bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2025–09–21
sixteen papers selected by
Mott Given
  1. Continuous Glucose Monitors in Radiology.
  2. Exploring the Relationship Between Newly Defined Continuous Glucose Monitoring (CGM) Metrics and the Standard CGM Metrics in 30,000 People with Type 1 Diabetes.
  3. Discrepancies between current displayed and auto-logged glucose values in FreeStyle Libre 3: Implications for clinical interpretation.
  4. Using digital tools to improve diabetes care in India with continuous glucose monitoring.
  5. Comment on Freckmann et al. A Comparative Analysis of Glycemic Metrics Derived From Three Continuous Glucose Monitors. Diabetes Care 2025;48:1213-1217.
  6. Implementing a Continuous Glucose Monitoring Hospital Discharge Program: Strategies and Best Practices.
  7. Performance of flash continuous glucose monitoring and glycemic marker correlations in Chinese pregnant women with non-type 1 diabetes.
  8. Impact of race and delayed adoption of diabetes technology on glycemia and partial remission in type 1 diabetes.
  9. Inverse Association Between the Dawn Phenomenon and Thyroid Feedback Quantile-Based Index in Type 2 Diabetes Using Continuous Glucose Monitoring: A Cross-Sectional Study.
  10. Correction: Use of an insulin titration protocol based on continuous glucose monitoring in postoperative cardiac surgery patients with type 2 diabetes and prediabetes: a randomized controlled trial.
  11. Use of Continuous Glucose Monitors in Publicly Insured Youth With Type 2 Diabetes: A 12-month Pilot and Feasibility Study.
  12. Glycemic responses of three mango varieties in subjects with and without T2D: a pilot crossover study using OTT and CGM.
  13. Associations between daily dietary carbohydrate intake and TIR in adults with type 1 diabetes.
  14. Response to Comments on Freckmann et al. A Comparative Analysis of Glycemic Metrics Derived From Three Continuous Glucose Monitoring Systems. Diabetes Care 2025;48:1213-1217.
  15. The therapeutic efficacy of continuous glucose monitoring in diabetes: an updated meta-analysis with meta-regression.
  16. Impact of Age at Diagnosis and Insulin Delivery Modality on Free-Living Glycemia in Type 1 Diabetes During Periods Associated with Dysglycemia: A Retrospective Analysis of the Type 1 Diabetes EXercise Initiative Study.
  1. Radiol Technol. 2025 Sep-Oct;97(1):97(1): 29-32
    Continuous Glucose Monitors in Radiology.
    Brittany N Gundersen, Jeffrey S Legg.
      
  2. Diabetes Technol Ther. 2025 Sep 11.
    Exploring the Relationship Between Newly Defined Continuous Glucose Monitoring (CGM) Metrics and the Standard CGM Metrics in 30,000 People with Type 1 Diabetes.
    Halis Kaan Akturk, Kagan Ege Karakus, Boyang Chen, Tomas C Walker.
      Background: Rebound hyperglycemia (RHyper), rebound hypoglycemia (RHypo), extended hyperglycemia (EHyper), and extended hypoglycemia (EHypo) are newly defined continuous glucose monitoring (CGM) metrics. Here, we investigated the characteristics of these new metrics and the relationship between new CGM metrics and standard metrics. Materials and Methods: In this retrospective cohort study, 30,000 CGM users with at least 90 days of CGM data were randomly selected from Dexcom Clarity database. Standard and new CGM metrics were calculated for each user. Four different cutoffs were used to define RHyper and RHypo, and two cutoffs were used to define EHyper and EHypo events. The number of RHyper, RHypo, EHyper, and EHypo events per week, mean duration of events, and mean area under the curve of events were calculated. For rebound events, the rate of change (ROC) was calculated. Pearson correlation and simple linear regression were used to analyze the data. Results: Mean time in 70-180 mg/dL was 61.8 ± 20.7%, mean glucose was 173 ± 37.1 mg/dL, and coefficient of variation (CV) was 32.1 ± 7.2%. RHyper, RHypo, and EHyper were more frequent during daytime and increased throughout the day. EHypo mostly occurred during nighttime. CV correlated strongly with RHyper (70-180 mg/dL) events/week (r = 0.67) and RHypo (180 to 70 mg/dL) events/week (r = 0.64). Time in range had the strongest correlation with EHyper events/week (r = -0.88) among new metrics. RHyper events and RHypo events were strongly correlated with each other (r = 0.92). RHyper and RHypo ROC have a stronger correlation with CV than the correlation between CV and time below range (TBR) metrics. Conclusions: For rebound and extended metrics, the most important metric was the number of events/week. RHyper and RHypo had a stronger correlation with CV and hypoglycemia metrics (TBR) than the correlation between CV and TBR. Thus, rebound events have the potential to detect hypoglycemia events caused by glycemic variability. [Figure: see text].
