Relationship between hemoglobin glycation index and risk of hypoglycemia in type 2 diabetes with time-in-range in target.

BACKGROUND: In patients with type 2 diabetes mellitus (T2DM), the risk of hypoglycemia also occurs in at a time-in-range (TIR) of > 70%. The hemoglobin glycation index (HGI) is considered the best single factor for predicting hypoglycemia, and offers new perspectives for the individualized treatment of patients with well-controlled blood glucose levels that are easily ignored in clinical settings. AIM: To investigate the relationship between HGI and hypoglycemia and the implications of HGI on hypoglycemia in T2DM with TIR > 70%. METHODS: All participants underwent a 7-days continuous glucose monitoring (CGM) using a retrospective CGM system. We obtained glycemic variability indices using the CGM system. We defined HGI as laboratory hemoglobin A1c minus the glucose management indicator. Patients were categorized into low HGI (HGI < 0.5) and high HGI groups (HGI ≥ 0.5) according to HGI median (0.5). Logistic regression and receiver operating characteristic curve analyses were used to determine the risk factors for hypoglycemia. RESULTS: We included 129 subjects with T2DM (54.84 ± 12.56 years, 46% male) in the study. Median TIR score was 90%. The high HGI group exhibited lower TIR and greater time below range with higher hemoglobin A1c than the low HGI group; this suggests more glycemic excursions and an increased incidence of hypoglycemia in the high HGI group. Multivariate analyses revealed that mean blood glucose, standard deviation of blood glucose and HGI were independent risk factors for hypoglycemia. Receiver operating characteristic curve analysis indicated that the HGI was the best predictor of hypoglycemia. In addition, the optimal cut-off points for HGI, mean blood glucose, and standard deviation of blood glucose in predicting hypoglycemia were 0.5%, 7.2 mmol/L and 1.4 mmol/L respectively. CONCLUSION: High HGI was significantly associated with greater glycemic excursions and increased hypoglycemia in patients with TIR > 70%. Our findings indicate that HGI is a reliable predictor of hypoglycemia in this population.

The Role of Whole Food Plant-Based Food Intake on Postprandial Glycemia in Type 1 Diabetes.

BACKGROUND: Whole food plant-based diet (WFPBD), minimally processed foods with limited consumption of animal products, is associated with improved health outcomes. The benefits of WFPBD are underexplored in individuals with type 1 diabetes (T1D). The primary objective of this analysis is to evaluate the association between WFPBD on glycemia in individuals with T1D. RESEARCH DESIGN AND METHODS: Utilizing prospectively collected meal events from the Type 1 Diabetes Exercise Initiative, we examined the effect of WFPBD intake on glycemia, determined by the Plant-Based Diet Index (PDI). The PDI calculates overall, healthful (hPDI), and unhealthy PDI (uPDI) to evaluate for degree of processed foods and animal products (i.e. WFPBD). Mixed effects linear regression model assessed time-in-range (TIR), time-above-range, and time-below-range. RESULTS: We analyzed 7,938 meals from 367 participants. TIR improved with increasing hPDI scores, conferring a 4% improvement in TIR between highest and lowest hPDI scores (high hPDI:75%, low hPDI:71%; p<0.001). Compared to meals with low hPDI, meals with high hPDI had lower glucose excursion (high hPDI:53mg/dL, low hPDI:62mg/dL; p<0.001) and less time >250mg/dL (high hPDI:8%, low hPDI:14%; p<0.001). These effects were present but less pronounced by PDI (high PDI:74%, low PDI:71%; p=0.01). No differences in time below 70mg/dL and 54mg/dL were observed by PDI or hPDI. CONCLUSIONS: Meal events with higher hPDI were associated with 4% postprandial TIR improvement. These benefits were seen primarily in WFPBD meals (captured by hPDI) and less pronounced plant-based meals (captured by PDI), emphasizing the benefit of increasing unprocessed food intake over limiting animal products alone.

Continuous glucose monitoring (Dexcom g6) in people with diabetes after kidney transplantation.

