bims-glumda 2026-11-01 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2026–11–01
twenty-two papers selected by
Mott Given

Performance and Safety of a Continuous Glucose Monitoring System in Pregnant Women With Gestational Diabetes Mellitus: A Multicenter, Open-Label Trial.
Postpartum glycemic trends among people with gestational diabetes using continuous glucose monitoring.
Achieving HbA1c Reduction in Diabetes Management : A Retrospective Comparison of Glucose Monitoring Methods.
Continuous glucose monitoring reveals thyroid feedback-related residual glycemic variability and hypoglycemia during inpatient glucose optimization in euthyroid adults with type 2 diabetes: a CGM-based observational study.
Type 2 Diabetes and Continuous Glucose Monitoring: A Pilot Cross-Sectional Study of Medication Adherence and Self-Management Behaviors.
Fuzzy Fault Detection and Band-Conditioned Data Quality Assessment for Sensor Streams: A Continuous Glucose Monitoring Case Study.
Piloting a Professional Continuous Glucose Monitoring Program in a Safety-Net Diabetes Clinic: A Quality Improvement Study.
Changes in CGM-Derived Glycemic Metrics and Triglyceride-Glucose Index During Ramadan in Adults With Type 2 Diabetes Using Real-Time Continuous Glucose Monitoring.
Six-month real-world glycemic improvement after Smart MDI system in type 1 diabetes.
How CGM Boosts Self-Efficacy, Engagement With Self-Management, and Clinical Outcomes in Adults With Type 2 Diabetes: A Mixed-Methods Study.
Assessing reproducibility of CGM-derived postprandial phenotypes without discordance-based exclusion.
A Comparative Analysis Between Original and Updated Glucose Management Indicator and Glycated Haemoglobin Across Continuous Glucose Monitoring Sensors in Type 1 Diabetes.
Closing the Gap: Strategies for Broader Adoption and Use of Continuous Glucose Monitors Among Children and Adolescents With Type 1 Diabetes.
Time in Range as a Marker of Concurrent Glycemic and Lipid Improvement in Adults with Type 2 Diabetes: A Real-World Retrospective Pre-Post Study.
Glycemic Dynamics and Management Strategies in Individuals With Type 1 Diabetes During Ramadan: A Continuous Glucose Monitoring-Based Narrative Review.
Behavior Modifications From CUT-DM, Including Lifestyle Modification and Self-Efficacy.
Continuous Glucose Monitoring Methods Evaluation and Recommendations for Reporting Guidelines.
Technology use in youth with type 1 diabetes and language of care other than English.
Real-World Evaluation of a Near-Infrared Spectroscopy-based Noninvasive Glucose Monitoring Device in Adults With Type 2 Diabetes.
Adaptive personalization for wearable non-invasive continuous glucose sensors.
Considerations for Swimmers with Type 1 Diabetes: A Narrative Review.
GlucoSense: early diabetes risk assessment via fusion of human activity recognition and glucose prediction.

J Diabetes Sci Technol. 2026 Oct 25. 19322968261489294

Performance and Safety of a Continuous Glucose Monitoring System in Pregnant Women With Gestational Diabetes Mellitus: A Multicenter, Open-Label Trial.

Jie Shen, Huiling Shang, Weiwei Zhu, Novihoho Abra Maudline.

   BACKGROUND: Continuous glucose monitoring (CGM) is increasingly important in pregnancies complicated by diabetes, where strict glycemic control is essential to prevent adverse outcomes such as fetal macrosomia and preterm birth. In gestational diabetes mellitus (GDM)-which accounts for most of the diabetes in pregnancy-maternal hyperglycemia is the primary clinical concern. This study evaluated the accuracy and safety of a factory-calibrated CGM system over 15 days in pregnant women with diabetes, with most having GDM.
METHODS: This prospective, multicenter, open-label trial enrolled 60 pregnant women (95% GDM, 3.3% type 1 diabetes, 1.7% type 2 diabetes). Each participant wore 2 sensors simultaneously, 1 on each upper arm, for up to 15 days. Venous blood glucose reference values were obtained using a Biosen C-line GP+ analyzer. Accuracy was assessed by 20/20% agreement rate, Diabetes Technology Society (DTS) error grid analysis, and mean absolute relative difference (MARD). Safety and usability were also evaluated.
RESULTS: A total of 2901 matched CGM-reference pairs were analyzed (1451 from left-arm sensors, 1450 from right-arm sensors). The 20/20% agreement rate was 96.6% (95% CI, 95.6%-97.5%) for the left arm and 96.8% (95% CI, 95.8%-97.7%) for the right arm. The overall MARD was 7.72% (95% CI, 7.33%-8.11%) for the left arm and 7.66% (95% CI, 7.27%-8.05%) for the right arm.
CONCLUSION: The CGM system demonstrated accurate, stable, and safe glucose monitoring over 15 days in pregnant women with predominantly GDM. Its strong performance supports its utility as a reliable tool for glucose monitoring during pregnancy.

Keywords:  accuracy; clinical trial; continuous glucose monitoring; gestational diabetes; pregnancy; safety

DOI:  https://doi.org/10.1177/19322968261489294
Am J Obstet Gynecol MFM. 2026 Oct 28. pii: S2589-9333(26)00271-5. [Epub ahead of print] 102172

Postpartum glycemic trends among people with gestational diabetes using continuous glucose monitoring.

Alyssa R Hersh, Alexandra C Gallagher, Lucy Ward, Christian Huertas-Pagán, Monica Rincon, Amy M Valent.