    Keywords:  Dexcom Clarity; continuous glucose monitoring; extended hyperglycemia; extended hypoglycemia; rebound hyperglycemia; rebound hypoglycemia; type 1 diabetes
    DOI:  https://doi.org/10.1177/15209156251377797
  3. Diabetes Obes Metab. 2025 Sep 18.
    Discrepancies between current displayed and auto-logged glucose values in FreeStyle Libre 3: Implications for clinical interpretation.
    Lilian Witthauer, Camilo Mendez, José Garcia-Tirado, Manuel Eichenlaub, Delia Waldenmaier, Stefan Pleus, Guido Freckmann.
       AIMS: The FreeStyle Libre 3 (FSL3) continuous glucose monitoring (CGM) system provides both auto-logged glucose values (AL) and current displayed glucose values (CUR). These values are often assumed to be interchangeable; however, discrepancies and their clinical relevance remain underexplored.
    MATERIALS AND METHODS: Data from a 15-day study in 24 study participants wearing FSL3 were analysed, including three in-clinic sessions with glycaemic excursions during which CUR values were retrieved every 15 min by study personnel. Paired AL and CUR readings were compared using descriptive statistics, Wilcoxon signed-rank tests, and mean absolute relative difference (MARD) calculations. Display errors defined as instances where the app showed an error message instead of a CUR value were analysed using linear mixed-effects models to assess associations with glucose level and rate of change (RoC).
    RESULTS: CUR values were comparable to AL in general (mean difference: -1.2 ± 6.4 mg/dL), but slightly lower in the hypoglycaemic range. Discrepancies exceeding ±10 mg/dL occurred in about 10% of cases. MARD was comparable between AL (9.7%) and CUR (10.1%), with greater deviation in hypoglycaemia. Display errors (3.9%) occurred more often at higher glucose levels (mean AL difference: +91.9 mg/dL) and during rapid fluctuations (mean absolute RoC difference: +1.52 mg/dL/min; both p < 0.001).
    CONCLUSIONS: Although differences between AL and CUR were generally small, they were systematic and more pronounced in critical contexts like hypoglycaemia and rapid glucose change. Recognising these patterns may improve CGM data interpretation and alignment between user actions, provider decisions, and automated systems. These differences can reclassify readings across clinical thresholds, affecting patient-clinician alignment despite small average biases.
    Keywords:  clinical trial; continuous glucose monitoring (CGM); glycaemic control; type 1 diabetes
    DOI:  https://doi.org/10.1111/dom.70140
  4. Ther Adv Endocrinol Metab. 2025 ;16 20420188251372290
    Using digital tools to improve diabetes care in India with continuous glucose monitoring.
    Jothydev Kesavadev, Banshi Saboo, Manoj S Chawla, Ambika Gopalakrishnan Unnikrishnan, Timothy C Dunn, Mangesh Harihar Tiwaskar.
      Continuous glucose monitoring (CGM) has revolutionized diabetes management globally, offering real-time insights into blood glucose levels and trends. In India, where diabetes prevalence is significant, the adoption of digital health tools (DHTs) for CGM has seen remarkable growth. However, successful integration and adoption of these DHTs require collaboration between healthcare professionals and individuals with diabetes. Ensuring the compatibility, accuracy, and reliability of CGM systems is imperative for optimizing diabetes management outcomes in India. Several challenges persist in adopting DHTs for CGM in the country. The adoption of ambulatory glucose profiles and CGM using DHTs has been transformative in diabetes clinics. This paper culminates with expert recommendations on integrating DHTs into diabetes clinics, focusing on training, communication, and technology utilization. The introduction of the Freestyle® Libre into diabetes clinics demonstrates the system's influence and the advantages seen by both patients and healthcare professionals. With real-time data, improved patient interaction, real-world data for evidence-based practices, and the ability to support patients' and healthcare professionals' informed decision-making, these tools have the potential to completely transform the management of diabetes. The goal is to enhance diabetes care through digital health solutions, considering the unique healthcare landscape of India.
