Explore the vast range of titles available.

Introduction The advanced hybrid closed loop (AHCL) MiniMed™ 780G system changes basal insulin delivery every 5 min and auto bolus in response to sensor glucose values. We assessed the performance of the AHCL system in real-world settings for individuals with type 1 diabetes (T1DM) as well as user and clinician perspectives and satisfaction. Methods We held two peer group discussions: one having adults with T1DM/parents of children and adolescents with T1DM to understand their experiences with the AHCL system and another with healthcare providers (HCPs). Responses from the discussions were analyzed and categorized into themes by two independent researchers, with any inconsistencies resolved by consensus. We also analyzed data from the system uploaded to CareLink personal software. Glycemic outcomes, including time in range (TIR), time below range (TBR), time above range (TAR), mean sensor glucose (SG) levels, glucose management indicator (GMI), sensor use, and percentage of time spent in AHCL, were determined. Results The peer group discussions revealed numerous key themes and issues for each group, such as the significance of setting reasonable expectations, carbohydrate counting and bolus dosing, technical difficulties, and overall user experience. The users ( n  = 25; T1DM; 17 female; age 13.8 ± 7.49 years; A1C 6.54 ± 0.45%; duration of diabetes 6 ± 6.78 years) were very satisfied with the system. Most users experienced consistent blood glucose values with very few hypoglycemic episodes. However, there were a few limitations reported, such as hyperglycemic episodes caused by inaccuracies in carb counting, issues with sensor connectivity, and cannula blockages or kinking for those using insulin Fiasp. Users achieved a mean GMI of 6.4 ± 0.26%, TIR of 83.0 ± 8.12%, TBR (54–70 mg/dL) of 2.0 ± 0.81%, TBR* (< 54 mg/dL) of 0%. All of the users achieved a TIR of > 70%. Conclusion The use of the AHCL system in T1DM resulted in robust glycemic control, minimizing hypoglycemia. Providing training to both users and HCPs can help them use the system effectively.

Recent upswings in the use of continuous glucose monitoring (CGM) technologies have given people with diabetes and healthcare professionals unprecedented access to a range of new indicators of glucose control. Some of these metrics are useful research tools and others have been welcomed by patient groups for providing insights into the quality of glucose control not captured by conventional laboratory testing. Among the latter, time in range (TIR) is an intuitive metric that denotes the proportion of time that a person’s glucose level is within a desired target range (usually 3.9–10.0 mmol/l [3.5–7.8 mmol/l in pregnancy]). For individuals choosing to use CGM technology, TIR is now often part of the expected conversation between patient and healthcare professional, and consensus recommendations have recently been produced to facilitate the adoption of standardised TIR targets. At a regulatory level, emerging evidence linking TIR to risk of complications may see TIR being more widely accepted as a valid endpoint in future clinical trials. However, given the skewed distribution of possible glucose values outside of the target range, TIR (on its own) is a poor indicator of the frequency or severity of hypoglycaemia. Here, the state-of-the-art linking TIR with complications risk in diabetes and the inverse association between TIR and HbA1c are reviewed. Moreover, the importance of including the amount and severity of time below range (TBR) in any discussions around TIR and, by inference, time above range (TAR) is discussed. This review also summarises recent guidance in setting ‘time in ranges’ goals for individuals with diabetes who wish to make use of these metrics. For most people with type 1 or type 2 diabetes, a TIR >70%, a TBR <3.9 mmol/l of <4%, and a TBR <3.0 mmol/l of <1% are recommended targets, with less stringent targets for older or high-risk individuals and for those under 25 years of age. As always though, glycaemic targets should be individualised and rarely is that more applicable than in the personal use of CGM and the data it provides.