   BACKGROUND: During the immediate postpartum period, glycemic changes among persons with gestational diabetes (GDM) have not been well characterized.
OBJECTIVE: Using continuous glucose monitoring (CGM) data, we sought to explore the differences in postpartum glycemic trends among people with GDM by patient-level characteristics.
STUDY DESIGN: This study was an exploratory secondary analysis of pregnant people with GDM randomized to using CGM versus capillary blood glucose during pregnancy. Participants without CGM data in the immediate postpartum period were excluded from analysis. Our primary outcome was mean glucose by hour from delivery through the first 48 hours postpartum. We performed additional analyses stratified by GDM type, mode of delivery and time in range during pregnancy (≥90% TIR, 63-140mg/dL) to determine differences in postpartum glycemia among these cohorts.
RESULTS: Of the 111 participants in the overall trial, we included 79 participants with postpartum data in this secondary analysis, of which 22.8% had A1GDM and 77.2% had A2GDM. Overall, there was a slight downward trend in glucose values over the first 48 hours post-delivery. Participants with A1GDM had lower mean glucose by 48 hours compared to those with A2GDM, as did participants with high percent TIR (≥90%) compared with lower percent TIR during pregnancy. Participants with higher gestational mean glucose and percent time-above-range (TAR) had higher mean glucose during the 48 hours post-delivery compared to those with lower gestational mean glucose and time-above-range.
CONCLUSION: We found that postpartum mean glucose trended downward after delivery and varied by multiple pregnancy and delivery characteristics. Future studies should assess whether differences in postpartum glycemic parameters are associated with clinically relevant outcomes.

Keywords:  cesarean delivery; continuous glucose monitoring; gestational diabetes mellitus; glucose tolerance test; obstetrics; pregnancy

DOI:  https://doi.org/10.1016/j.ajogmf.2026.102172
Dela J Public Health. 2026 Oct;12(4): 38-43

Achieving HbA1c Reduction in Diabetes Management : A Retrospective Comparison of Glucose Monitoring Methods.

Eshita Sharmin, Cameron Golden, Ejaz Mahmood.

Objective: To evaluate the effectiveness of continuous glucose monitoring (CGM) compared to point-of-care (POC) glucose testing in reducing HbA1c among adults with diabetes.
Methods: This single-center, retrospective cohort study included adult patients with type 1 or type 2 diabetes attending Bayhealth Sussex Endocrinology Clinic between January 1, 2023 and December 31, 2024. Controls were POC testers, while the intervention group was CGM users. Data was extracted from Epic electronic medical records via SlicerDicer and chart review. Exclusion criteria included pregnancy, terminal illnesses (i.e. end-stage renal disease, cancer), and medications affecting CGM accuracy (i.e. hydroxyurea, ascorbic acid). The primary endpoint was change in HbA1c from baseline to 3- and 6-month follow-ups. Secondary endpoints included estimated average glucose (eAG) and CGM metrics (time sensor active, time in range (TIR), time above range (TAR)).
Results: Of 90 patients, 63 used CGM and 27 were POC testers. Baseline characteristics were similar between the groups, though CGM patients had higher comorbidity burden and insulin use. CGM users achieved significantly greater HbA1c reduction than POC testers (-1.8% vs. -1%; p < 0.001). Improvements were most pronounced among patients with baseline HbA1c ≥9% (time sensor active of -2 with p = 0.227, TIR 13.4 with p = 0.43, high TAR -8.7 with p = 0.344, very high TAR 1.9 with p = 0.455) but significant among baseline HbA1c 7-9% (time sensor active of -1.5, TIR -3.6, high TAR 1.9, very high TAR -1, with p < 0.001 for all metrics). CGM compliance maintained high (81.9% at 3 months vs. 75.4% at 6 months, p = 0.021) with notable improvement of time-in-range (TIR) (1.8, p = 0.002).
Conclusion: CGM use significantly improves glycemic outcomes for patients at-risk of developing HbA1c >9%, which supports broader CGM access for all patients with diabetes.

DOI: https://doi.org/10.32481/djph.2026.10.08
BMC Endocr Disord. 2026 Jul 28. pii: 333. [Epub ahead of print]26(1):

Continuous glucose monitoring reveals thyroid feedback-related residual glycemic variability and hypoglycemia during inpatient glucose optimization in euthyroid adults with type 2 diabetes: a CGM-based observational study.

Miriayi Alimujiang, Lei Zhang, Wenwen Chen, Shuai Ma, Jiejie Zhao, Qiyu Chen, Dilidaer Muhanhali, Peng Yu, Yan Ling.

   BACKGROUND: Continuous glucose monitoring (CGM) captures short-term glucose excursions and hypoglycemia beyond what HbA1c reflects, but endocrine traits that shape inpatient glycemic variability (GV) during therapy intensification are poorly defined. We evaluated whether thyroid feedback indices that proxy central thyroid hormone sensitivity are associated with CGM-derived residual GV and hypoglycemia in euthyroid inpatients with type 2 diabetes.
METHODS: We conducted a retrospective cohort study of 224 euthyroid adults with type 2 diabetes admitted for structured glucose optimization who wore blinded CGM for at least 6 consecutive days. Baseline FT3, FT4 and TSH were used to derive thyroid feedback indices (TFQI, TSHi and TT4RI). Daily CGM metrics were computed; Day 6 was prespecified as the primary later-inpatient analysis day at the cohort level. High GV was defined as Day 6 MAGE ≥ 3.9 mmol/L, and hypoglycemia as ≥ 2 consecutive readings < 3.9 mmol/L. Associations were tested using linear regression (including day-specific models) and multivariable logistic regression with sequential adjustment, including mean glucose and clinical covariates; post hoc sensitivity analyses additionally adjusted for available discharge medication classes.
RESULTS: Overall CGM profiles improved from Day 2 to Day 6 (TIR: 62 ± 25% to 84 ± 15%; MAGE: 6.34 ± 2.73 to 4.78 ± 2.04 mmol/L; both p < 0.001), while hypoglycemia still occurred in a subset. The TFQI-MAGE association increased in magnitude across inpatient days and was significant on Day 6 (β = 1.38, p < 0.001). In fully adjusted models, higher TFQI was associated with high GV (OR 3.11, 95% CI 1.27-7.60) and hypoglycemia (OR 4.78, 95% CI 1.56-14.63).
CONCLUSIONS: In euthyroid adults with type 2 diabetes undergoing inpatient titration, higher thyroid feedback indices, particularly TFQI, were linked to greater residual CGM variability and a higher risk of hypoglycemia on the later inpatient day. These readily available indices may augment CGM-based inpatient risk stratification for monitoring intensity and titration pace; prospective studies incorporating treatment dose, timing, dietary intake and stress physiology are needed.
CLINICAL TRIAL REGISTRATION: Not applicable.