    Keywords:  continuous glucose monitoring; diabetes; diabetes management; digital health tools healthcare professionals
    DOI:  https://doi.org/10.1177/20420188251372290
  5. Diabetes Care. 2025 Oct 01. 48(10): e124-e125
    Comment on Freckmann et al. A Comparative Analysis of Glycemic Metrics Derived From Three Continuous Glucose Monitors. Diabetes Care 2025;48:1213-1217.
    Roy W Beck.
      
    DOI:  https://doi.org/10.2337/dc25-0920
  6. J Diabetes Sci Technol. 2025 Sep 16. 19322968251370754
    Implementing a Continuous Glucose Monitoring Hospital Discharge Program: Strategies and Best Practices.
    Nishant Kumar, Amy M Knight, Andrew P Demidowich, Camille F Stanback, Holly Bashura, Qudsia Hussain, Eva H Gonzales, Jordan Funk, Mahsa Motevalli, Mihail Zilbermint.
      Continuous glucose monitoring (CGM) has become the standard of care for outpatient diabetes management, yet its initiation during hospitalization-particularly at discharge-remains underutilized. The transition from hospital to home presents a unique opportunity to start CGM, educate patients, and improve glycemic outcomes. Although preliminary studies suggest that CGM initiation at discharge can increase time-in-range and reduce hypoglycemia and hospital readmissions, widespread adoption faces several challenges, including therapeutic inertia, patient selection, insurance barriers, and limited implementation guidance. At the time of this writing, CGMs are not yet US Food and Drug Administration-approved for inpatient use, but approval is anticipated. In this article, we present an actionable, stepwise protocol for CGM initiation at hospital discharge, developed by the Council for Clinical Excellence in Inpatient Diabetes at Johns Hopkins Medicine. The protocol includes multidisciplinary coordination, inclusive patient selection, structured education, designation of outpatient follow-up providers, and emphasis on consistent postdischarge care. We address common barriers such as impaired cognition during recovery and device compatibility with imaging studies. While further research is needed to confirm long-term cost-effectiveness and clinical outcomes, we believe our protocol can serve as a practical foundation for hospitals and providers seeking to safely and effectively integrate CGM initiation into discharge workflows.
    Keywords:  CGM; clinical protocol; continuous glucose monitoring; diabetes technology; discharge; hospital; strategy
    DOI:  https://doi.org/10.1177/19322968251370754
  7. World J Diabetes. 2025 Aug 15. 16(8): 106967
    Performance of flash continuous glucose monitoring and glycemic marker correlations in Chinese pregnant women with non-type 1 diabetes.
    Ling Lyu, Yi-Ling Huang, Yu Huang, Ze-Yu Wu, Fan Ping, Yu-Xiu Li.
       BACKGROUND: Maternal diabetes significantly increases the risk of adverse maternal and neonatal outcomes. Traditional self-monitoring of blood glucose is often invasive and limited in its ability to capture glycemic variability. Flash continuous glucose monitoring (FCGM) offers a promising alternative; however, its reliability and correlation with biochemical markers such as hemoglobin A1c (HbA1c) and glycated albumin (GA) in pregnant women with gestational diabetes mellitus (GDM) and type 2 diabetes mellitus (T2DM) remain underexplored.
    AIM: To evaluate the performance of the FreeStyle Libre H FCGM against plasma glucose and its correlations with HbA1c and GA.
    METHODS: This prospective observational study involved 152 pregnant women with GDM or T2DM, with intermittent collection of venous plasma glucose, HbA1c, GA, and concurrent FCGM data at regular intervals at a single center. Relationships were evaluated using restricted cubic spline and mixed-effects models. Receiver operating characteristic curve analysis was performed to compare the ability of HbA1c and GA to detect suboptimal glycemic control.
