bims-glumda 2025-08-17 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2025–08–17
twenty-two papers selected by
Mott Given

Continuous glucose monitoring system in diabetes in pregnancy: a narrative review.
Continuous glucose monitoring remote monitoring does not meet the needs of all adult users: A qualitative study of adults with type 1 diabetes who do not use remote monitoring.
The Virtual DCCT #3: Relationship of HbA1c and CGM Metrics with Cardiovascular Outcomes.
Accuracy of Dexcom G6 Pro Continuous Glucose Monitor in the Intensive Care Setting: TIGHT ICU G6 Study.
Diabetes screening in dialysis populations with a glucose challenge test and continuous glucose monitoring-DIGEST study.
Effectiveness of continuous glucose monitoring systems on glycemic control in adults with type 1 diabetes: A systematic review and meta-analysis.
CGM Data Analysis 2.0: Functional Data Pattern Recognition and Artificial Intelligence Applications.
Effect of switching from intermittently scanned to real-time continuous glucose monitoring on glycaemic outcomes in adults with type 1 diabetes: A real-world, Canadian retrospective study.
Evaluating Insulin Delivery Systems Using Dynamic Glucose Region Plots and Risk Space Analysis.
Incorporating Uncertainty Estimation and Interpretability in Personalized Glucose Prediction Using the Temporal Fusion Transformer.
Privacy Preserved Blood Glucose Level Cross-Prediction: An Asynchronous Decentralized Federated Learning Approach.
Feasibility of continuous glucose monitoring in children with diabetic ketoacidosis: an exploratory observational study.
Diabetes Technology and the Older Adult: Clinical Outcomes and Implementation Strategies.
Dietary intakes and physical activity of women with gestational diabetes are not associated with continuous glucose monitoring metrics; Secondary analysis of the DiGest trial.
Correction to "Effects of Insulin Glargine U300 Versus Insulin Degludec U100 on Glycemic Variability, Hypoglycemia, and Diet Evaluated by Continuous Glucose Monitoring in Type 1 Diabetes: A Retrospective Cross-Sectional Study".
Impaired central thyroid hormone sensitivity is associated with time in range in patients with type 2 diabetes mellitus in the euthyroid population.
Continuous Glucose Monitoring-Enhanced eConsult Improves Clinical Outcomes in Adults Living With Diabetes in a Safety Net Primary Care Setting.
Swiss recommendations on driving ability in patients with diabetes mellitus.
Race and ethnic disparities in insulin pump and continuous glucose monitor use between 2017 and 2024: a systematic review with a focus on health equity.
Risk of Recurrent Hypoglycemia and Long-term Survival after total Pancreatectomy: A Prospective Observational Study.
The assessment of clinical factors influencing Glucose Management Indicator and Hba1c discordance in children with type one diabetes - one-year real-world data observation.
Cost Analysis of the FreeStyle Libre Systems in People with Type 2 Diabetes Mellitus on Basal Insulin with Poor Glycemic Control: A Spanish Perspective.

Diabetol Metab Syndr. 2025 Aug 09. 17(1): 322

Continuous glucose monitoring system in diabetes in pregnancy: a narrative review.

Melanie Rodacki, Marcio Krakauer, Denise Reis Franco, Patricia Medici Dualib, Mauro Sancovski, Lenita Zajdenverg.

  Diabetes in pregnancy increases maternal and fetal risks as well as the burden of chronic complications and comorbidities associated with this condition. In addition to HbA1c and blood glucose monitoring (BGM), continuous glucose monitoring systems (CGM) provide a complementary tool that enables comprehensive glycemic assessments and improves glycemic control. This review highlights the clinical value of CGM in the management of diabetes in pregnancy, encompassing type 1 diabetes, type 2 diabetes, gestational diabetes mellitus (GDM), but also early GDM. CGM derived metrics, such as time in range (TIR) and mean glucose levels, are associated with adverse pregnancy outcomes, emphasizing the importance of optimizing glycemic control. Overall, CGM is a valuable tool for detecting glucose fluctuations in pregnancies complicated by all forms of diabetes.