Background Highly variable insulin sensitivity, susceptibility to hypoglycemia and inability to effectively communicate hypoglycemic symptoms pose significant challenges for young children with type 1 diabetes (T1D). Herein, outcomes during clinical MiniMed™ 670G system use were evaluated in children aged 2–6 years with T1D. Methods Participants (N = 46, aged 4.6 ± 1.4 years) at seven investigational centers used the MiniMed™ 670G system in Manual Mode during a two‐week run‐in period followed by Auto Mode during a three‐month study phase. Safety events, mean A1C, sensor glucose (SG), and percentage of time spent in (TIR, 70–180 mg/dl), below (TBR, <70 mg/dl) and above (TAR, >180 mg/dl) range were assessed for the run‐in and study phase and compared using a paired t‐test or Wilcoxon signed‐rank test. Results From run‐in to end of study (median 87.1% time in auto mode), mean A1C and SG changed from 8.0 ± 0.9% to 7.5 ± 0.6% (p < 0.001) and from 173 ± 24 to 161 ± 16 mg/dl (p < 0.001), respectively. Overall TIR increased from 55.7 ± 13.4% to 63.8 ± 9.4% (p < 0.001), while TBR and TAR decreased from 3.3 ± 2.5% to 3.2 ± 1.6% (p = 0.996) and 41.0 ± 14.7% to 33.0 ± 9.9% (p < 0.001), respectively. Overnight TBR remained unchanged and TAR was further improved 12:00 am–6:00 am. Throughout the study phase, there were no episodes of severe hypoglycemia or diabetic ketoacidosis (DKA) and no serious adverse device‐related events. Conclusions At‐home MiniMed™ 670G Auto Mode use by young children safely improved glycemic outcomes compared to two‐week open‐loop Manual Mode use. The improvements are similar to those observed in older children, adolescents and adults with T1D using the same system for the same duration of time.

Background Continuous glucose monitoring (CGM)-derived time in range (TIR) is closely associated with micro- and macrovascular complications in type 2 diabetes mellitus (T2DM). This study was performed to investigate the relationship between key CGM-derived metrics and specific cognitive domains in patients with T2DM. Methods Outpatients with T2DM who were otherwise healthy were recruited for this study. A battery of neuropsychological tests was performed to evaluate cognitive function, including memory, executive functioning, visuospatial ability, attention, and language. Participants wore a blinded flash continuous glucose monitoring (FGM) system for 72 h. The key FGM-derived metrics were calculated, including TIR, time below range (TBR), time above range (TAR), glucose coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE). Furthermore, the glycemia risk index (GRI) was also calculated by the GRI formula. Binary logistic regression was used to assess risk factors for TBR, and we further analysed the associations between neuropsychological test results and key FGM-derived metrics with multiple linear regressions. Results A total of 96 outpatients with T2DM were recruited for this study, with 45.8% experiencing hypoglycemia (TBR < 3.9 mmol/L ). Spearman analysis results revealed that a higher TBR < 3.9 mmol/L was correlated with worse performance on the Trail Making Test A (TMTA), Clock Drawing Test (CDT), and cued recall scores ( P  < 0.05). Logistic regression analysis results indicated that the TMTA (OR = 1.010, P  = 0.036) and CDT (OR = 0.429, P  = 0.016) scores were significant factors influencing the occurrence of TBR < 3.9 mmol/L . Multiple linear regressions further demonstrated that TBR < 3.9 mmol/L (β = -0.214, P  = 0.033), TAR > 13.9 mmol/L (β = -0.216, P  = 0.030) and TAR 10.1–13.9 mmol/L (β = 0.206, P  = 0.042) were significantly correlated with cued recall scores after adjusting for confounding factors. However, TIR, GRI, CV and MAGE showed no significant correlation with the results of neuropsychological tests ( P  > 0.05). Conclusions A higher TBR < 3.9 mmol/L and TAR > 13.9 mmol/L were associated with worse cognitive functions (memory, visuospatial ability, and executive functioning). Conversely, a higher TAR of 10.1–13.9 mmol/L was associated with better memory performance in memory tasks.

Background and aims To investigate the association between the frequency of intermittent-scanning continuous glucose monitoring (isCGM) and diurnal variation of time in range (TIR), time above range (TAR), and time below range (TBR), we performed a post hoc analysis of the ISCHIA study, a multicenter, prospective, open-label, randomized crossover study of patients with type 1 diabetes mellitus. Method Data of 93 people who completed the ISCHIA study were used. We calculated scan frequency, TAR, TIR, and TBR of four approximately 6-h intervals: 6:00–11:59 (morning), 12:00–17:59 (afternoon), 18:00–23:59 (evening), and 0:00–5:59 (night). The correlation between scan frequency and diurnal variation of CGM metrics was analyzed using nonparametric Spearman correlation analysis. Results More frequent scanning was associated with higher TIR in the afternoon (rho = 0.343, P < 0.001), evening (rho = 0.243, P = 0.019), and night (rho = 0.218, P = 0.036); furthermore, it was associated with lower TAR in the afternoon (rho = -0.275, P = 0.008) and TBR in the evening (rho = -0.235, P = 0.024). Concern about the effect of blood glucose fluctuation on social communication affected the number of scans during the day. Concerns about loneliness and hypoglycemia when alone also influenced the number of nighttime scans. Conclusion Scan frequency is influenced by psychological factors. Afternoon scans were associated with the highest increase in TIR and decrease in TAR. Evening scans were linked to a reduction in TBR.