    RESULTS: Analysis of 507 FCGM-plasma glucose pairs revealed an overall mean absolute relative difference of 7.96%. Mean absolute relative differences were 9.22%, 7.75%, and 4.15% for low (3.5-4.4 mmol/L), medium (4.5-7.8 mmol/L), and high (7.9-13 mmol/L) glucose levels, respectively. Most values fell within zone A or zone B on the Clarke and Parkes Error Grids. Bland-Altman analysis indicated a slight underestimation by FCGM (-0.121 mmol/L). Restricted cubic spline analysis revealed significant linear or nonlinear associations between HbA1c/GA and mean glucose, time in range, time above range, and coefficient of variation, but not time below range. Both HbA1c and GA were influenced by gestational age and pregestational body mass index. Receiver operating characteristic analysis showed that HbA1c had comparable or superior performance to GA in detecting suboptimal glycemic control based on FCGM-derived thresholds.
    CONCLUSION: The FCGM system served as a validated reference for evaluating glycemic markers in pregnant women with T2DM and GDM. HbA1c reliably assessed average glycemia, while GA provided complementary insight.
    Keywords:  Continuous glucose monitoring; Diabetes; Glycated albumin; Hemoglobin A1c; Pregnancy
    DOI:  https://doi.org/10.4239/wjd.v16.i8.106967
  8. J Pediatr Endocrinol Metab. 2025 Sep 17.
    Impact of race and delayed adoption of diabetes technology on glycemia and partial remission in type 1 diabetes.
    Adriana Chader-Gata Garcia, Komalpreet Kaur, Rashida Talib, Parissa Salemi, Joanna Fishbein, Benjamin Udoka Nwosu.
       OBJECTIVES: Continuous glucose monitors (CGM) are the mainstay of glucose monitoring in type 1 diabetes (T1D). However, the impact of race/ethnicity and the timing of CGM adoption following T1D diagnosis is unclear. We examined the effect of race/ethnicity and CGM adoption on glycemia and partial remission (PR) in T1D.
    METHODS: A 24-month longitudinal retrospective cohort study of youth with T1D who used Dexcom CGM G5/G6 between 2018 and 2022 was conducted. Subjects were classified as non-Hispanic White (NHW) or Other (Asian, Black/African American, Hispanic/Latino, or other). Glycemia was measured as %change in hemoglobin A1c (A1c) and time in range (TIR) from baseline to 24 months. PR was denoted as an insulin-dose-adjusted A1c (IDAA1c) value of ≤9. The statistical approach included the paired t-test, the Wilcoxon signed-rank test, and mixed effects models for repeated measures.
    RESULTS: Early CGM adoption occurred in 90 % (61/68) of NHW subjects vs. 63 % (43/68) of the Other, p=0.0003. Early CGM adoption was associated with improved glycemia and PR as marked by a significantly greater %decrease in A1c, p=0.0008, and IDAA1c, p=0.0003, at 24 months following CGM adoption. Temporal trends in A1c and IDAA1c were significantly lower among NHW subjects, p<0.0001, and the probability of PR was significantly greater, p<0.0001. Early CGM adoption conferred a greater probability of PR than late CGM adoption, p<0.0001.
    CONCLUSIONS: Early adoption of diabetes technology should be accelerated in all children with T1D, particularly minority children, to reduce hyperglycemia, promote PR, and close the gap in diabetes care and complications in the United States.
    Keywords:  continuous glucose monitoring; hemoglobin A1c; insulin pump; race/ethnicity; type 1 diabetes; youth
    DOI:  https://doi.org/10.1515/jpem-2025-0332
  9. Diabetes Metab Syndr Obes. 2025 ;18 3465-3475
    Inverse Association Between the Dawn Phenomenon and Thyroid Feedback Quantile-Based Index in Type 2 Diabetes Using Continuous Glucose Monitoring: A Cross-Sectional Study.
    Yan Xia, Hong-Jing Chen, Reng-Na Yan, Xiao-Wei Zhu, Han Zhao, Bo Ding, Yun Hu.
       Purpose: The mechanism of the dawn phenomenon remains poorly understood, and no targeted therapies are currently available. Emerging evidence suggests thyroid dysfunction may contribute to dawn phenomenon by modulating hepatic glucose output, insulin sensitivity, and β-cell function. This study utilized continuous glucose monitoring (CGM) to identify patients with type 2 diabetes exhibiting dawn phenomenon and to investigate its association with thyroid feedback efficiency.
