bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2026–08–30
seventeen papers selected by
Mott Given
  1. Continuous Glucose Monitoring Student Experience: Responding to "CGM User-Wear Experience Fosters Empathy and Learning".
  2. Continuous Glucose Monitoring in Gestational Diabetes Mellitus: Evidence, Clinical Benefits and Remaining Challenges.
  3. Summarizing data from continuous glucose monitors using the cgmstats command.
  4. Continuous Glucose Monitoring in Gestational Diabetes: Does More Treatment Translate to Better Outcomes?
  5. Continuous glucose monitoring-derived glycemic metrics and platelet morphology in individuals with type 1 diabetes.
  6. ACTIVE-GLU: Personalised modelling of physical activity-driven glucose dynamics in type 1 diabetes under free-living conditions.
  7. Using technology to address disparities and promote healthcare equity in Type 1 Diabetes (EquiT1D) A nonrandomized clinical trial investigating solutions to low technology use.
  8. Impact of Continuous Glucose Monitoring for American Indian/Alaska Native Adults With Type 2 Diabetes Mellitus Not Using Insulin.
  9. Youth with type 2-diabetes: clinical findings at onset and impact of continuous glucose monitoring (CGM) on glycemic control and disease management.
  10. Thigh abscess following alternate-site continuous glucose monitoring sensor placement.
  11. Early-onset transient neonatal diabetes: safe use of continuous glucose monitoring and sensor-integrated insulin pump therapy.
  12. Discordantly Low HbA1c in Type 1 Diabetes: Undiagnosed G6PD Deficiency Masking Poor Glycemic Control-A Case Report.
  13. Pharmacokinetics, Clinical Efficacy, and Safety of Once-Weekly Insulin Icodec: A Structured Narrative Review (2022-2026).
  14. Causal mediation pathways in continuous postprandial glucose monitoring for type 1 diabetes patients.
  15. Early loss and progressive deterioration of glucagon responses to hypoglycemia in children with type 1 diabetes.
  16. Ready for transition, but ready for outcomes? Discordance between transition readiness and metabolic control in adolescents with type 1 diabetes.
  17. Menstrual cycle-related variations in insulin requirements and glycemic control during automated insulin delivery in adolescents with type 1 diabetes.
  1. Am J Pharm Educ. 2026 Aug 27. pii: S0002-9459(26)01442-7. [Epub ahead of print] 102084
    Continuous Glucose Monitoring Student Experience: Responding to "CGM User-Wear Experience Fosters Empathy and Learning".
    Kayleigh Moyer, Catherine B Rebitch, Karen S Pater, Amy C Donihi, Lucas A Berenbrok.
      
    Keywords:  Continuous Glucose Monitors; Diabetes Education; User-wear Experience
    DOI:  https://doi.org/10.1016/j.ajpe.2026.102084
  2. Diabetes Ther. 2026 Aug 22.
    Continuous Glucose Monitoring in Gestational Diabetes Mellitus: Evidence, Clinical Benefits and Remaining Challenges.
    Dorota Bomba-Opoń, Katarzyna Cypryk, Krzysztof Czajkowski, Ewa Wender-Ożegowska, Dorota Zozulińska-Ziółkiewicz.
      Use of continuous glucose monitoring (CGM) technology has contributed to significant improvements in the care of women with pregestational type 1 diabetes (T1D), including for preconception management of glycemia. Increasingly, it is being recommended for use in women with type 2 diabetes (T2D) to achieve similar goals. Gestational diabetes mellitus (GDM) is a complication of pregnancy in women without dysglycemia prior to conception, and the use of CGM in this group is limited and is now only beginning to accumulate evidence. This growing evidence base indicates that the use of CGM can be associated with reductions in adverse pregnancy outcomes for women with GDM and their infants. These include reduced large for gestational age (LGA) offspring, fewer infants with macrosomia, reduced admissions to neonatal intensive care units (NICU), and fewer Cesarean section deliveries. Use of CGM has also been associated with earlier prediction of GDM risk and earlier detection of GDM, potentially enabling earlier glycemic management. The range of CGM-derived metrics that can be applied in the management of women with GDM includes sensor-detected average glucose, time in range (TIR), time above range (TAR), time below range (TBR) and glycemic variability (GV). However, to date, no specific CGM targets for these metrics have been agreed. In this narrative review, we identify the clinical evidence that supports the use of CGM and CGM metrics of glucose control in women with GDM and indicate CGM targets that may have value in this important group. We also provide practical insights on how CGM devices can be used to understand daily and weekly glucose trends, thereby optimising glycemia during and after a pregnancy with GDM.