OBJECTIVES: Use of continuous glucose monitoring-CGM in patients on kidney replacement therapy including kidney transplant recipients, may improve glycemic control and detection of hypoglycemia. However, studies in this population in particular in kidney transplant recipients are very limited. METHODS: The study aimed to evaluate glycemic profiles using the Dexcom G6 CGM system for 30 d a personal smartphone in people with diabetes after kidney transplantation and to assess the impact of monthly use of the CGM system on glycemic control and quality of life in this group. RESULTS: Over 8 months, 9 people after kidney transplantation were included in the study (7 women, median age 57 years), 8 people with new-onset diabetes after transplantation (NODAT), and 1 person with diabetes mellitus type 1. The time since kidney transplantation in each of the study participants was less than 2 years. In 7 people with NODAT, the time in range was above 70%. In all study participants, hyperglycemia was observed mainly in the afternoon (2-6 pm). In some patients, pressure-induced sensor attenuations (PISAs) were noted. There was no effect of the use of Dexcom G6 on the HbA1c value. There was no impact of the use of the Dexcom G6 system on the perception of overall quality of life, but monthly use had a positive impact on the perception of the quality of health. CONCLUSIONS: CGM systems seem to be a promising method for assessing glycemic control in people with diabetes after kidney transplantation. More extensive research is needed to assess safety and usefulness in everyday practice.

Impact of Telemedicine Versus In-Person Pediatric Outpatient Type 1 Diabetes Visits on Immediate Glycemic Control: Retrospective Chart Review.

BACKGROUND: Children and adolescents with type 1 diabetes require frequent outpatient evaluation to assess glucose trends, modify insulin doses, and screen for comorbidities. Continuous glucose monitoring (CGM) provides a detailed glycemic control assessment. Telemedicine has been increasingly used since the COVID-19 pandemic. OBJECTIVE: To investigate CGM profile parameter improvement immediately following pediatric outpatient diabetes visits and determine if visit modality impacted these metrics, completion of screening laboratory tests, or diabetic emergency occurrence. METHODS: A dual-center retrospective review of medical records assessed the CGM metrics time in range and glucose management indicator for pediatric outpatient diabetes visits during 2021. Baseline values were compared with those at 2 and 4 weeks post visit. Rates of completion of screening laboratory tests and diabetic emergencies following visits were determined. RESULTS: A total of 269 outpatient visits (41.2% telemedicine) were included. Mean time in range increased by 1.63% and 1.35% at 2 and 4 weeks post visit (P=.003 and .01, respectively). Mean glucose management indicator decreased by 0.07% and 0.06% at 2 and 4 weeks post visit (P=.003 and .02, respectively). These improvements in time in range and glucose management indicator were seen across both telemedicine visits and in-person visits without a significant difference. However, patients seen in person were 2.69 times more likely to complete screening laboratory tests (P=.03). Diabetic emergencies occurred too infrequently to analyze. CONCLUSIONS: Our findings demonstrate an immediate improvement in CGM metrics following outpatient visits, regardless of modality. While statistically significant, the magnitude of these changes was small; hence, multiple visits over time would be required to achieve clinically relevant improvement. However, completion of screening laboratory tests was found to be more likely after visits occurring in person. Therefore, we suggest a hybrid approach that allows patient convenience with telemedicine but also incorporates periodic in-person assessment.

Glucose metrics and device satisfaction in adults with type 1 diabetes using different treatment modalities: a multicenter, real-world observational study.