    Patients and Methods: This study included patients with type 2 diabetes. All patients underwent CGM before any adjustments to their glucose-lowering therapy. The dawn phenomenon was determined if the elevation of blood glucose from 3 AM to 7 AM was more than 1.11 mmol/L. Clinical data, including medications, diabetic complications and comorbidities, biochemical markers, hemoglobin A1c (HbA1c), beta-cell function, and thyroid function, were recorded.
    Results: A total of 524 patients were included, of whom 265 (50.6%) exhibited the dawn phenomenon. A control group of 216 patients was matched based on HbA1c levels from those without dawn phenomenon using propensity score matching. The standard deviation of blood glucose (SDBG) (2.26 vs 1.78, P=0.001) and coefficient of variation (CV) (22.86 vs 16.97, P<0.001) were significantly higher in the dawn phenomenon group compared to the non-dawn phenomenon group. Thyroid feedback quantile-based index (TFQI) of free thyroxine (FT4) was negatively correlated with the elevation of blood glucose from 3 AM to 7 AM (BG 3-7) (r=-0.211, P=0.002). Low-density lipoprotein (LDL) showed a positive correlation with fasting blood glucose (r=0.242, P=0.001) and BG 3-7 (r=0.123, P=0.083). Regression analysis indicated that TFQI of free triiodothyronine (FT3) (β=-2.399, P<0.001) and LDL (β=0.550, P=0.004) were independent predictors of BG 3-7.
    Conclusion: The dawn phenomenon significantly correlates with glycemic fluctuation severity and TFQI. These findings indicate the relationship between thyroid hormones and glucose regulation, providing new insights into the mechanism of the dawn phenomenon.
    Keywords:  blood glucose variability; dawn phenomenon; diabetes; thyroid hormones
    DOI:  https://doi.org/10.2147/DMSO.S543452
  10. Cardiovasc Diabetol. 2025 Sep 13. 24(1): 361
    Correction: Use of an insulin titration protocol based on continuous glucose monitoring in postoperative cardiac surgery patients with type 2 diabetes and prediabetes: a randomized controlled trial.
    Sun-Joon Moon, Min-Su Kim, Yun Tae Kim, Ha-Eun Lee, Young-Woo Lee, Su-Ji Lee, Euy-Suk Chung, Cheol-Young Park.
      
    DOI:  https://doi.org/10.1186/s12933-025-02908-0
  11. J Diabetes Sci Technol. 2025 Sep 20. 19322968251368366
    Use of Continuous Glucose Monitors in Publicly Insured Youth With Type 2 Diabetes: A 12-month Pilot and Feasibility Study.
    Sejal Shah, Molly L Tanenbaum, Alondra Loyola, Nathan Grant L Sala, Himani Darji, Sarah Hanes, Franziska K Bishop, Korey K Hood, David M Maahs.
       BACKGROUND: Type 2 diabetes (T2D) disproportionately affects youth with public insurance of minority and lower socioeconomic status backgrounds. We aimed to determine feasibility of CGM use in this understudied population.
    METHODS: We enrolled youth <20 years old with T2D, provided or prescribed intermittent scanned CGM, and followed established clinic workflows with six data collection visits over 12-months. CGM use was measured by % wear time per two-week period (>75% wear-time as goal) from downloaded report prior to clinic visit. Exploratory outcomes included: 14-day CGM wear time in range (TIR: % time spent between 70 and 180 mg/dl), HbA1c, and patient-reported outcomes (PROs) collected from youth and parents.
    RESULTS: We enrolled 30 youth (age 15.1 years [SD 2.48]; HbA1c 10.2%, range: 6.5%-15.5%), 46.7% female, 90% Hispanic. At baseline, 37% previously used CGM and 53% lacked glucometer data. CGM use was 50% at three months and 23% at 12 months. CGM wear time decreased by 6.4 days per two weeks by 12 months. Mean HbA1c was 9.8% at 12 months and median TIR decreased from 71% to 42%. Parents and youth had moderate-to-positive attitudes about diabetes technology. Youth endorsed fair levels of global health; and youth and parents endorsed fair general and diabetes-related health-related quality of life.
    CONCLUSIONS: Strategies for sustained CGM use in youth with T2D may differ from adults with T2D or youth with type 1 diabetes. Additional studies are needed to evaluate facilitators and barriers of sustained CGM use to optimize CGM use in youth with T2D.