    Keywords:  CGM; Continuous glucose monitoring; GDM; Gestational diabetes mellitus; Pregnancy outcomes; Review
    DOI:  https://doi.org/10.1007/s13300-026-01906-z
  3. Stata J. 2026 Jun;26(2): 274-290
    Summarizing data from continuous glucose monitors using the cgmstats command.
    Natalie Daya Malek, Dan Wang, Sui Zhang, Michael Fang, Amelia Wallace, Scott Zeger, Elizabeth Selvin.
      In this article, we present the cgmstats package for the analysis of continuous glucose monitoring (CGM) data. The use of wearable CGMs is growing rapidly. The latest generation of CGM systems do not require fingerstick calibration, are minimally invasive, and are frequently used in research studies. CGM sensors are typically worn for up to 2 weeks and record interstitial glucose measurements every minute to every 15 minutes, depending on the sensor used. CGM systems generate hundreds of measurements per day and thousands of measurements in one person over a single wear. There is a need for tools that allow researchers to efficiently organize and summarize the wealth of data on glucose patterns produced by CGM systems. The cgmstats package generates CGM summary measures for data from a variety of CGM systems and allows the user to flexibly define ranges and generate data visualizations. In this article, we provide an overview of the cgmstats package and examples of its use. The cgmstats package supports rigorous and reproducible analyses of CGM data.
    Keywords:  cgmstats; continuous glucose monitoring metrics; glucose profile
    DOI:  https://doi.org/10.1177/1536867x261450271
  4. Diabetes Obes Metab. 2026 Aug 25.
    Continuous Glucose Monitoring in Gestational Diabetes: Does More Treatment Translate to Better Outcomes?
    Jie Liao, Qinqin Yuan, Yanmei Xia.
      
    DOI:  https://doi.org/10.1111/dom.71282
  5. Pol Arch Intern Med. 2026 Aug 25. pii: 17373. [Epub ahead of print]136(7-8):
    Continuous glucose monitoring-derived glycemic metrics and platelet morphology in individuals with type 1 diabetes.
    Ramzi A Ajjan, Robert F Storey.
      
    DOI:  https://doi.org/10.20452/pamw.17373
  6. Digit Health. 2026 Jan-Dec;12:12 20552076261456506
    ACTIVE-GLU: Personalised modelling of physical activity-driven glucose dynamics in type 1 diabetes under free-living conditions.
    Ahmad Bilal, Hood Thabit, Paul W Nutter, Simon Harper.
       Objective: Physical activity (PA) lowers blood glucose (BG) levels in individuals with Type 1 Diabetes Mellitus (T1DM), with effects varying by intensity and duration. Predicting BG fluctuations under free-living conditions, beyond structured exercise, helps reduce hypoglycaemia risk. This study aimed to model and predict BG responses across varying PA levels using personalised, activity-informed temporal patterns derived from continuous glucose monitoring (CGM) data.
    Methods: Fourteen adults with T1DM were monitored under free-living conditions using Garmin smartwatches for PA tracking and CGM devices for BG measurement. PA was quantified using step count and maxMotion intensity, and categorised into four levels: low, medium, high, and very high. A 10-day rolling window (moving average) was applied to each participant's data to construct the personalised ACTIVE-GLU model, which estimates mean BG change at 15-minute intervals following PA.
