, and alerts. It has also been noticed that an arm insertion site might have better accuracy than abdomen or other sites, like the buttock for kids. Lag time between YSI and different sensors have been reported differently, sometimes it is down to 2-3 min; however, in many instances, it is still 15-20 min, especially when the rate of change of glucose is > 2 mg/min. We believe that in the next decade there will be a significant increase in the number of people who use CGM for their day-to-day diabetes care.

Erste Anwendungserfahrung eines neuen, Glukosesensor-unterstützten Pumpensystems mit vorausschauender Insulin-Abschaltung zum Hypoglykämieschutz bei pädiatrischen Patienten in Deutschland

Einleitung Die prädiktive Insulinabschaltung ist als System zur Prävention von Hypoglykämien in Deutschland etabliert (Smartguard). Seit 2020 ist in Deutschland ein zweites System verfügbar (Basal-IQ). Unterschiede betreffen eine nicht veränderbare prädiktive Abschaltgrenze von 80 mg/dl (vs. 50–90 mg/dl), eine Abschaltzeit von minimal 5 Minuten (vs. 30 Minuten) sowie die Festlegung der Wiedereinschaltung des Insulin bei einem höheren Wert als zuvor (vs. einem Abstand von 20 mg/dl über der Abschaltgrenze und höherer Prädiktion). Die Systeme wurden in einer Altersgruppe, die besonders von Unterzuckerungen bedroht ist, verglichen.

Methodik Pädiatrische Patienten (Alter 6–13 Jahre), mit Pumpen- und Sensorerfahrung (kein AID) wurde die Erprobung von Basal-IQ für eine Dauer von 3 Monaten angeboten. Betrachtet wurden die CGM-Parameter Zeit unter Zielbereich (TBR < 70mg/dl), im Zielbereich (TIR 70–180 mg/dl), glykämische Variabilität (Varianzkoeffizient CV%) und HbA1c. Patienten-bezogene Outcomes (PROʼs) wurden mit dem Diabskids-Elternfragebogen und einem Gerätefragebogen erfasst.

Ergebnisse Neun Teilnehmer (alle männlich, Mittelwerte: 9.7 Jahre, Diabetesdauer 6.1 Jahre, HbA1c 6.8%, Time in Range (TIR) 61.9%, Time below Range (TBR) 4.5%, mittlere Glukose (MW) 164 mg/dl, (CV) 40) wurden gefunden. Nach 3 Monaten konnten Verbesserungen der glykämischen Parameter beobachtet werden (HbA1c 6.5%, TIR 69.2%, TBR 2.8%, MW 159, CV 40; Kontrollen HbA1c 7.2%, TIR 64.9%, TBR 4.3%, MW 158, CV 39), die sich von einer zeitgleich mit Smartguard behandelten Kindern nicht unterschieden. Die Erfassung der PROʼs zeigte einen Rückgang der Diabetes- und Therapiebelastung, sowie eine Zufriedenheit mit dem System.

Diskussion Das neue System mit prädiktiver Abschaltung zeigte nach 3 Monaten eine Verbesserung der glykämischen Parameter und PROʼs. Ein statistischer Vergleich vorher/nachher ist aufgrund der geringen Patientenzahl nicht erfolgt, aber die Daten zeigen zumindest die Nichtunterlegenheit gegenüber dem Baseline-Zeitpunkt und den Daten, die aus einer Gruppe von Patienten mit kontinuierlicher Systemnutzung stammen. Somit stehen in Deutschland aktuell zwei verschiedene effiziente Systeme mit prädiktiver Insulinabschaltung für Kinder und Jugendliche mit Diabetes zur Verfügung, so dass diese nach fundierter Beratung auswählen können.

Type 1 Diabetes, Sleep, and Hypoglycemia

PURPOSE OF REVIEW

To review the relationship between sleep and hypoglycemia, sleep characteristics, and their associations with glycemic control in persons with type 1 diabetes (T1D). The effects of sleep interventions and diabetes technology on sleep are summarized.

RECENT FINDINGS

Nocturnal hypoglycemia affects objective and subjective sleep quality and is related to behavioral, psychological, and physiological factors. Sleep disturbances are common, including inadequate sleep, impaired sleep efficiency, poor subjective satisfaction, irregular timing, increased daytime sleepiness, and sleep apnea. Some have a bidirectional relationship with glycemic control. Preliminary evidence supports sleep interventions (e.g., sleep extension and sleep coach) in improving sleep and glycemic control, while diabetes technology use could potentially improve sleep. Hypoglycemia and sleep disturbances are common among persons with T1D. There is a need to develop sleep promotion programs and test their effects on sleep, glucose, and related outcomes (e.g., self-care, psychological health).

Newest Diabetes-Related Technologies for Pediatric Type 1 Diabetes and Its Impact on Routine Care: a Narrative Synthesis of the Literature

Purpose of Review

This review aims to address the actual state of the most advanced diabetes devices, as follows: continuous subcutaneous insulin infusions (CSII), continuous glucose monitoring systems (CGM), hybrid-closed loop (HCL) systems, and “Do-it-yourself” Artificial Pancreas Systems (DIYAPS) in children, adolescents, and young adults. This review has also the objective to assess the use of telemedicine for diabetes care across three different areas: education, social media, and daily care.

Recent Findings

Recent advances in diabetes technology after integration of CSII with CGM have increased the popularity of this treatment modality in pediatric age and shifted the standard diabetes management in many countries. We found an impressive transition from the use of CSII and/or CGM only to integrative devices with automated delivery systems. Although much has changed over the past 5 years, including a pandemic period that precipitated a broader use of telemedicine in diabetes care, some advances in technology may still be an additional burden of care for providers, patients, and caregivers. The extent of a higher rate of “auto-mode” use in diabetes devices while using the HCL/DIYAPS is essential to reduce the burden of diabetes treatment.

Summary

More studies including higher-risk populations are needed, and efforts should be taken to ensure proper access to cost-effective advanced technology on diabetes care.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40124-021-00248-7.