Keywords:  Continuous glucose monitoring; Diabetes technology; Glycemic variability; Hypoglycemia; Thyroid feedback quantile-based index; Time in range; Type 2 diabetes

DOI:  https://doi.org/10.1186/s12902-026-02437-1
J Pharm Pract. 2026 Oct 30. 8971900261505220

Type 2 Diabetes and Continuous Glucose Monitoring: A Pilot Cross-Sectional Study of Medication Adherence and Self-Management Behaviors.

Thomas Pile, Angel Kimble, Mary Catherine Cole.

  Continuous glucose monitoring (CGM) is associated with improved glycemic outcomes, largely in insulin-treated populations, potentially through enhanced engagement and self-management. Its relationship with adherence to oral diabetes medications remains unclear. This study aimed to assess medication adherence among CGM users prescribed oral diabetes medications and explore perceived behavioral changes associated with CGM use. A cross-sectional pilot survey was conducted among adults with type 2 diabetes using CGM and at least one oral diabetes medication, recruited from a community pharmacy. Concurrent insulin use was not exclusionary and was not recorded. Adherence was measured using the 9-item Hill-Bone Medication Adherence Scale (HB-MAS). Quantitative data were summarized descriptively, and qualitative responses underwent thematic analysis. Twenty-nine participants completed the survey (mean age 54.7, SD 12.9 years; 59% female). CGM use was well established (62% ≥ 12 months; 90% checked glucose multiple times daily). Self-reported adherence was high (mean HB-MAS 34.1 ± 2.2; median 35), with 72% classified as excellent (≥33). No differences were observed across age groups (P = .46). Most participants reported CGM improved medication consistency (72%) and dietary choices (69%), with smaller effects on physical activity (31%). Themes included convenience, real-time feedback, and reduced finger sticks. Among established CGM users, self-reported adherence was high and perceived to improve with CGM use, suggesting CGM feedback may support medication-taking behaviors. Because concurrent insulin use was not recorded, findings may not generalize to individuals treated with oral agents alone. Further study using objective adherence measures and longitudinal designs is warranted.

Keywords:  community pharmacy; continuous glucose monitoring; diabetes mellitus, type 2; medication adherence; patient compliance

DOI:  https://doi.org/10.1177/08971900261505220
Sensors (Basel). 2026 Oct 12. pii: 6442. [Epub ahead of print]26(20):

Fuzzy Fault Detection and Band-Conditioned Data Quality Assessment for Sensor Streams: A Continuous Glucose Monitoring Case Study.

Juan F Gaitán-Guerrero, Carmen Martínez-Cruz, Macarena Espinilla, José L López.

  Sensor faults can propagate beyond raw measurements and distort the aggregates used to interpret a monitored phenomenon. We propose a domain-agnostic, five-layer fuzzy pipeline that characterizes the reliability of a sensor stream jointly over time and value bands and carries it through to every derived aggregate: (L1) fault tagging of each sample against five fuzzy failure primitives; (L2) fuzzy windowing; (L3) band reliability; (L4) routed repair with propagated reconstruction uncertainty; and (L5) veracity aggregation with linguistic protoforms. An end-to-end acquisition architecture is also specified. The pipeline was instantiated for continuous glucose monitoring (CGM) with clinical knowledge of glucose dynamics and applied to a 14-month recording of an adult with type 1 diabetes (FreeStyle Libre 3, 5-min cadence), of which 294 days contained at least 120 readings. Clean reference days remained essentially unchanged (mean sample quality 0.98-0.99). On the most corrupted day, the estimated time below range fell from 16% to 3%, with a veracity of only 0.14. Over the recording, 38% of the days were too unreliable to phenotype and 5% changed phenotype. Joint time- and band-conditioned reliability assessment thus prevents corrupted sensor data from producing falsely precise clinical conclusions.

Keywords:  continuous glucose monitoring; data reliability; fuzzy logic; linguistic protoforms; sensor monitoring; uncertainty-aware aggregation

DOI:  https://doi.org/10.3390/s26206442
Diabetes Obes Cardiometab CARE. 2026 Jul-Aug;1(4):1(4): e4-e6

Piloting a Professional Continuous Glucose Monitoring Program in a Safety-Net Diabetes Clinic: A Quality Improvement Study.

Pooja Goel, Dalgliesh Thomas, Kristie Adame, Daniel Okorodudu, Felona Gunawan.

DOI: https://doi.org/10.2337/doc26-0034
J Diabetes Sci Technol. 2026 Oct 28. 19322968261496274

Changes in CGM-Derived Glycemic Metrics and Triglyceride-Glucose Index During Ramadan in Adults With Type 2 Diabetes Using Real-Time Continuous Glucose Monitoring.

Ayman Al Hayek, Wael M Al Zahrani, Mo'men Al Ajlouni, Haifa F Alotaibi, Mohammed A Al Dawish.