AIMS: To evaluate glucose metrics, device satisfaction and diabetes impact in adults with type 1 diabetes using different treatment modalities in a real-life setting in Italy. METHODS: This was a multicentre, nationwide, cross-sectional study. Candidates were consecutively evaluated for eligibility during their routine medical visit at the diabetes centre. Researchers collected comprehensive demographic, socioeconomic, anamnestic and clinical data, and administered the Diabetes Impact and Device Satisfaction scale. RESULTS: From 2021 to 2022, a total of 428 subjects, 45% males, with a median age of 32 years (IQR 23-47) were recruited in 11 participating centres from all over Italy. No differences in age, physical activity, and diabetes impact were found for the different treatment modalities. HCL/AHCL and SAP groups reported higher device satisfaction vs. MDI + SMBG and MDI + CGM (p < 0.001). Subjects treated with HCL/AHCL exhibited significantly higher TIR and significantly lower time spent in hypoglycemia level 1, time spent in hyperglycemia, CV and GMI compared to MDI + CGM, and significantly higher TIR and significantly lower time spent in hypoglycemia level 2, time spent in hyperglycemia, and CV compared to SAP. Significant reduction in hypoglycemia level 2 was also found with PLGM compared to SAP. High education attainment was associated with optimal metabolic control. CONCLUSION: Real-life use of advanced technologies for type 1 diabetes is associated with improved glucose metrics and device satisfaction. Education level also contributes to success of treatment.

Association of Continuous Glucose Monitoring-Derived Glycemia Risk Index With Cardiovascular Autonomic Neuropathy in Patients With Type 1 Diabetes Mellitus: A Cross-sectional Study.

BACKGROUND: The glycemia risk index (GRI) is a new composite continuous glucose monitoring (CGM) metric for weighted hypoglycemia and hyperglycemia. We evaluated the association between the GRI and cardiovascular autonomic neuropathy (CAN) and compared the effects of the GRI and conventional CGM metrics on CAN. METHODS: For this cross-sectional study, three-month CGM data were retrospectively analyzed before autonomic function tests were performed in 165 patients with type 1 diabetes. CAN was defined as at least two abnormal results of parasympathetic tests according to an age-specific reference. RESULTS: The overall prevalence of CAN was 17.1%. Patients with CAN had significantly higher GRI scores, target above range (TAR), coefficient of variation (CV), and standard deviation (SD) but significantly lower time in range (TIR) than those without CAN. The prevalence of CAN increased across higher GRI zones (P for trend <.001). A multivariate logistic regression analysis, adjusted for covariates such as HbA1c, demonstrated that the odds ratio (OR) of CAN was 9.05 (95% confidence interval [CI]: 2.21-36.96, P = .002) per 1-SD increase in the GRI. TIR and CV were also significantly associated with CAN in the multivariate model. The area under the curve of GRI for the prediction of CAN (0.85, 95% CI: 0.76-0.94) was superior to that of TIR (0.80, 95% CI: 0.71-0.89, P for comparison = .046) or CV (0.71, 95% CI: 0.57-0.84, P for comparison = .049). CONCLUSIONS: The GRI is significantly associated with CAN in patients with type 1 diabetes and may be a better CGM metric than TIR for predicting CAN.

Low-carbohydrate diet proved effective and safe for youths with type 1 diabetes: A randomised trial.

AIM: Low-carbohydrate (LC) diets have gained popularity. We compared glycaemic and metabolic parameters following an LC versus a Mediterranean (MED) diet in adolescents and youths with type 1 diabetes. METHODS: In a six-month, open-label, randomised trial, 40 individuals were assigned to either diet. Glycaemic outcomes, based on continuous glucose monitoring, included per cent time of blood glucose in the range [3.9-10.0 mmol/L (70-180 mg/dL)] and haemoglobin A1c (HbA1c). RESULTS: Twenty-eight (70%) were females. The median age was 18 years. After 6 months, the median time in range increased from 47% to 58% in the LC and from 52% to 64% in the MED diet group (p = 0.98). The delta values for the time in range were 16% and 7% for the respective groups (p = 0.09). The percentage of time >13.9 mmol/L (>250 mg/dL) improved more in the LC diet than in the MED diet group: -10% vs. -2% (p = 0.005). The percentage of time <3.0 mmol/L (<54 mg/dL) was comparable. The delta HbA1c improved in both groups: -0.7% vs. -0.1% (p = 0.02). Changes in BMI Z-score and lipid levels were similar. CONCLUSION: Both diets improved glycaemic outcomes in adolescents and youths with type 1 diabetes, without increasing hypoglycaemia or cardiovascular risk factors, indicating comparable safety and efficacy.