    Results: The ACTIVE-GLU model accurately predicted BG changes across all PA intensities. The lowest average accuracy (81.67%) was observed under low PA, while the highest prediction error occurred during very high PA (MAE = 0.44 mmol/L, RMSE = 0.57 mmol/L, mean bound deviation = 0.38 mmol/L). Bland-Altman analysis confirmed close agreement between predicted and observed BG values, with negligible bias across intensity levels.
    Conclusion: In this exploratory cohort study, quantifying daily PA within a personalised temporal framework enables accurate prediction of BG responses in T1DM under real-world conditions. By incorporating PA intensity into BG dynamics, ACTIVE-GLU provides a personalised, PA-aware framework that may support interpretation of BG trends and inform future decision-support strategies. Future work will validate the model using virtual participants to simulate adaptive dosing interventions.
    Keywords:  blood glucose prediction; continuous glucose monitoring; digital health; free-living conditions; glucose dynamics; personalised modelling; physical activity; rolling window; type 1 diabetes; wearable devices
    DOI:  https://doi.org/10.1177/20552076261456506
  7. J Clin Transl Endocrinol. 2026 Nov;46 100453
    Using technology to address disparities and promote healthcare equity in Type 1 Diabetes (EquiT1D) A nonrandomized clinical trial investigating solutions to low technology use.
    Elizabeth A Murphy, Wen Wan, Neda Laiteerapong, Monica E Peek, Elbert S Huang, Rabia S Ali, Zachary J Schreckenberger, Harshavardhan Nalam, Celeste C Thomas.
      Although diabetic ketoacidosis (DKA) is more frequent among racial and ethnic minority populations, continuous glucose monitoring (CGM) use is lower in such groups. We sought to determine if care navigation support increases CGM utilization in patients with recurrent admissions for DKA. Using Technology to Address Disparities and Promote Healthcare Equity in Type 1 Diabetes (EquiT1D) is a prospective, single-arm study conducted at an academic medical center. Adult patients with type 1 diabetes (T1D) at high risk for DKA were recruited for participation. From November 2020 to April 2022, patients were consented to participate in an intervention which involved regular contact and care navigation to address barriers to CGM utilization. The primary study outcome was CGM utilization (percentage of days with sensor data). At 12 months, navigation support was associated with an increase in model-estimated mean (SE) CGM utilization from 17.5% (6.8%) at baseline to 51.4% (6.9%) at 12 months (P < 0.001). This study suggests that navigation support may be an effective way to increase CGM utilization among patients at high risk for DKA recurrence. Additional studies are needed to address barriers to CGM utilization. Trial Registration:clinicaltrials.gov, NCT06899984 (https://clinicaltrials.gov/study/NCT06899984?term=equit1d&rank=1#study-overview).
    Keywords:  Continuous glucose monitoring; Diabetic ketoacidosis; Patient navigation; Type 1 diabetes
    DOI:  https://doi.org/10.1016/j.jcte.2026.100453
  8. Fed Pract. 2025 Nov;42(Suppl6): S6-S11
    Impact of Continuous Glucose Monitoring for American Indian/Alaska Native Adults With Type 2 Diabetes Mellitus Not Using Insulin.
    Chantelle Robert, Ryan G Pett.
       Background: American Indian and Alaskan Native (AI/AN) populations have the highest prevalence of type 2 diabetes mellitus (T2DM) in the United States. Continuous glucose monitors (CGMs) have revolutionized diabetes management, but their impact on AI/AN individuals with T2DM who are not insulin dependent remains understudied.
    Methods: A retrospective observational study was conducted using deidentified electronic health records from an outpatient Indian Health Service clinic between 2019 and 2024. Ninety-three AI/AN patients with non-insulin-dependent T2DM who used CGMs for ≥ 1 year were included. Hemoglobin A1c (HbA1c), blood pressure (BP), weight, low-density lipoprotein cholesterol, and estimated glomerular filtration rate were compared at baseline and 1 year after CGM initiation without a control group.