   PURPOSE: To evaluate longitudinal changes in continuous glucose monitoring (CGM)-derived glycemic metrics, glycemia risk indices (GRIs), triglyceride-glucose (TyG) index, and diabetes self-management before, during, and after Ramadan fasting in adults with type 2 diabetes (T2D) receiving non-intensive diabetes therapy and using real-time CGM (rtCGM).
METHODS: This ambispective longitudinal cohort study included 110 adults with T2D managed at a tertiary diabetes center in Riyadh, Saudi Arabia. The study combined retrospective ascertainment of pre-enrollment data with prospective follow-up from enrollment during Ramadan through the post-Ramadan period. Glycemic outcomes were assessed across pre-Ramadan, Ramadan, and post-Ramadan periods using CGM-derived metrics, including time in range (%TIR70-180), time above range, glucose variability, GRI, and hypoglycemia indices. The TyG index and Perceived Diabetes Self-Management Scale (PDSMS) were also evaluated.
RESULTS: Compared with the pre-Ramadan period, median %TIR70-180 increased significantly during Ramadan from 60.8% to 65.0% (P < .001), while median sensor glucose decreased from 187 to 175 mg/dL (P < .001). Glucose variability also improved during Ramadan (36.5% vs 32.0%, P < .001), accompanied by lower GRI values (38.0 vs 35.3, P < .001). Severe hypoglycemia exposure (time below range, %TBR<54) remained unchanged (P = .358), although mild hypoglycemia exposure increased modestly. The TyG index decreased during Ramadan (9.65 vs 9.55, P = .003), whereas PDSMS scores increased from 27.0 to 29.0 (P < .001). Several glycemic and metabolic parameters demonstrated post-Ramadan rebound toward pre-Ramadan levels. No hospitalizations or treatment-escalation events occurred during Ramadan.
CONCLUSION: Improved glycemic control, reduced hyperglycemia exposure, and enhanced diabetes self-management were observed during Ramadan among selected adults with T2D receiving non-intensive diabetes therapy, rtCGM, and structured Ramadan-focused support, with stable severe hypoglycemia exposure despite a modest increase in mild hypoglycemia.

Keywords:  Ramadan fasting; blood glucose monitoring; continuous; diabetes mellitus; glycemia risk index; triglyceride-glucose (TyG) index; type 2

DOI:  https://doi.org/10.1177/19322968261496274
J Endocr Soc. 2026 Nov;10(11): bvag244

Six-month real-world glycemic improvement after Smart MDI system in type 1 diabetes.

Giada Rossi, Ida Pastore, Laura Montefusco, Lorenzo Pozzi Canova, Francesca D'Addio, Paolo Fiorina.

   Background and Aims: Smart multiple daily injection (Smart MDI) system integrating continuous glucose monitoring (CGM), insulin pens, and decision-support tools may optimize glycemic control in type 1 diabetes (T1D). However, real-world data remain limited. We evaluated 6-month glycemic outcomes following transition to Smart MDI in adults with T1D and explored differences according to carbohydrate counting status.
Methods: This retrospective, single-center, observational study included 24 adults with T1D on MDI who transitioned to Smart MDI. CGM metrics were analyzed at baseline and after 1, 3, and 6 months. The primary outcome was change in time in range (TIR 70-180 mg/dL). Secondary outcomes included time above range (TAR), time below range (TBR), mean glucose, glucose management indicator (GMI), coefficient of variation, and HbA1c. Exploratory analyses compared individuals practicing carbohydrate counting (n = 12) with those who did not (n = 12).
Results: TIR increased progressively from 56.1 ± 20.4% to 66.3 ± 17.5% (median change +9.0%, P < .01). TAR and TBR significantly decreased. HbA1c declined from 7.6 ± 1.1% to 7.3 ± 0.9% (median change -0.2%, P = .01). While between-group differences were not significant, individuals not practicing carbohydrate counting showed preliminary within-group improvements in TIR, TAR, mean glucose, GMI, and HbA1c, without increased TBR, whereas changes in the carbohydrate counting group were smaller.
Conclusions: Transition to the Smart MDI system was associated with clinically meaningful improvements in CGM metrics and HbA1c over 6 months. Improvements among individuals not practicing carbohydrate counting suggest that the Smart MDI system may provide standardized decision support also beneficial in less structured self-management settings. Larger studies are warranted to confirm these findings.

Keywords:  carbohydrate counting; continuous glucose monitoring; multiple daily injections; smart insulin pen; type 1 diabetes

DOI:  https://doi.org/10.1210/jendso/bvag244
Diabetes Obes Cardiometab CARE. 2026 Jan-Feb;1(1):1(1): 118-127

How CGM Boosts Self-Efficacy, Engagement With Self-Management, and Clinical Outcomes in Adults With Type 2 Diabetes: A Mixed-Methods Study.

Emily C Soriano, William H Polonsky, Taylor L Clark, Mariya Chichmarenko, Haley Sandoval, Alessandra Bastian, Addie L Fortmann, Andrew Kwist, Fleur Levrat-Guillen.

OBJECTIVE: Continuous glucose monitoring (CGM) improves type 2 diabetes (T2D) outcomes, but how this is achieved remains unclear. We explored how CGM affects diabetes-related attitudes and behavior, and whether these changes are associated with engagement in self-management and glycemic outcomes.
RESEARCH DESIGN AND METHODS: T2D adults who completed the FreeStyle Libre 3 (FSL3) arm of a 3-month randomized controlled trial were invited to participate in semistructured interviews. Thematic analysis was used to identify attitudinal and behavioral themes. Linear regression tested whether themes were associated with changes in self-reported engagement and HbA1c.
RESULTS: Thirty-one of 47 (66%) FSL3 arm participants were interviewed. Three attitudinal themes emerged: greater awareness, effective decision-making, and enhanced self-efficacy. Behavioral themes included diet modifications, physical activity changes, and medication-taking changes. Participants reporting enhanced self-efficacy (65% of the sample) showed greater HbA1c reductions (1.5% [16 mmol/mol] vs. 0.1% [1 mmol/mol], P = 0.004) and greater gains in engagement (0.5 vs. 0.1, P = 0.005) than those who did not.
CONCLUSIONS: CGM use is associated with meaningful improvements in diabetes-related attitudes and behaviors. Enhanced diabetes self-efficacy, in particular, may be a key pathway by which CGM improves glycemic outcomes and engagement in self-management among adults with T2D.