The related factors affecting the relationship between HbA1c and glucose management indicator in adult T2D patients with good glycemic control.

PURPOSE: To explore the relationship between glucose management indicator (GMI) and HbA1c and find the affecting factors in adult T2D patients with good glycemic control. METHODS: Adult T2D patients with both HbA1c < 7% and time in range (TIR) > 70% were retrospectively analyzed. A significant difference between GMI and HbA1c was defined as an absolute value of hemoglobin glycation index (|HGI|, HbA1c minus GMI) ≥ 0.5%. Factors associated with high |HGI| were determined by logistic regression analysis. The performance of possible factors in predicting high |HGI| was verified by ROC curve analysis. And the linear relationship between GMI and HbA1c was also investigated. RESULTS: Of all the 94 patients (median HbA1c 6.18%, mean GMI 6.34%) included, 28.72% had an |HGI | ≥ 0.5% and only 15.96% had an |HGI | < 0.1%. Standard deviation of blood glucose (SDBG), a glycemic variability index, affected |HGI| (OR = 3.980, P = 0.001), and showed the best performance in predicting high |HGI| (AUC = 0.712, cutoff value = 1.63 mmol/L, P = 0.001). HbA1c was linearly correlated with GMI (ß = 0.295, P = 0.004). Their correlation weakened after further adjusting for SDBG (ß = 0.232, P = 0.012). Linear correlation between them was closer in patients with smaller SDBG ( < 1.63 mmol/L) than those with larger SDBG (P = 0.004). CONCLUSIONS: Even in adult T2D patients with good glycemic control, the discrepancy between GMI and HbA1c existed. Their relationship was affected by glycemic variability. SDBG mainly accounted for this consequence. TRIAL REGISTRATION: Chinese clinical trial registry ( www.chictr.org.cn ), ChiCTR2000034884, 2020-07-23.

Safety and Efficacy of Using Advanced Hybrid Closed Loop Off-Label in an Infant Diagnosed with Permanent Neonatal Diabetes Mellitus: A Case Report and a Look to the Future.

The case report shows the safety and efficacy of insulin treatment with Advanced Hybrid Closed Loop (AHCL) system in a young patient affected by permanent neonatal diabetes mellitus (PNDM) due to chromosome 8 deletion syndrome involving the GATA4 gene. In the first days of life, he presented hyperglycaemia and started an intravenous insulin infusion therapy, replaced by a continuous subcutaneous insulin infusion (CSII) with Medtronic Minimed 780G® insulin pump (Medtronic, Northridge, CA, USA). At the age of 2 years, the off-label activation of SmartGuard® automated insulin delivery mode led to a great improvement in glycaemic control, reaching all recommended targets. At the 1-month follow-up visit, Time in Range (TIR) increased from 66% to 79%, with a Time in Tight Range (TTIR) of 55% and a reduction of 11% in time in hyperglycaemia and of 2% in time in hypoglycaemia. During the entire follow-up, no episodes of ketoacidosis or severe hypoglycaemia were observed and the patient maintained the glycaemic recommended targets reached at 1 month. Maintaining optimal glycaemic control and reducing hyperglycaemia are essential for brain growth and neurocognitive development in young patients. AHCL use should be considered to ensure good glycaemic control in patients affected by neonatal diabetes.

The importance of arterial stiffness in pediatric patients with type 1 diabetes mellitus: What's new?

Youths with type 1 diabetes (T1D) exhibits higher levels of pulse wave velocity (PWV) compared to healthy controls. Higher PWV in T1D subjects is associated with increased hazard of progression in albuminuria, decline in eGFR, cardiovascular (CV) events and mortality. In the recently published work by Georeli et al., increased PWV was associated with poor glycemic control as expressed by time-in-range (TIR) < 50 % in T1D children, adolescents and young adults. This finding is of great interest, since it is well known that glycemic control, as measured by TIR, is an important contributor of CV risk. The duration of TIR < 50 % is not reported by the authors, but is of importance, knowing that CGM provide data for the last 3-6 months, depending on the CGM model. In conclusion, PWV looks promising for risk stratification in T1D, but its exact role in T1D still remains to be fully explored.