    Results: The mean age of participants was 55 years and 60% were female. Mean (SD) HbA1c significantly decreased from 9.5% (2.4%) at baseline to 7.6% (2.2%) at 1 year (95% CI, -2.35 to -1.37; P < .001, paired t test). Higher baseline HbA1c was associated with greater HbA1c reduction over 1 year (β = -0.576; P < .001, linear regression), explaining 34.6% of the variance in change. Mean (SD) systolic BP decreased by 4.9 (17) mm Hg (95% CI, -8.6 to -1.1; P = .01, paired t test), but diastolic BP and other variables showed no significant changes.
    Conclusions: CGM use in an AI/AN population was significantly associated with improved glycemic control in patients with non- insulin-dependent T2DM. The effect was more pronounced in patients with higher baseline HbA1c levels, suggesting CGMs could be beneficial for patients at greatest risk.
    DOI:  https://doi.org/10.12788/fp.0644
  9. J Pediatr Endocrinol Metab. 2026 Aug 26.
    Youth with type 2-diabetes: clinical findings at onset and impact of continuous glucose monitoring (CGM) on glycemic control and disease management.
    Rosa Thielemann, Lorenz Greifoner, Marlene Dieke, Nicole Kuplin, Kerstin Placzek, Andreas Wienke, Susann Weihrauch-Blüher.
       OBJECTIVES: The global obesity pandemic is associated with a higher prevalence of youth-onset type 2 diabetes (T2D). Continuous glucose monitoring (CGM) is established in type 1 diabetes, however, evidence regarding its impact in pediatric T2D is limited. This study has analyzed (a) clinical and metabolic characteristics in adolescents at T2D onset and (b) the impact of CGM on glycemic control, patient satisfaction and disease management in youths with T2D.
    METHODS: a) Clinical and biochemical parameters at diagnosis were assessed in adolescents with T2D. b) The impact of 8 weeks of CGM on HbA1c, time in range (TIR), markers of the Metabolic Syndrome (MetS), lifestyle and treatment satisfaction were exploratively examined in a subgroup. HbA1c was subsequently monitored for 12 months.
    RESULTS: Study a): Between 2018 and 2024, 24 adolescents were diagnosed with T2D (25 % female; 14 ± 3 years; HbA1c: 9.9 ± 2.9 %). Symptoms included polydipsia (45.8 %), polyuria (33.3 %), features of the MetS (100 %), ketoacidosis (16.7 %). Study b): 11 patients participated in the CGM study (14 ± 3 years). After 8 weeks, HbA1c significantly decreased from 6.9 ± 1.1 to 6.4 ± 0.7 %, TIR increased from 78.5 ± 30.3 % to 87.1 ± 17.6 %. More frequent glucose monitoring was reported by 91 %, more appropriate responses to glucose fluctuations by 82 %, improved quality of life and dietary habits by 73 %. Ninety one percent of participants preferred CGM over capillary testing. HbA1c remained stable at 6 months (6.4 ± 0.9 %) but increased to 6.9 ± 1.8 % at 12 months after discontinuation of CGM.
    CONCLUSIONS: In youth-onset T2D, CGM may improve glycemic outcomes and disease management/quality of life. Larger studies are required.
    Keywords:  continuous glucose monitoring (CGM); glycemic control; metabolic syndrome; quality of life; type 2 diabetes (T2D); youths
    DOI:  https://doi.org/10.1515/jpem-2026-0344
  10. Am J Health Syst Pharm. 2026 Aug 28. pii: zxag252. [Epub ahead of print]
    Thigh abscess following alternate-site continuous glucose monitoring sensor placement.
    Kristy M Shaeer, Raechel T White, Benjamin Lord, Tina L Pham, Sarah Kimble, Erin L Reynolds, Jennifer Teeters, Kevin Cowart.