Keywords:  Accuracy; Continuous glucose monitoring; Diabetes; Gestational diabetes; Pregnancy

DOI:  https://doi.org/10.1186/s13098-025-01854-x
Diabet Med. 2025 Aug 13. e70120

Continuous glucose monitoring remote monitoring does not meet the needs of all adult users: A qualitative study of adults with type 1 diabetes who do not use remote monitoring.

Anjana Rathan, Alisa Boucsein, Hamish Crocket, Benjamin J Wheeler.

   AIMS: Continuous glucose monitoring (CGM) is increasingly popular in the management of type 1 diabetes (T1D). These devices have a remote monitoring function that allows for a third-party individual to monitor the user's glucose levels. While remote monitoring in CGM devices is widely used in T1D management, especially in paediatric populations, there are some individuals with T1D that do not utilise this function. This study aimed to explore the reasons behind some adults not using the remote following function on their real-time CGM (rtCGM) devices.
METHODS: Adults with T1D who had been using rtCGM without the remote monitoring function were invited to participate in a semi-structured interview. Interviews explored the participants' experiences using CGM and their reasons on why remote monitoring was not for them. Interviews were analysed thematically.
RESULTS: Interviews were conducted with fifteen people with T1D. Mean age was 27.3 years ± 9.34 SD. Thematic analysis identified three remote monitoring themes: (1) anxiety/concern regarding sharing data; (2) independence with diabetes management; and (3) desire for more customised sharing. There was a universal appeal of the efficacy, ease and practicality of glucose management with CGM devices among participants, particularly when compared to their past experiences with finger-prick testing.
CONCLUSIONS: Remote monitoring can be a valuable complement to CGM, but it may not appeal to all individuals with T1D, particularly some adults. These findings offer insights for healthcare teams and provide feedback to help CGM manufacturers develop a more customised remote monitoring experience. Some users clearly wish to prioritise privacy and autonomy while still gaining a safety net in critical situations.

Keywords:  continuous blood glucose monitoring; diabetes; qualitative methods

DOI:  https://doi.org/10.1111/dme.70120
Diabetes Technol Ther. 2025 Aug 13.

The Virtual DCCT #3: Relationship of HbA1c and CGM Metrics with Cardiovascular Outcomes.

William B Horton, Boris P Kovatchev, Lauren G Kanapka, Roy W Beck.

  Objective: Using a multistep machine-learning approach, the aim is to create virtual continuous glucose monitoring (CGM) traces from glycemic data collected in the Diabetes Control and Complications Trial (DCCT) to assess the relationship between CGM metrics and DCCT cardiovascular (CV) outcomes in people with type 1 diabetes. Research Design and Methods: Utilizing the virtual CGM traces created for each DCCT participant, as previously published, discrete Cox proportional hazard models were used to calculate hazard ratios (HRs) for the association between glycemic metrics (hemoglobin A1c [HbA1c] and virtual CGM) and 3 separate DCCT CV outcome definitions: (1) all DCCT-recorded events; (2) a restricted set of "hard" CV end points; and (3) a restricted set of major CV and major peripheral vascular events. Results: Mean HbA1c and CGM metrics reflective of hyperglycemia were consistently higher, and time-in-range (70-180 mg/dL) and time-in-tight-range (70-140 mg/dL) were consistently lower, in DCCT participants who experienced a CV outcome versus those who did not. For the outcome definition encompassing all CV events, specific adjusted HRs for a CV outcome per a 1 standard deviation (SD) change in glucose metrics were 1.29 for HbA1c with nearly identical values of 1.29-1.31 for relevant CGM metrics. A similar pattern was seen when assuming a 0.5 SD change in glucose metrics. Notably, there was no increased risk for experiencing a CV outcome as time-below-range increased, and in fact, there was a trend toward a slightly protective effect when assuming either a 1- or 0.5-SD change in virtual hypoglycemia metrics. Conclusions: Virtual CGM metrics are associated with CV outcomes in people with type 1 diabetes. These findings support the case for CGM metrics to be included as clinical trial primary endpoints for this population.