Diurnal variation in the association between the scan frequency of isCGM and CGM metrics: post hoc analysis of the ISCHIA study.

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.

Time in range and mean glucose cut-off points for reduction of fetal outcomes in pregnant women with type 1 diabetes using automated insulin delivery systems.

AIM: In pregnant women with Type 1 Diabetes (T1D), achieving a lower recommended time in range (TIRp,63-140 mg/dl) could have an impact on fetal outcomes. To determine the TIRp and mean glucose cut-off point associated with better fetal outcomes in pregnant women using automated insulin delivery (AID) systems. METHODS: A prospective cohort of pregnant women with T1D, using AID systems and followed-up in Latin America was analyzed. Optimal TIRp and mean glucose cut-off points for predicting large for gestational age (LGA) were determined using the Liu method. Fetal outcomes were evaluated for the identified cut-off point and the one recommended by guidelines (TIRp > 70 %). RESULTS: Sixty-two patients were included (mean age 31.9 ± 5.9 years, HbA1c 7.57 %±1.29 %, TIRp 59.8 %±14.6 %). 27.5 % on advanced hybrid closed loop systems (AHCL). LGA (50 vs 17.9 %,p = 0.010) and hyperbilirubinemia (45 % vs 11.8 %,p = 0.016) were more common in patients with TIRp < 59.1 %. Optimal cut-off of TIRp in the second trimester for predicting LGA was < 59.1 % (sensitivity 75 %, specificity 61 %) with an AUC of 0.68(CI 0.48-0.88). Optimal cut-off for mean glucose was 133 mg/dL (sensitivity 69 %, specificity 70 %) with an AUC of 0.70(CI 0.51-0.88) in the same trimester. Better metabolic control during the third trimester was seen in the AHCL users compared to other devices. CONCLUSIONS: TIRp > 59.1 % and mean glucose < 133 mg/dl in the second trimester, is associated with lower fetal outcomes of large for gestational age. One of the strategies that would improve TIRp is the early use of AHCL systems. Further studies are needed before a strong recommendation can be made.

Psychological and Clinical Challenges in the Management of Type 1 Diabetes during Adolescence: A Narrative Review.

Adolescence, a critical period of physical and psychological development, presents unique challenges in type 1 diabetes (T1D) management due to endocrinological changes, reduced therapeutic adherence, and elevated susceptibility to psychological issues such as depression, anxiety, and eating disorders. This narrative review explores the impact of psychological and behavioral factors on glycemic control in adolescents with T1D. We examine the prevalence and influence of mental health disorders, lifestyle factors, harmful behaviors, and social dynamics on diabetes management and glycemic outcomes. Strategies for improving metabolic control are also reviewed, including cognitive behavioral therapy, technological devices, and educational interventions. The importance of tailored psychological support, family involvement, and targeted interventions to improve adherence to treatment and glycemic control in adolescents with T1D should be emphasized.

Glucose Variability in People with Type 1 Diabetes: Associations with Body Weight, Body Composition, and Insulin Sensitivity.

The prevalence of overweight and obesity increases in people with type 1 diabetes (T1D). However, the impact of fat accumulation on glucose dynamics in T1D is poorly understood. We assessed continuous glucose monitoring (CGM) parameters in patients with T1D depending on their body weight, body composition, and insulin sensitivity. In 547 patients, including 238 overweight/obese individuals, CGM-derived time in range (TIR) and glucose variability (GV) were estimated. Body composition was assessed by DXA. Estimated glucose disposal rate (eGDR) was used as an indicator of insulin sensitivity. Overweight/obese patients, when compared to normal-weight ones, have a lower time below range (TBR) (<3 mmol/L), GV, and experienced fewer episodes of low glucose. In men, lower TIR, higher time above range (TAR), and GV reduction were associated with central adiposity assessed by total, trunk, and android fat mass. In women, gynoid fat mass only was associated with a lower TIR and higher TAR. The eGDR was a positive predictor of TIR and a negative predictor of TAR, TBR, and GV in men and women. In conclusion, adiposity in people with T1D is associated with a lower risk of CGM-confirmed hypoglycemia, higher TAR, and reduced GV. These features of daily glucose dynamics may be mediated by insulin resistance.