       PURPOSE: To describe a methicillin-susceptible Staphylococcus aureus (MSSA) thigh abscess following alternate-site placement of a continuous glucose monitor (CGM) sensor and to highlight safety considerations associated with off-label device use in patients with poorly controlled diabetes.
    SUMMARY: A 49-year-old man with uncontrolled type 2 diabetes (glycated hemoglobin, 11.3%) was referred to an ambulatory care pharmacist for diabetes management. The patient placed the sensor on his upper thigh due to prior dislodgement from the upper arm. Three days later, the patient presented with a painful, erythematous, fluctuant 4.5 x 5 cm abscess at the sensor insertion site. Initial incision and drainage (I&D) was performed and oral sulfamethoxazole/trimethoprim was prescribed. Four days later, he returned with worsening pain and impaired ambulation requiring repeat I&D. Wound cultures grew MSSA. Management additionally included wound packing, topical mupirocin, and continuation of sulfamethoxazole/trimethoprim, with clinical improvement noted after the second I&D procedure. Cutaneous complications with CGM use are typically mild, infrequent, and most often involve contact or irritant dermatitis rather than infection. Reports of CGM-associated skin infections are rare, and none have been reported following sensor placement at unapproved insertion sites.
    CONCLUSION: This case underscores the potential for a skin and soft tissue infection following off-label CGM placement, especially in patients with uncontrolled hyperglycemia. Pharmacists play a critical role in reinforcing appropriate device use, identifying early signs of infection, and coordinating interdisciplinary care to mitigate device-related complications.
    Keywords:  abscess; adverse event; continuous glucose monitoring; diabetes; skin infection
    DOI:  https://doi.org/10.1093/ajhp/zxag252
  11. Acta Diabetol. 2026 Aug 27.
    Early-onset transient neonatal diabetes: safe use of continuous glucose monitoring and sensor-integrated insulin pump therapy.
    Carolina Jesus E Sá, Clara Picão de Carvalho, Rita Ribeiro Martins, Sara Martins, Ana Raquel Henriques, Brígida Robalo, Carla Pereira, Lurdes Sampaio.
      
    Keywords:  Blood Glucose Self-Monitoring; Insulin Infusion Systems; Neonatal Diabetes
    DOI:  https://doi.org/10.1007/s00592-026-02789-z
  12. Case Rep Endocrinol. 2026 ;2026 3927494
    Discordantly Low HbA1c in Type 1 Diabetes: Undiagnosed G6PD Deficiency Masking Poor Glycemic Control-A Case Report.
    Javeria Khan, Irfan Khan, Muhammad Maaz Bin Zahid, Hoor Qazi, Ayesha Nasir.
       Background: Glycated hemoglobin (HbA1c) is a widely used biomarker for assessing long-term glycemic control in patients suffering from diabetes mellitus. However, certain hematologic conditions, such as hemolytic disorders, can produce misleadingly low HbA1c values, potentially masking poor glycemic control and leading to mismanagement of the patient. This case represents a rare but clinically significant scenario, where G6PD deficiency leads to spuriously low HbA1c level, emphasizing the need for alternative glycemic markers.
    Case Presentation: We report the case of a 17-year-old male who presented with classic symptoms of hyperglycemia and was diagnosed with type 1 diabetes mellitus (T1DM) based on clinical features, elevated blood glucose, high HbA1c (>14%), and positive glutamic acid decarboxylase (GAD) antibodies. One month after initiating basal-bolus insulin therapy, his follow-up HbA1c unexpectedly dropped to 3%, despite continuous glucose monitoring (CGM) showing incomplete control of glucose level. Work-up for nonglycemic factors, specifically those affecting the red blood cells (RBCs) revealed normal hemoglobin electrophoresis but confirmed glucose-6-phosphate dehydrogenase (G6PD) deficiency. The intravascular hemolysis associated with G6PD deficiency likely shortened RBC lifespan, producing spuriously low HbA1c values. Fructosamine testing was consistent with ongoing hyperglycemia.