    CLINICALTRIALS: gov registration:NCT05074667.
    Keywords:  continuous glucose monitor; pediatrics; public insurance; type 2 diabetes
    DOI:  https://doi.org/10.1177/19322968251368366
  12. Eur J Clin Nutr. 2025 Sep 13.
    Glycemic responses of three mango varieties in subjects with and without T2D: a pilot crossover study using OTT and CGM.
    Sugandha Kehar, Surya Prakash Bhatt, Ravindra M Pandey, Irshad Ahmad Ansari, Rajashekar Reddy Palavalli, Vimal Gupta, Anoop Misra.
       OBJECTIVES: Mango consumption is often restricted in diet consumed by people with diabetes due to concerns about its glycemic impact. This study aimed to compare the glycemic effects of mango consumption with those of white bread and glucose in subjects with and without type 2 diabetes (T2D).
    METHODS: We conducted a two-phase study involving 95 participants (45 with T2D, 50 non-diabetic). Phase 1 employed oral tolerance test (OTT) to assess immediate glycemic responses to mango (Safeda, Dasheri, and Langra), bread, and glucose. Phase 2 utilized continuous glucose monitoring (CGM) to evaluate glycemic profiles over three days.
    RESULTS: On OTT, in non-diabetic subjects, mango consumption resulted in non-significantly lower postprandial glucose peaks compared to glucose and bread, except Langra variety which showed lowest area under the curve for glucose of borderline significance. In subjects with T2D, mango varieties performed similarly to bread. CGM data revealed that mango consumption over three days resulted in a similar glycemic profile to bread in non-diabetic subjects and a lower glycemic profile in subjects with T2D, though most differences were statistically not significant. Mean Amplitude of Glycemic Excursion (MAGE) was significantly lower after mango ingestion as compared to bread in CGM data in subjects with T2D.
    CONCLUSIONS: Data show limited glycemic impact of tested mango varieties, comparable to or lower than white bread, especially in T2D subjects. The significant reduction in MAGE observed with mango consumption suggests potential benefits for glycemic variability. With portion control in calorie restrictive diets, mango may be suitable for people with T2D.
    DOI:  https://doi.org/10.1038/s41430-025-01659-1
  13. Front Nutr. 2025 ;12 1638849
    Associations between daily dietary carbohydrate intake and TIR in adults with type 1 diabetes.
    Yunying Cai, Xi Li, Xin Xiong, Lun Zhang, Jianfeng He, Heng Su.
       Objective: To assess the association between daily carbohydrate (CHO) intake and glycemic control in adults with type 1 diabetes (T1D).
    Methods: Patients with T1D who received continuous glucose monitoring (CGM) to manage their blood glucose levels were enrolled in the study. A dietitian analyzed dietary components, including carbohydrate, protein, and fat percentages in the total dietary intake. Mean individual daily CHO intake (MIDC) and relative deviation from MIDC (< 80% low; 81%-120% medium, >120% high CHO consumption) were compared with parameters of glycemic control assessed by CGM.
    Results: Records from 36 patients [11 male, 25 female; age 39.5 ± 13.9 years; HbA1c 9.0 ± 2.8% (75 ±31 mmol/mol)]. Provided 356 days of data for a total of 1,068 meals. Time in range (3.9-10 mmol/l) for low, medium, and high CHO consumption was 81.6 (70.96, 90.28)%, 74.65 (59.55, 84.9)%, and 64.58 (51.04, 77.78)%, respectively (P < 0.001). Time above range (>10 mmol/L) was 9.55 (1.39, 17.95)%, 10.42 (2.78, 27.43)%, and 27.08 (11.46, 47.92)%, respectively (P < 0.001). There was no between-group difference for time in hypoglycemia (< 3.9 mmol/L; P = 0.136). After adjusting for HbA1c, total calorie intake, and total daily insulin dose, carbohydrate intake was negatively correlated with achieving TIR ≥ 70%.
    Conclusions: Daily CHO intake was inversely associated with glycemic control in adults with T1D. A carbohydrate energy percentage between 40% and 50% and a relatively low daily carbohydrate intake may be a strategy to optimize glucose control in suboptimal-controlled T1D in real-world settings.