Temporary Target Versus Suspended Insulin Infusion in Patients with Type 1 Diabetes Using the MiniMed 780G Advanced Closed-Loop Hybrid System During Aerobic Exercise: A Randomized Crossover Clinical Trial.

Aim: To compare the safety in terms of hypoglycemic events and continuous glucose monitoring (CGM) metrics during aerobic exercise (AE) of using temporary target (TT) versus suspension of insulin infusion (SII) in adults with type 1 diabetes (T1D) using advanced hybrid closed-loop systems. Methods: This was a randomized crossover clinical trial. Two moderate-intensity AE sessions were performed, one with TT and one with SII. Hypoglycemic events and CGM metrics were analyzed during the immediate (baseline to 59 min), early (60 min to 6 h), and late (6 to 36 h) post-exercise phases. Results: In total, 33 patients were analyzed (44.6 ± 13.8 years), basal time in range (%TIR 70-180 mg/dL) was 79.4 ± 12%, and time below range (%TBR) <70 mg/dL was 1.8 ± 1.7% and %TBR <54 mg/dL was 0.5 ± 0.9%. No difference was found in the number of hypoglycemic events, %TBR <70 mg/dL and %TBR <54 mg/dL between TT and SII. Differences were found in the early phase, with better values when using TT for %TIR 70-180 mg/dL (83.0 vs. 65.3, P = 0.005), time in tight range (%TITR 70-140 mg/dL) (56.3 vs. 41.5, P = 0.04), and time above range (%TAR >180 mg/dL) (15.3 vs. 31.8, P = 0.01). In the diurnal period, again %TIR was better for TT use (82.1 vs. 73.1, P = 0.02) and %TAR (15.0 vs. 22.96, P = 0.04). No significant differences were found in the CGM metrics during the different phases of AE. Conclusion: Our data appear to show that the use of TT compared with SII is equally safe in all phases of AE. However, the use of TT allows for a better glycemic profile in the early phase of exercise.

Efficacy and Safety of Different Hybrid Closed Loop Systems for Automated Insulin Delivery in People With Type 1 Diabetes: A Systematic Review and Network Meta-Analysis.

AIMS: To compare the efficacy and safety of different hybrid closed loop (HCL) systems in people with diabetes through a network meta-analysis. METHODS: We searched MEDLINE, EMBASE, CENTRAL and PubMed for randomised clinical trials (RCTs) enrolling children, adolescents and/or adults with type 1 or type 2 diabetes, evaluating Minimed 670G, Minimed 780G, Control-IQ, CamAPS Fx, DBLG-1, DBLHU, and Omnipod 5 HCL systems against other types of insulin therapy, and reporting time in target range (TIR) as outcome. RESULTS: A total of 28 RCTs, all enrolling people with type 1 diabetes, were included. HCL systems significantly increased TIR compared with subcutaneous insulin therapy without continuous glucose monitoring (SIT). Minimed 780G achieved the highest TIR ahead of Control IQ (mean difference (MD) 5.1%, 95% confidence interval (95% CI) [0.68; 9.52], low certainty), Minimed 670G (MD 7.48%, 95% CI [4.27; 10.7], moderate certainty), CamAPS Fx (MD 8.94%, 95% CI [4.35; 13.54], low certainty), and DBLG1 (MD 10.69%, 95% CI [5.73; 15.65], low certainty). All HCL systems decreased time below target range, with DBLG1 (MD -3.69%, 95% CI [-5.2; -2.19], high certainty), Minimed 670G (MD -2.9%, 95% CI [-3.77; -2.04], moderate certainty) and Minimed 780G (MD -2.79%, 95% CI [-3.94; -1.64], high certainty) exhibiting the largest reductions compared to SIT. The risk of severe hypoglycaemia and diabetic ketoacidosis was similar to other types of insulin therapy. CONCLUSIONS: We show a hierarchy of efficacy among the different HCL systems in people with type 1 diabetes, thus providing support to clinical decision-making. TRIAL REGISTRATION: PROSPERO CRD42023453717.