DOI: https://doi.org/10.2337/doc25-0053
Metabolism. 2026 Oct 27. pii: S0026-0495(26)00324-0. [Epub ahead of print] 156811

Assessing reproducibility of CGM-derived postprandial phenotypes without discordance-based exclusion.

Jiaqi Shen, Fangfang Huang.



Keywords:  Continuous glucose monitoring; Postprandial glucose response; Precision nutrition; Reproducibility; Type 2 diabetes

DOI:  https://doi.org/10.1016/j.metabol.2026.156811
Diabetes Obes Metab. 2026 Oct 27.

A Comparative Analysis Between Original and Updated Glucose Management Indicator and Glycated Haemoglobin Across Continuous Glucose Monitoring Sensors in Type 1 Diabetes.

Lavanta Farouk, Bilal Bashir, Rachel Seese, Parizad Avari, Monika Reddy, Richard M Bergenstal, Viral N Shah, Nick Oliver, Mark L Evans, Hood Thabit, Lalantha Leelarathna.

   AIMS: The continuous glucose monitoring (CGM)-derived glucose management indicator (GMI) is used for estimating glycated haemoglobin (HbA1c). This study assessed agreement between GMI-calculated using both original and updated (uGMI) models-and laboratory-measured HbA1c across Dexcom, MiniMed and Abbott sensors.
MATERIALS AND METHODS: Real-world data from adults with type 1 diabetes using automated insulin delivery were retrospectively analysed. Δ(GMI-HbA1c) and Δ(uGMI-HbA1c) were evaluated over 90 days preceding HbA1c (n = 383) and over 28 days preceding HbA1c (n = 375). Agreement was measured as directional difference, indicating GMI overestimation or underestimation of HbA1c, and absolute difference, indicating magnitude of agreement between GMI and HbA1c. Agreement was assessed across sensor groups using ANCOVA, adjusting for coefficient of variation and ethnicity.
RESULTS: Although mean directional differences were statistically significant for Δ(GMI-HbA1c) and Δ(uGMI-HbA1c) across all sensor groups (p < 0.001), differences were small and not clinically important, 90-day adjusted means (95% CI)-Δ(GMI-HbA1c): Dexcom 0.17% (0.09, 0.25), MiniMed -0.15% (-0.28, -0.02), Abbott -0.08% (-0.25, 0.09); Δ(uGMI-HbA1c): Dexcom 0.22% (0.14, 0.30), MiniMed -0.10% (-0.23, 0.02), Abbott -0.02% (-0.19, 0.15). Mean absolute difference did not significantly differ across sensor groups-Δ(GMI-HbA1c): 0.42%-0.51% (p = 0.353), Δ(uGMI-HbA1c): 0.41%-0.52% (p = 0.221).
CONCLUSIONS: GMI/uGMI performed consistently across sensor groups. Where clinically meaningful discrepancies between GMI/uGMI and HbA1c arise, these warrant interpretation within the context of individual clinical and laboratory factors rather than attribution to sensor manufacturer, reinforcing the need for personalised use of GMI alongside HbA1c.

Keywords:  continuous glucose monitoring (CGM); glycaemic control; real‐world evidence; type 1 diabetes

DOI:  https://doi.org/10.1111/dom.71484
Diabetes Obes Cardiometab CARE. 2026 Jan-Feb;1(1):1(1): 40-44

Closing the Gap: Strategies for Broader Adoption and Use of Continuous Glucose Monitors Among Children and Adolescents With Type 1 Diabetes.

Ashley N Garrity, Jacqueline S Fisher, Inas H Thomas, Joyce M Lee.

OBJECTIVE: This project aimed to increase continuous glucose monitor (CGM) adoption and use among pediatric and adolescent patients with type 1 diabetes at the University of Michigan while reducing racial and ethnic disparities.
RESEARCH DESIGN AND METHODS: We conducted a quality improvement (QI) project from February 2022 through December 2023. Over the project period, several interventions were tested through plan-do-study-act cycles, including patient-facing CGM education, implementation of revised electronic health record (EHR) flowsheets to track CGM adoption and use, as well as address barriers, prescribing-related workflow changes, and provision of technical support to newly diagnosed patients starting a CGM. CGM adoption and use rates were measured and stratified by race and ethnicity.
RESULTS: At baseline, 87% of non-Hispanic White (NHW) patients and 75% of non-White patients had a CGM. By June 2024, adoption rates increased to 98% for NHW patients and 97% for non-White patients. CGM use (>70% of the time) also improved, reaching 89% among NHW and 88% among non-White patients.
CONCLUSIONS: This initiative demonstrates that QI interventions, including efforts to address individual-level barriers, can substantially increase CGM adoption and use while improving equity. The findings highlight the importance of standardizing clinic workflows and patient engagement in advancing diabetes technology adoption.

DOI: https://doi.org/10.2337/doc25-0042
Life (Basel). 2026 Oct 05. pii: 1667. [Epub ahead of print]16(10):

Time in Range as a Marker of Concurrent Glycemic and Lipid Improvement in Adults with Type 2 Diabetes: A Real-World Retrospective Pre-Post Study.

Mi-Joon Lee, Bum-Jeun Seo, Jae-Hyoung Cho.

  This study aims to evaluate whether continuous glucose monitoring (CGM)-derived time in range (TIR) attainment is associated with concurrent improvements in glycemic control and lipid profiles among adults with type 2 diabetes mellitus (T2DM). In this retrospective, single-arm pre-post study, 542 adults with T2DM who underwent intermittently scanned CGM for 12 weeks were analyzed. Glycated hemoglobin (HbA1c), fasting plasma glucose (FPG), total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were compared before and after CGM use. Participants were stratified by TIR into low (<50%), intermediate (50-70%), and target (>70%) groups. Overall, HbA1c decreased from 8.12% to 7.49% and FPG from 153.35 to 136.70 mg/dL (both p < 0.001). Significant improvements were also observed in total cholesterol, triglycerides, HDL-C, and LDL-C. Glycemic improvement occurred across all TIR strata; however, significant improvements in all lipid parameters were observed only in participants achieving TIR >70%. In this group, total cholesterol decreased by 4.23 mg/dL, triglycerides by 11.12 mg/dL, and LDL-C by 4.48 mg/dL, and HDL-C increased by 1.34 mg/dL. These findings suggest that achieving the consensus TIR target of >70% may be associated with broader cardiometabolic benefits beyond glycemic improvement alone. TIR may therefore serve as a clinically useful complementary target to HbA1c in routine diabetes management.