    Keywords:  carbohydrate; continuous glucose monitoring; diet effect; hypoglycemia; type 1 diabetes
    DOI:  https://doi.org/10.3389/fnut.2025.1638849
  14. Diabetes Care. 2025 Oct 01. 48(10): e128-e129
    Response to Comments on Freckmann et al. A Comparative Analysis of Glycemic Metrics Derived From Three Continuous Glucose Monitoring Systems. Diabetes Care 2025;48:1213-1217.
    Delia Waldenmaier, Stephanie Wehrstedt, Manuel Eichenlaub, Stefan Pleus, Manuela Link, Nina Jendrike, Sükrü Öter, Derek Brandt, Cornelia Haug, Guido Freckmann.
      
    DOI:  https://doi.org/10.2337/dci25-0071
  15. Endocrine. 2025 Sep 15.
    The therapeutic efficacy of continuous glucose monitoring in diabetes: an updated meta-analysis with meta-regression.
    Maria Ida Maiorino, Nicole Di Martino, Silvia Angelino, Antonietta Maio, Paola Caruso, Michela Petrizzo, Lorenzo Scappaticcio, Miriam Longo, Daniela Forestiere, Chiara Porcellini, Giuseppe Bellastella, Dario Giugliano, Katherine Esposito.
      
    Keywords:  Continuous glucose monitoring; HbA1c; Mean glucose; Time in range; Type 1 diabetes; Type 2 diabetes
    DOI:  https://doi.org/10.1007/s12020-025-04405-6
  16. Diabetes Technol Ther. 2025 Sep 19.
    Impact of Age at Diagnosis and Insulin Delivery Modality on Free-Living Glycemia in Type 1 Diabetes During Periods Associated with Dysglycemia: A Retrospective Analysis of the Type 1 Diabetes EXercise Initiative Study.
    Guy S Taylor, Bram Burger, Jadine H Scragg, Ollie Page, Henry Schmid, Jeremie Nsengimana, Daniel J West, James A M Shaw.
      Objective: To determine the impact of age at diagnosis and insulin delivery modality on free-living glycemia in type 1 diabetes overall and during common periods of dysglycemia (sleep, post-prandially, exercise). Research Design and Methods: Retrospective analysis of 4 weeks' free-living data from 423 people with type 1 diabetes duration >5 years within the T1DEXI Study. Participants were divided into putative age at diagnosis endotype groups: AgeDx<7 (diagnosed <7 years old); AgeDx7-12 (7-12 years); AgeDx13-30 (13-30 years); and AgeDx>30 (>30 years). Mixed-effects linear regression, fitted with a random effect for individuals and fixed effects for age at diagnosis groups, insulin delivery modality, and duration of diabetes, was used to analyze percentage time in different glycemic states over 24 h, during sleep/exercise, and for the 2 h post-prandially. Results: Participants using hybrid closed-loop systems spent more time in range (TIR: 70-180 mg/dL) than those using continuous subcutaneous insulin infusion alone (P < 0.001) or multiple daily injections (P < 0.001). TIR correlated positively with age at diagnosis and increased incrementally between diagnostic age groups overall (mean ± standard deviation, AgeDx<7: 71.4 ± 16.0%, AgeDx13-30: 73.0 ± 13.9%; AgeDx>30 78.3 ± 14.1%), during exercise, while sleeping and post-prandially. Linear effects modeling confirmed higher TIR in AgeDx>30 compared with AgeDx<7 overall (12.3%, 95% confidence interval [CI] 4.9%-19.8%, P = 0.0002), during exercise (13.7%, 95% CI 5.3%-22.0%, P = 0.0002), while sleeping (11.0%, 95% CI 3.5%-17.0%, P = 0.0043) and post-prandially (14.9%, 95%CI 5.9 to 23.9%, P = 0.0001). AgeDx13-30 spent more TIR than AgeDx<7 during exercise (8.3%, 95% CI 1.9%-14.7%, P = 0.0050). Conclusions: In addition to insulin modality, age at type 1 diabetes diagnosis independently impacts on glycemia in adults and should be factored into personalized care planning.
    Keywords:  CGM; age at diagnosis; endotypes; exercise; free-living glucose control; insulin delivery modality; postprandial; sleep
    DOI:  https://doi.org/10.1177/15209156251370942
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