Time-in-range derived from self-measured blood glucose in people with type 2 diabetes advancing to iGlarLixi: A participant-level pooled analysis of three phase 3 LixiLan randomized controlled trials.

AIM: To evaluate the efficacy of a fixed-ratio combination of insulin glargine 100 U/mL plus lixisenatide (iGlarLixi) in people with type 2 diabetes (T2D) using derived time-in-range (dTIR). METHODS: Participant-level data from LixiLan-L, LixiLan-O and LixiLan-G were pooled and dTIR (70-180 mg/dL), derived time-above-range (> 180 mg/dL) and derived time-below-range (dTBR; < 70 mg/dL) were calculated from participant seven-point self-monitored blood glucose profiles. RESULTS: This pooled analysis included data from 2420 participants receiving iGlarLixi (n = 1093), iGlar (n = 836), Lixi (n = 234) or a glucagon-like peptide-1 receptor agonist (GLP-1 RA) (n = 257). Numerically greater improvements in least square (LS) means dTIR were seen from baseline to end of treatment (EOT) with iGlarLixi (25.7%) versus iGlar (15.8%), Lixi (11.7%) or GLP-1 RA (16.2%). At EOT, the mean (standard deviation) dTBR was 0.71% ± 3.4%, 0.61% ± 3.2%, 0.08% ± 1.0% and 0.0% ± 0.0% for iGlarLixi, iGlar, Lixi and GLP-1 RA, respectively. In a subgroup analysis, participants aged younger than 65 years (n = 1690) and 65 years or older (n = 713) showed numerically greater improvements in LS means dTIR from baseline to EOT with iGlarLixi versus iGlar, Lixi or GLP-1 RA. CONCLUSIONS: iGlarLixi achieved improvements in dTIR, with low dTBR values, providing further evidence to inform clinical outcomes with the use of iGlarLixi.

Performance of the MiniMed 780G system on mitigating menstrual cycle-dependent glycaemic variability.

AIM: To map the glycaemic variabilities and insulin requirements across different phases of the menstrual cycle and assess the efficacy and performance of the MiniMed 780G system on mitigating glycaemic variabilities during phases of the menstrual cycle. MATERIALS AND METHODS: A pilot study recruiting 15 adolescent and young adult females with type 1 diabetes was conducted. Only females with regular spontaneous menstruation were enrolled in the current study. Phases of each menstrual cycle were determined as either follicular phase or luteal phase. The study analysed continuous glucose monitoring metrics during two study periods: the open loop period (OLP) and the advanced hybrid closed-loop (AHCL) period; each period lasted 3 consecutive months. RESULTS: During the OLP, the mean time in range (TIR) significantly decreased during the luteal phase compared with the follicular phase (65.13% ± 3.07% vs. 70.73% ± 2.05%) (P < .01). The mean time above range significantly increased from 21.07% ± 2.58% during the follicular phase to 24.87% ± 2.97% during the luteal phase (P < .01). After initiating the AHCL period, TIR was comparable during both phases of the menstrual cycle (P = .72), without increasing the time spent below 70 mg/dL (P > .05). Regarding insulin delivery during the AHCL period, the percentage of Auto basal and Auto correction delivered by the algorithm increased by 13.55% and 30.6%, respectively (P < .01), during the luteal phase. CONCLUSIONS: The fully automated adaptive algorithm of the MiniMed 780G system mitigated menstrual cycle-dependent glycaemic variability, successfully attaining the recommended glycaemic outcomes with a TIR greater than 70% throughout the entire menstrual cycle.