    Conclusion: This case underscores the importance of considering alternative glycemic markers, such as fructosamine or CGM metrics, when discordance exists between HbA1c and clinical or CGM findings. Early recognition of G6PD deficiency in diabetic patients with such unusual presentation is critical to ensure accurate monitoring and to guide patient education on avoiding oxidative stress triggers.
    Keywords:  G6PD deficiency; HbA1c; case report; continuous glucose monitoring; fructosamine; hemolysis; type 1 diabetes mellitus
    DOI:  https://doi.org/10.1155/crie/3927494
  13. Cureus. 2026 Jul;18(7): e113509
    Pharmacokinetics, Clinical Efficacy, and Safety of Once-Weekly Insulin Icodec: A Structured Narrative Review (2022-2026).
    Yash Patel, Riddhi Patel, Rutvik Raval.
      Suboptimal adherence to daily basal insulin remains a significant barrier to achieving glycemic targets in patients with diabetes mellitus. Insulin icodec is a novel, once-weekly basal insulin analog designed to reduce injection burden and improve treatment compliance. This review evaluates the pharmacological profile, clinical efficacy, and safety of insulin icodec by synthesizing data from the comprehensive Phase 3 ONWARDS clinical trial program. A structured narrative review of recent literature (2022-2026) was conducted, focusing on randomized controlled trials (RCTs), pharmacokinetic studies, and meta-analyses comparing insulin icodec with daily basal insulins (glargine U-100 and degludec). Insulin icodec achieves a half-life of approximately 196 hours through reversible binding to albumin, enabling a once-weekly dosing interval. In patients with type 2 diabetes (T2D), the ONWARDS 1-5 trials demonstrated that icodec provides non-inferior, and in several cohorts, superior, reductions in glycated hemoglobin (HbA1c) compared to daily basal insulins, with a comparable risk of clinically significant or severe hypoglycemia. Time-in-range (TIR) metrics were significantly improved. However, in patients with type 1 diabetes (T1D) (ONWARDS 6), while glycemic efficacy was non-inferior, icodec was associated with a statistically significant increase in the risk of severe or clinically significant hypoglycemia compared to insulin degludec. Insulin icodec may represent an important advancement in the management of T2D, offering improved glycemic control with a substantially reduced injection burden. While its use in T1D requires cautious consideration due to hypoglycemia risks, icodec has the potential to become a preferred standard of care for insulin-requiring T2D globally.
    Keywords:  continuous glucose monitoring; glycemic control; hypoglycemia; insulin icodec; medication adherence; once-weekly basal insulin; pharmacokinetics; type 2 diabetes mellitus
    DOI:  https://doi.org/10.7759/cureus.113509
  14. NPJ Metab Health Dis. 2026 Aug 27. pii: 35. [Epub ahead of print]4(1):
    Causal mediation pathways in continuous postprandial glucose monitoring for type 1 diabetes patients.
    Spencer Hilligoss, Annie Qu.
      Managing postprandial glucose in Type 1 Diabetes Mellitus (T1DM) requires understanding how carbohydrate intake affects glucose through both direct pathways and insulin-mediated compensation. Standard analyses treat insulin as a confounder rather than a mediator, obscuring these distinct causal channels and patient-level heterogeneity in carbohydrate response. Using meal-centered continuous glucose monitoring windows from twelve adults in the OhioT1DM cohorts, we apply causal mediation analysis to decompose the total effect of carbohydrate intake on glucose change into average direct (ADE), insulin-mediated (ACME), and total effects, by meal type and across outcome quantiles. To adjust for pre-meal confounding, we introduce a Causally-constrained Linear Autoencoder that learns low-dimensional representations improving adjustment for measured pre-meal state. Across cohorts, carbohydrate intake raises postprandial glucose chiefly through a large direct effect that insulin only partially offsets. The prespecified primary endpoint, the pooled ADE of a + 30 g contrast at two h, is large and highly significant, robust to multiple-testing correction, and replicates in the independent DiaTrend cohort (54 adults); the insulin-mediated effect is comparatively small. Meal- and quantile-specific signals, including greater dinner-time excursions, do not survive false-discovery-rate correction and are reported as hypothesis-generating. These results localize where postprandial insulin dosing may be refined.