Introduction: Time in range (TIR), a metric of continuous glucose monitoring (CGM) provides better information regarding the individual's glycemic variability than a static measure like glycated hemoglobin (HbA1c). TIR is emerging as an independent risk factor for diabetic complications, both microvascular and macrovascular complications independent of HbA1c. Hence, this study evaluates the association between TIR and cardiac autonomic neuropathy (CAN) in type 2 diabetic patients. Materials and Methods: A total of 42 patients with type 2 diabetes mellitus were enrolled in this study and underwent a 3-day CGM using the \"FreeStyle Libre Pro Flash Glucose Monitoring System Sensor\" along with tests for CAN within the 3 days of attaching the CGM. Results: Out of 42 patients, 36 patients (85.7%) were diagnosed with CAN (early CAN 57.1% and definite CAN 28.6%) and the mean TIR was 64.4% ±23.5%. Out of those with TIR <70%, 42.9% were affected with definite CAN compared to only 14.3% among those with TIR >70%. Patients with more severe CAN were found to have a lower TIR (P = 0.115). Conclusion: The study found a high prevalence of cardiac autonomic neuropathy (CAN) of around 85.7% in type 2 diabetes patients. Lower TIR values were associated with a higher incidence of definite CAN (42.9% vs. 14.3% in TIR <70% vs. >70% groups). The findings suggest TIR is inversely associated with the presence and severity of cardiac autonomic neuropathy in type 2 diabetic patients and also a potential link between TIR and CAN severity.

Aims/hypothesis The aim of this study was to evaluate the association of chronic complications with time in tight range (TITR: 3.9–7.8 mmol/l) and time in range (TIR: 3.9–10.0 mmol/l) in people with type 1 diabetes. Methods The prevalence of microvascular complications (diabetic retinopathy, diabetic nephropathy and diabetic peripheral neuropathy [DPN]) and macrovascular complications according to sensor-measured TITR/TIR was analysed cross-sectionally in 808 adults with type 1 diabetes. Binary logistic regression was used to evaluate the association between TITR/TIR and the presence of complications without adjustment, with adjustment for HbA 1c , and with adjustment for HbA 1c and other confounding factors (sex, age, diabetes duration, BMI, BP, lipid profile, smoking, and use of statins and renin–angiotensin–aldosterone system inhibitors). Results The mean TITR and TIR were 33.9 ± 12.8% and 52.5 ± 15.0%, respectively. Overall, 46.0% had any microvascular complication (34.5% diabetic retinopathy, 23.8% diabetic nephropathy, 16.0% DPN) and 16.3% suffered from any macrovascular complication. The prevalence of any microvascular complication, diabetic retinopathy, diabetic nephropathy and a cerebrovascular accident (CVA) decreased with increasing TITR/TIR quartiles (all p trend <0.05). Each 10% increase in TITR was associated with a lower incidence of any microvascular complication (OR 0.762; 95% CI 0.679, 0.855; p <0.001), diabetic retinopathy (OR 0.757; 95% CI 0.670, 0.856; p <0.001), background diabetic retinopathy (OR 0.760; 95% CI 0.655, 0.882; p <0.001), severe diabetic retinopathy (OR 0.854; 95% CI 0.731, 0.998; p =0.048), diabetic nephropathy (OR 0.799; 95% CI 0.699, 0.915; p <0.001), DPN (OR 0.837; 95% CI 0.717, 0.977; p =0.026) and CVA (OR 0.651; 95% CI 0.470, 0.902; p =0.010). The independent association of TITR with any microvascular complication (OR 0.867; 95% CI 0.762, 0.988; p =0.032), diabetic retinopathy (OR 0.837; 95% CI 0.731, 0.959; p =0.010), background diabetic retinopathy (OR 0.831; 95% CI 0.705, 0.979; p =0.027) and CVA (OR 0.619; 95% CI 0.426, 0.899; p =0.012) persisted after adjustment for HbA 1c . Similar results were obtained when controlling for HbA 1c and other confounding factors. Conclusions/interpretation TITR and TIR are inversely associated with the presence of microvascular complications and CVA in people with type 1 diabetes. Although this study was not designed to establish a causal relationship, this analysis adds validity to the use of TITR and TIR as key measures in glycaemic management. Trial registration ClinicalTrials.gov NCT02601729 and NCT02898714 Graphical Abstract