Keywords:  continuous glucose monitoring; glycated hemoglobin; glycemic control; lipid metabolism; time in range; type 2 diabetes mellitus

DOI:  https://doi.org/10.3390/life16101667
Cureus. 2026 Sep;18(9): e116933

Glycemic Dynamics and Management Strategies in Individuals With Type 1 Diabetes During Ramadan: A Continuous Glucose Monitoring-Based Narrative Review.

Abubakr Sowilem, Abdelrhman K Mohamed, Emad Wissa, Raof Rashed, Mahmoud M Magdi.

  Ramadan is the ninth month of the Islamic lunar calendar, during which healthy adult Muslims fast daily from sunrise to sunset. Fasting during Ramadan presents unique physiological and behavioral challenges for individuals with type 1 diabetes mellitus (T1DM), who are generally classified as high- to very-high-risk for fasting. Because traditional markers such as hemoglobin A1C (HbA1c) and self-monitored blood glucose fail to capture short-term glycemic excursions, continuous glucose monitoring has become essential for evaluating real-world glycemic dynamics during this period. This review examines recent continuous glucose monitoring-based studies to characterize the direction, magnitude, and determinants of glycemic changes during Ramadan. Across the literature, findings demonstrate considerable heterogeneity, ranging from glycemic deterioration to temporary improvement or stability, influenced heavily by baseline glycemic control, age, insulin delivery modalities, and whether participants received structured pre-Ramadan education. Notably, exposure to hypoglycemia does not appear to increase during Ramadan fasting; instead, postprandial hyperglycemia clustered around the evening and pre-dawn meals emerges as the predominant and most variable challenge. Structured pre-Ramadan education, individualized insulin adjustments, and continuous glucose monitoring-guided management are critical levers for supporting safer fasting in this population.

Keywords:  continuous glucose monitoring; glycemic control; pre-ramadan education; ramadan fasting; type 1 diabetes mellitus (t1d)

DOI:  https://doi.org/10.7759/cureus.116933
Diabetes Obes Cardiometab CARE. 2026 Jul-Aug;1(4):1(4): 592-600

Behavior Modifications From CUT-DM, Including Lifestyle Modification and Self-Efficacy.

Jovana Vidovic, Ana Gabriela Vasconcelos, Peter Berberian, Bryan A Comstock, Laura Montour, Lorena Alarcon-Casas Wright, Nicole Ehrhardt.

OBJECTIVE: To investigate the effects of diabetes self-management education and support (DSMES) and real-time continuous glucose monitoring (RT-CGM) on lifestyle among Latinx patients with type 2 diabetes (T2D).
RESEARCH DESIGN AND METHODS: The CUT-DM (Diabetes Education With Real-time Continuous Glucose Monitoring) open-label randomized controlled trial enrolled 119 Latinx participants with uncontrolled diabetes receiving nonintensive insulin to investigate DSMES and RT-CGM effects on lifestyle and self-care and, in RT-CGM users, perception of benefit. All participants attended 12 sessions and were randomly assigned at a one-to-one ratio to education only with blinded CGM or education with RT-CGM.
RESULTS: Lifestyle improved over 12 weeks in both groups. Days of physical activity increased by 60% (95% CI 20-120%; P < 0.01), and days walking at least 10 min increased by 20% (95% CI 0-30%; P < 0.01). Nutrition summary scores improved by 1.7 (95% CI 1.0-2.3) units (P < 0.01). Self-efficacy improved by 1.2 (95% CI 0.8-1.7) points (P < 0.01). Self-care improved by 1.6 (95% CI 1.0-2.2) units for diet (P < 0.01), 1.1 (95% CI 0.6-1.7) units for exercise (P < 0.01), 1.6 (95% CI 1.0-2.2) units for foot care (P < 0.01), and 0.6 (95% CI 0.0-1.2) units for medication use (P = 0.063). Self-care for diet improved more with RT-CGM than with blinded CGM (2.4 [95% CI 1.3-3.4) vs. 0.8 [95% CI -0.3 to 1.9] points; P = 0.01). Nutrition score improvement differences were not significant (P = 0.5). Of RT-CGM participants, 97% reported that CGM benefited their health.
CONCLUSIONS: DSMES supported lifestyle modifications. Perception of benefit among RT-CGM users receiving education was high. CGM use likely enhances nutrition, physical activity, and self-care in T2D, but more research is needed.

DOI: https://doi.org/10.2337/doc25-0093
Diabetes Technol Ther. 2026 Oct 22. 15209156261499152

Continuous Glucose Monitoring Methods Evaluation and Recommendations for Reporting Guidelines.

Ashley Y DuNova, Casey M Rand, Mandy M Shao, Agatha F Scheideman, Cindy N Ho, Alessandra T Ayers, Kevin T Nguyen, Eric Williams, Shahid N Shah, David C Klonoff, Juan C Espinoza.