IDegLira improves time in range in a cohort of patients with type 2 diabetes: TiREX study.

AIMS: To assess the effects of IDegLira on glucometric indices deriving from intermittently scanned Continuous Glucose Monitoring (isCGM) in patients with type 2 diabetes (T2D). METHODS: Retrospective, observational, cohort, multi-center, "pre - post" study. All adults consecutively identified in the medical records who started treatment with IDegLira, and for whom an isCGM report before and after the initiation of IDegLira was available were included in the study. Time in range (TIR) represented the primary endpoint. Additional glucometric indices, insulin doses and body weight were also assessed. RESULTS: Overall, 87 patients were included by 5 diabetes centers [mean age 70.2 ± 11.0 years, mean duration of T2D 15.5 ± 9.6 years; BMI 29.4 ± 5.4 kg/m2, baseline HbA1c 9.1 ± 2.1%, 33% insulin naïve, 20.7% treated with basal-oral therapy (BOT), and 46% treated with multiple daily injections of insulin (MDI)]. After an average of 1.7 weeks from IDegLira initiation, TIR significantly increased from 56.8 ± 23.5% to 81.3 ± 13.5% (p < 0.0001), TAR decreased from 42.3 ± 24.2% to 17.1 ± 13.6% (p < 0.0001), while TBR remained steadily low (from 1.3 ± 2.3% to 1.4 ± 2.6%; p = 0.62). Estimated HbA1c decreased from 9.1 ± 2.1% to 6.7 ± 0.6% (p < 0.0001) and percentage of patients with a blood glucose coefficient of variation ≥ 36% dropped from 33.2 to 13.8% (p = 0.0005). In patients on MDI, the reduction in the total insulin dose was substantial (from 55.8 ± 31.2 IU to 27.2 ± 12.3 U). CONCLUSIONS: In T2D patients with poor metabolic control, either insulin naïve or treated with BOT or MDI, the introduction of IDegLira produces a significant increase in the time spent in good metabolic control and a marked reduction in glycemic fluctuations.

Effects of glucagon-like peptide-1 receptor agonists on glycated haemoglobin and continuous glucose monitoring metrics as adjunctive therapy to insulin in adults with type 1 diabetes: A meta-analysis of randomized controlled trials.

AIMS: To conduct a meta-analysis of randomized controlled trials (RCTs) to evaluate the effect of glucagon-like peptide-1 receptor agonists (GLP-1RAs) on glycated haemoglobin (HbA1c) and continuous glucose monitoring (CGM) metrics as an adjunct to insulin therapy in adults with type 1 diabetes mellitus (T1D). METHODS: A systematic literature search was conducted through Medline (via PubMed), Cochrane Library, and Google Scholar up to 27 May 2024. Dual-independent study selection, data extraction, and quality assessment were performed. Results were summarized using random-effects meta-analysis. RESULTS: Six RCTs were identified, involving a total of 378 individuals with T1D. The use of GLP-1RAs in addition to standard insulin therapy was associated with a significant reduction in HbA1c (mean difference [MD] -0.21%, 95% confidence interval [CI] -0.36 to -0.06; p = 0.007) and a similar time in range (TIR) compared to placebo (MD -0.22%, 95% CI -2.39 to 1.95; p = 0.84). GLP-1RA therapy resulted in a significantly higher time below range (MD 1.13%, 95% CI 0.50 to 1.76; p < 0.001) and a lower time above range compared with placebo (MD -1.83%, 95% CI -2.51 to -1.15; p < 0.001). Nonsignificant differences were noted for the secondary outcomes, including the mean amplitude of glucose excursion, continuous overall net glycaemic action for 60 min, mean daily glucose, coefficient of variation, and mean standard deviation of weekly glucose levels. CONCLUSION: Our findings suggest that, in individuals with T1D, add-on therapy with GLP-1RAs does not confer significant benefits in terms of CGM metrics and is associated with a longer time below the target glycaemic range.