Chi Xu,1,2 Wu Dai,1 Yan Liu,1 Rong Zhang,1 Erlan Shi,1 Xiangxiang Shan,1 Yonghong Cao1,2 1Department of Endocrinology, Hefei Hospital Affiliated to Anhui Medical University (Hefei Second People’s Hospital), Hefei, 230011, People’s Republic of China; 2The Fifth Clinical Medical College, Anhui Medical University, Hefei, 230032, People’s Republic of ChinaCorrespondence: Yonghong Cao, Department of Endocrinology, Hefei Hospital Affiliated to Anhui Medical University (Hefei Second People’s Hospital), Hefei, 230011, People’s Republic of China, Email fish1982cao@126.comAim: Our study aimed to investigate the association between time in range (TIR) and diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM) patients with hypoglycemia unawareness.Methods: This is a retrospective cross-sectional study. In our study, 298 T2DM patients with hypoglycemia unawareness were recruited from the Department of Endocrinology, Hefei Second People’s Hospital from 01/09/2020 to 30/06/2023. Patients were divided into DR group (97 cases) and non-DR group (NDR, 201 cases). We compared the clinical data and blood glucose fluctuation indexes of the two groups. Meanwhile, we also observed these indicators, especially the prevalence of DR and the time below range (TBR) in groups with different TIR levels (Q1 group: TIR≤ 70%, 79 cases; Q2 group: 70%

Background: The aim of this study was to assess and compare the time in range (TIR) of children with type 1 diabetes (T1D) before and during a diabetes summer camp using different therapy modalities. Methods: A retrospective analysis of continuous glucose monitoring (CGM) data collected from 26 children with T1D (mean age: 11.0 ± 1.4 years; 62% female; 62% on insulin pump; Hb1Ac 7.3 ± 0.8% (56.3 ± 8.7 mmol/mol) before and during a 14-day summer camp. CGM methods: 50% intermittently scanned CGM (isCGM) and 50% real-time CGM (rtCGM). No child was using a hybrid closed loop system. Results: Mean TIR during camp was significantly higher than before camp ((67.0 ± 10.7%) vs. 58.2% ± 17.4%, p = 0.004). There was a significant reduction in time above range (TAR) (p = 0.001) and increase in time below range (TBR) (p < 0.001), Children using isCGM showed a more pronounced improvement in TIR during camp compared to rtCGM-users (p = 0.025). The increase in TIR strongly correlated with numbers of scans per day in isCGM-users (r = 0.751, p = 0.003). Compared to isCGM-users, rtCGM-users showed significantly less TBR. The TIR target was met by 30.8% of participants during camp. Conclusion: Glycemic control improved significantly during the camp. However, on average, the therapy goal (TIR > 70%) could not be achieved despite great professional effort.

Background The hypothalamic-pituitary-adrenal axis is thought to play a vital role in glucose homeostasis and diabetes. This study investigated the association between morning serum cortisol and time in range (TIR), including daytime TIR, in type 2 diabetes (T2DM). Methods 310 patients with T2DM had serum cortisol measured at 8 a.m. All participants underwent continuous glucose monitoring (CGM) for three consecutive days, then TIR and glycemic variability (GV) parameters were evaluated. Using 100 g standard steamed bread meal test, blood glucose, C peptide and insulin at different points were collected to assess insulin sensitivity and islet function. Results Patients with higher serum cortisol exhibited lower TIR and TITR ( P  < 0.001). Spearman correlation analysis showed that the negative correlation between cortisol and daytime TIR ( r =-0.231, P  < 0.001) was stronger than that of overnight TIR ( r =-0.134, P  = 0.028). Similarly, there existed a negative correlation between cortisol and pancreatic function indicators such as HOMA-β, insulinogenic index (IGI), area under the curve of C-peptide within half an hour (AUCCp0.5 h) and three hours (AUCCp3h) ( r =-0.248, -0.176, -0.140, -0.185, respectively, P  < 0.05). In contrast, cortisol was positively associated with TAR ( r  = 0.217, P  < 0.001) and GV parameters including MBG, MAGE, LAGE, HBGI, MODD, ADDR (P of MAGE and MODD > 0.05). Multiple stepwise regression revealed that cortisol was an independent contributor of TIR, TITR and diurnal TIR, with diurnal TIR of stronger relevance. Conclusions Morning serum cortisol is negatively correlated with TIR, especially diurnal TIR and positively associated with GV parameters. Inappropriate cortisol secretion may have an adverse influence on glucose homeostasis in T2DM.