    DOI:  https://doi.org/10.1038/s44324-026-00127-z
  15. BMJ Open Diabetes Res Care. 2026 Aug 26. pii: e005959. [Epub ahead of print]14(4):
    Early loss and progressive deterioration of glucagon responses to hypoglycemia in children with type 1 diabetes.
    Antoine Harvengt, Maude Beckers, Ilektra Iakovidou, Anaïs Maure, Zain Syed, Laure Boutsen, Dominique Beckers, Philippe A Lysy.
       INTRODUCTION: Impaired glucagon counterregulation is a major contributor to hypoglycemia risk in type 1 diabetes (T1D). While well described in adults, the timing, trajectory, and determinants of glucagon dysfunction in children remain poorly defined. Our objective was to characterize the evolution of glucagon secretion during insulin-induced hypoglycemia in children with newly diagnosed T1D and to identify biomarkers of counterregulatory failure.
    RESEARCH DESIGN AND METHODS: GLUcagon REsponse to hypoglycemia in children and adolescents with new-onset type 1 DIAbetes (GLUREDIA) - Work Package (WP) 1 is a prospective, multicenter longitudinal study including 22 children and adolescents (aged 2-17 years) with newly diagnosed T1D and eight healthy first-degree relatives. Participants underwent standardized insulin-induced hypoglycemia tests (IIHTs). In patients with T1D, IIHTs were performed at diagnosis and at 6, 12, and 18 months. Plasma glucagon and counterregulatory hormones were measured at baseline and during hypoglycemia. Continuous glucose monitoring (CGM) metrics and circulating biomarkers were analyzed using longitudinal mixed models and regression analyses.
    RESULTS: In healthy participants, IIHT elicited a robust physiological increase in glucagon during hypoglycemia (p<0.001). In contrast, children with T1D showed no significant glucagon response despite deeper hypoglycemia. Longitudinally, glucagon responsiveness was absent at diagnosis, transiently improved at 6 months (p=0.04), absent at 12 months, and paradoxically suppressed at 18 months (p=0.02). Basal glucagon levels remained stable over time. Glucagon responses correlated positively with CGM time-in-range (70-180 mg/dL) and negatively with glycemic variability and hypoglycemia frequency. A CGM-based logistic model integrating these metrics predicted impaired glucagon responses with good discrimination (area under the curve 0.79). Circulating glucose-dependent insulinotropic polypeptide, glucagon-like peptide-1, tumor necrosis factor-α, and interferon-γ correlated positively with glucagon secretion, whereas partial remission status did not.
    CONCLUSIONS: Glucagon counterregulation is profoundly impaired early in pediatric T1D and deteriorates dynamically within the first 18 months after diagnosis. Glycemic instability and recurrent hypoglycemia are key determinants of α-cell dysfunction. CGM-derived metrics may serve as non-invasive surrogates of impaired counterregulation and support early risk stratification for hypoglycemia in children with T1D.
    TRIAL REGISTRATION NUMBER: NCT06770621.
    Keywords:  Biomarkers; Continuous Glucose Monitoring; Counterregulation; Glucagon
    DOI:  https://doi.org/10.1136/bmjdrc-2026-005959
  16. J Pediatr Endocrinol Metab. 2026 Aug 26.
    Ready for transition, but ready for outcomes? Discordance between transition readiness and metabolic control in adolescents with type 1 diabetes.
    Ayşe Yaşar, Fatma Dursun, Esma Ebru Altun, Heves Kırmızıbekmez.
       OBJECTIVES: Transition from pediatric to adult care is a critical period for adolescents with type 1 diabetes mellitus (T1DM). This study aimed to evaluate transition readiness and its association with glycemic outcomes, and to analyze factors affecting readiness in adolescents with T1DM.