   OBJECTIVE: To evaluate the completeness of methodological reporting in continuous glucose monitoring (CGM)-based clinical trials, and based on our findings, to propose a standardized reporting framework to improve reproducibility and transparency.
RESEARCH DESIGN AND METHODS: We conducted a search to assemble a study sample of CGM-based clinical trials published between 2019 and 2024. Articles were identified via PubMed and screened based on predefined eligibility criteria. We measured the presence or absence of reporting elements across seven core methodological features essential for reproducibility, spanning CGM device characteristics, data platforms, data extraction processes, preprocessing and transformation methods, handling of missing data, CGM metrics, and analytic approaches. Data were manually extracted by trained reviewers, with quality assurance performed on a subset of records. Descriptive statistics were used to summarize reporting completeness.
RESULTS: A total of 248 studies met inclusion criteria. On average, studies reported 4.39 (SD 1.22) of the seven core methodological features. Reporting was highest for CGM metrics (100%), analytic methods (100%), and device make/model (96%). In contrast, key elements of the CGM data pipeline were frequently underreported, including data extraction processes (56%), preprocessing methods (43%), handling of missing data (32%), and CGM data platform (30%). Only 6% of studies reported all seven features. These findings demonstrate substantial heterogeneity and consistent gaps in reporting practices across CGM clinical research within the literature sampling frame.
CONCLUSIONS: Incomplete reporting of CGM data pipelines limits reproducibility, comparability, and the clinical and computational utility of CGM-derived outcomes. We propose a preliminary, candidate CGM-specific reporting checklist to standardize documentation of data acquisition, processing, and analysis. Adoption of a refined, consensus-based version of such a framework may strengthen methodological rigor, support regulatory and clinical interpretation, and enhance the reliability of CGM data for emerging digital health and artificial intelligence applications.

Keywords:  continuous glucose monitoring (CGM); data pipeline; diabetes research; digital biomarkers; digital health; reporting guidelines; reproducibility

DOI:  https://doi.org/10.1177/15209156261499152
J Pediatr Endocrinol Metab. 2026 Oct 26.

Technology use in youth with type 1 diabetes and language of care other than English.

Samantha Goldklang, Kristen Carlin, Meenal Gupta, Isabella Niu, Alissa J Roberts.

   OBJECTIVES: Our primary aim was to describe continuous glucose monitor (CGM) and insulin pump use in youth with T1D with a preferred language of care other than English (LOE) and examine associations between diabetes technology use and hemoglobin A1c (HbA1c) in this population.
METHODS: We assessed baseline technology use for youth with LOE and T1D seen in diabetes clinics at a single center between February 2022 and February 2023. A two-sample t-test was used to compare HbA1c values between groups. A linear regression model was used to examine differences in HbA1c between the 3-level technology groups with Tukey-adjusted pairwise comparisons.
RESULTS: Ninety-four youth with T1D and LOE with complete data on technology use were included in analysis. At baseline 66 % were using diabetes technology with 42 (45 %) using CGM only, 1 (1 %) using insulin pump only, 19 (20 %) using both insulin pump and CGM, and 32 (34 %) not using any technology. HbA1c was significantly lower in the technology use group (Mean=9.1 %, SD=2.4) compared to the non-technology use group (Mean=10.5 %, SD=2.2) (p=0.01).
CONCLUSIONS: Despite advances in technology for diabetes management, about one-third of youth with T1D and LOE were not using any diabetes technology. Diabetes technology use in this group was associated with lower HbA1c. Further work should be done to increase diabetes technology use in youth with T1D and LOE.

Keywords:  diabetes technology; language of care; type 1 diabetes

DOI:  https://doi.org/10.1515/jpem-2026-0370
J Diabetes Sci Technol. 2026 Oct 25. 19322968261496268

Real-World Evaluation of a Near-Infrared Spectroscopy-based Noninvasive Glucose Monitoring Device in Adults With Type 2 Diabetes.

Sandra Amuedo, Mónica Enríquez Macías, José Manuel Fornés, Arturo Moreno Arteaga, Jesús Riesgo Barrau, Virginia Bellido, Fernando Losada Viñau, Luz María Hidalgo Pichardo, Alfonso Soto Moreno, Antonio Puppo Moreno, Alfonso Pumar López.

   BACKGROUND: Self-monitoring of blood glucose remains widely used in many individuals with type 2 diabetes (T2D), although the burden of capillary testing often limits the frequency of measurements. Noninvasive technologies may improve glucose monitoring. This study evaluated the analytical performance and applicability of a near-infrared spectroscopy-based noninvasive glucose monitoring device.
METHODS: In this prospective, open-label clinical investigation, 52 adults with T2D performed 4 daily paired glucose measurements for more than 21 days using the investigational device and a reference capillary glucometer (Ascensia Contour Next). Following individualized calibration (10 paired measurements), post-calibration measurements within the 70 to 400 mg/dL range were included in the primary analysis. Accuracy was assessed using a combined mean absolute difference/mean absolute relative difference (MAD/MARD) metric, Parkes consensus error grid (CEG), and DTS error grid analyses.
RESULTS: Forty-eight participants were included in the primary analysis, contributing 2,616 paired post-calibration measurements. The mean age was 58.0 ± 9.9 years, and 31.3% were female. The overall combined MAD/MARD value was 16.3, calculated by applying MAD to paired measurements with reference glucose values <100 mg/dL and MARD to paired measurements with reference glucose values ≥100 mg/dL. Overall, 69.8%, 86.3%, and 94.5% of measurements were within ±20%, ±30%, and ±40% of reference values, respectively. Parkes CEG analysis classified 69.9% of measurements in zone A, 29.1% in zone B, 1.0% in zone C, and none in zones D or E. Accuracy improved after the first week. No device-related adverse events were reported.
CONCLUSION: The device demonstrated a favorable clinical risk profile, stable analytical performance, and good safety under real-world conditions. Although analytical precision remains lower than current continuous glucose monitoring systems, its fully noninvasive design supports further development as a complementary monitoring strategy for individuals with T2D unwilling or unable to use invasive monitoring technologies.
TRIAL REGISTRATION: ClinicalTrials.gov (NCT07075796).

Keywords:  glucose monitoring accuracy; near-infrared spectroscopy; noninvasive glucose monitoring; self-monitoring of blood glucose; type 2 diabetes; usability

DOI:  https://doi.org/10.1177/19322968261496268
Nat Commun. 2026 Sep 28. pii: 11211. [Epub ahead of print]17(1):

Adaptive personalization for wearable non-invasive continuous glucose sensors.