    METHODS: This cross-sectional study included 75 adolescents with T1DM aged 17-21 years. Transition readiness was assessed using a diabetes-adapted 23-item questionnaire based on the Transition Readiness Assessment Questionnaire (TRAQ). Clinical and demographic data were collected retrospectively. Associations between transition readiness scores and HbA1c levels, categorized using two clinically relevant thresholds, as well as demographic and clinical variables, were analyzed.
    RESULTS: The mean transition readiness score was 83.91 ± 14.46. Higher scores were observed in communication and self-management domains, whereas lower scores were noted in healthcare navigation and transition-specific readiness. Transition readiness scores were not associated with HbA1c levels across different classifications. Diabetes duration was positively correlated with readiness scores (r=0.311, p=0.007), while no significant association was found with age or gender. Technology use (continuous glucose monitoring and insulin pump) was not associated with transition readiness.
    CONCLUSIONS: Transition readiness in adolescents with T1DM appears to be a multidimensional construct that is not directly reflected by glycemic control. This discrepancy between perceived readiness and clinical outcomes suggests that transition assessments should extend beyond subjective measures and incorporate broader functional domains, including healthcare navigation and real-life independence.
    Keywords:  adolescents; glycemic control; transition readiness; transition to adult care
    DOI:  https://doi.org/10.1515/jpem-2026-0293
  17. J Pediatr Endocrinol Metab. 2026 Aug 31.
    Menstrual cycle-related variations in insulin requirements and glycemic control during automated insulin delivery in adolescents with type 1 diabetes.
    Nora Struckmeyer, Sarah Landsberg, Torben Biester, Rodica Mia Doelle, Ann-Kristin Frerking, Kerstin Kapitzke, Niclas Knottnerus-Meyer, Mareike Niemeyer, Rebecca Toenne, Thekla von dem Berge, Zlata Vukadinovic-Nikolic, Jantje Weiskorn, Olga Kordonouri, Felix Reschke.
       OBJECTIVES: Data on menstrual cycle-related metabolic variability in adolescents with type 1 diabetes (T1D) using automated insulin delivery (AID) systems are scarce. We aimed to quantify cycle-dependent differences in insulin requirements and glycemic outcomes in this population.
    METHODS: In this retrospective observational cohort study, adolescents with T1D aged 12.0-17.9 years who were at least 1 year postmenarche and had used AID for ≥6 months were included. Menstrual cycles were tracked using smartphone applications, and nine complete cycles per participant were analyzed. Insulin delivery and continuous glucose monitoring data were extracted from Glooko. Outcomes included total daily insulin dose (TDD), time in range (TIR), time above range (TAR), time below range (TBR), mean glucose, glucose coefficient of variation (CV), and recorded carbohydrate intake. Linear mixed-effects models were used.
    RESULTS: Fifty-one adolescents contributed 459 menstrual cycles. Mean age was 14.7 ± 1.8 years, and median HbA1c was 7.2 % (interquartile range 6.8-7.5 %). TDD was higher during the luteal than the follicular phase (1.05 vs. 0.95 U/kg/day; mean difference +0.10 U/kg/day, 95 % CI 0.05-0.15; p<0.001). The luteal phase was associated with reduced TIR (-6.3 %, p=0.001), increased TAR (+5.5 %, p=0.01), higher mean glucose (+12.5 mg/dL, p=0.03), and higher CV (39.4 vs. 35.0 %, p=0.03). TBR and carbohydrate intake did not differ significantly.
    CONCLUSIONS: In adolescents with T1D who menstruate and use AID systems, insulin requirements and glycemic control vary across the menstrual cycle, with increased insulin demand and hyperglycemia during the luteal phase. These findings highlight clinically relevant cycle-related metabolic variability despite the use of AID.
    Keywords:  continuous glucose monitoring; glucose variability; insulin sensitivity; luteal phase; puberty
    DOI:  https://doi.org/10.1515/jpem-2026-0309
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