Chuanjie Yao, Lukang Gao, Xinze Wang, Haolin Wang, Shuang Huang, Guanbin Li, Xiongqi Han, Hanqi Yang, Zhengjie Liu, Shanshan Liang, Peng Yun, Yunuo Wang, Yeyun Cai, Peikai Zhang, Yuanqing Wu, Mingqiang Li, Ji Wang, Hui-Jiuan Chen, Xinshuo Huang, Xi Xie.

Accurate continuous glucose monitoring (CGM) is essential for diabetes management, yet non-invasive CGM remains challenging. Universal "one-sensor-fits-all" approaches often fail, because correlations between non-invasive physiological readouts and blood glucose (BG) are highly individualized. Here, we propose a personalized "Adaptive Non-invasive CGM" methodology, which integrates a short-term minimally invasive CGM (MI-CGM) module for measuring interstitial fluid glucose, and a long-term non-invasive CGM (NI-CGM) module based on metabolic heat conformation. During a ~2-days training, the NI-CGM learns accurate sensing from the MI-CGM via GRU-based AI model, forming patient-specific sensor. The MI-CGM is then removed, leaving only the NI-CGM for long-term monitoring. In a 5-day CGM test, the system achieved MARD ~15.6%. This method also demonstrated good reproducibility and maintained reasonable accuracy (MARD ~23.9%) during long-term interval use (>2 months). This personalized approach offers a pathway from conventional "one-sensor-fits-all" strategies toward individualized sensor development, potentially mitigating inter-patient variability and non-invasive monitoring inaccuracies.

DOI: https://doi.org/10.1038/s41467-026-74531-w
Sports (Basel). 2026 Oct 01. pii: 422. [Epub ahead of print]14(10):

Considerations for Swimmers with Type 1 Diabetes: A Narrative Review.

Andrija Djuranovic, Sebastijan Higl, Tijana Cirkovic Higl, Milena Antic, Gordana Korolija Mrdjanov, Djordje Batinic, Milos Maletic, Jovana Ristic, Vladimir Jakovljevic.

  Achieving success at the highest level in swimming requires exceptional physical abilities and technical skills. Type 1 diabetes (T1D) poses an additional challenge to maintaining optimal glycemic control. Most information on the nutritional aspects of competitive swimming is available in the literature, but specific considerations for swimmers with T1D are scarce. To excel, swimmers' nutrition and fueling strategies must align with the varied training and competition requirements, which can elicit different glycemic responses. Continuous glucose monitoring can help develop optimal fueling strategies. Dryland and altitude training will require different approaches than regular pool sessions. Competition-related stress can make glycemia unpredictable, and practiced scenarios must be established. The importance of early recognition of hypoglycemia with planned and practiced treatment scenarios should be established. There is limited evidence on the safety of using ergogenic aids other than caffeine in swimmers with T1D. Given the higher incidence of disordered eating behaviors and eating disorders among swimmers and other individuals with T1D, coaches and everyone involved in the swimmers' environment should be educated on how to communicate potential body composition issues and, if necessary, manage body composition safely. Swimmers and their team members should be aware of the specific considerations for T1D in swimming for safe sports participation, as presented in this review.

Keywords:  CGM; carbohydrate; diabulimia; nutrition; swimming; type 1 diabetes

DOI:  https://doi.org/10.3390/sports14100422
Front Digit Health. 2026 ;8 1932366

GlucoSense: early diabetes risk assessment via fusion of human activity recognition and glucose prediction.

Md Fokrul Islam Khan, Md Zia Uddin, Mohammed Shamsul Alam, Adel Baselizadeh, Abdul Kadar Muhammad Masum.

  Non-Insulin-Dependent Diabetes Mellitus (NIDDM) is a chronic and progressive metabolic disease characterized by chronically high blood glucose levels. It is a disease with an often asymptomatic onset, which means that a high percentage of affected individuals remain unidentified until quite far in the disease process, thereby underlining the importance of a good, reliable screening instrument for proactive detection. In this paper, GlucoSense is introduced as a single framework for early NIDDM risk stratification by combining Human Activity Recognition (HAR) with continuous blood glucose forecasting using two Graph Attention Network version 2 (GATv2)-based architectures. The first is a HAR module trained with smartphone triaxial accelerometer data that covers 23 activity classes, while the second is a glucose prediction module trained with the OhioT1DM dataset to predict glucose levels for a 30 min horizon. Unlike sequential models, GlucoSense encodes complex dependencies between movement patterns, cardiac activity, nutrition, and glycemic behaviour by modeling relationships in a graph structure. The study was longitudinal, spanning 90 days, with six participants. Three important clinical parameters, mean glucose level, time above hyperglycemic level, and glycemic coefficient of variance were calculated. The system was able to correctly identify metabolically healthy individuals and those with prediabetic patterns. The framework was cross-validated with HbA1c laboratory tests to verify the clinical consistency of the framework. Both modules were benchmarked against sequential, convolutional, attention-based, and graph-based baselines under an identical protocol with five independent runs. The glucose module lowered the root mean squared error from 31.82 mg/dL for an LSTM baseline to 25.60 mg/dL, and the activity module reached 98.50% accuracy, with every difference confirmed by paired significance testing and reported with 95% confidence intervals. Understanding glucose dynamics based on smartphone sensor data and a limited number of physiological markers, GlucoSense offers a non-invasive, scalable and cost-effective alternative to traditional clinical glucose screening. This paper demonstrates the feasibility of smartphone-based longitudinal diabetes risk assessment and motivates future large-scale population studies.

Keywords:  NIDDM; continuous glucose monitoring; early diabetes diagnosis; graph attention network; human activity recognition; type 2 diabetes

DOI:  https://doi.org/10.3389/fdgth.2026.1932366