Keywords:  cardiovascular disease; continuous glucose monitoring; hyperglycemia; type 1 diabetes mellitus

DOI:  https://doi.org/10.1177/15209156251369538
Diabetes Technol Ther. 2025 Aug 13.

Accuracy of Dexcom G6 Pro Continuous Glucose Monitor in the Intensive Care Setting: TIGHT ICU G6 Study.

TIGHT RCT Study Group

  Objective: To evaluate the accuracy of the Dexcom G6 Pro continuous glucose monitoring (CGM) system in the intensive care unit (ICU) setting. Methods: We performed a prospective, observational, multicenter study in adult ICU patients with a known diagnosis of diabetes or stress hyperglycemia who were being treated with insulin. Two Dexcom G6 Pro sensors were placed. Sensor accuracy was assessed by pairing sensor and blood glucose (BG) measurements obtained as a part of usual ICU care. Accuracy of the G6 Pro also was assessed concurrently in non-ICU hospitalized individuals. Results: A total of 130 participants were enrolled, with mean (±SD) age of 62 ± 12 years, and preexisting diabetes was present in 73% and stress hyperglycemia in 27%. A total of 9120 sensor-BG pairs were analyzed. The mean relative absolute difference (RAD) was 23% (median 19%), with a mean difference of +25 mg/dL (median 25 mg/dL). Forty-one percent of sensor glucose values were within 15% of BG values for BG values ≥100 mg/dL or within 15 mg/dL of BG values for BG values <100 mg/dL, 53% within 20%/20 mg/dL, and 72% within 30%/30 mg/dL. For the two sensors worn simultaneously, the mean absolute difference was 24 mg/dL (median 19 mg/dL) and the mean RAD was 14% (median 11%). In the non-ICU setting (N = 60; 1318 sensor-BG pairs), the mean difference was 24 mg/dL (median 21 mg/dL) and the mean RAD was 21% (median 17%). Conclusions: Accuracy of the Dexcom G6 Pro sensor in the ICU setting was worse than has previously been reported for this sensor, with sensor values tending to be biased high. However, this appears to be a function of the G6 Pro sensor and not the setting as similar results were obtained in a non-ICU setting. Results should not be generalized to the real-time G6 or other sensors.

Keywords:  accuracy; blood glucose measurements; comparison; continuous glucose monitoring; intensive care unit

DOI:  https://doi.org/10.1177/15209156251368933
Diabetes Obes Metab. 2025 Aug 14.

Diabetes screening in dialysis populations with a glucose challenge test and continuous glucose monitoring-DIGEST study.

L Depoorter, Y Laghrib, J W De Fijter, R Hellemans, C De Block.

   BACKGROUND: People on dialysis are at a higher risk of diabetes mellitus. The oral glucose tolerance test (OGTT) is the gold standard for detecting dysglycaemia, but is cumbersome. This study investigates the OGTT in comparison to the glucose challenge test (GCT) and continuous glucose monitoring (CGM) as a simpler screening tool for people on dialysis.
METHODS: This single-centre prospective diagnostic cohort study included adults on dialysis at the Antwerp University Hospital without a diabetes history or glucose-lowering therapy. Participants underwent a 50 g-GCT followed by a 75 g-OGTT 8-10 days later, with CGM conducted in between.
RESULTS: Of 50 eligible individuals, 27 declined participation due to the OGTT burden. Thirteen out of 23 participants had dysglycaemia (2 -hr OGTT ≥140 mg/dL or ≥7.8 mmol/L). Those with dysglycaemia had a higher BMI (26.2 ± 3.9 vs. 22.8 ± 3.3 kg/m2, p = 0.039), longer dialysis vintage (4.5 ± 2.9 vs. 1.6 ± 1.4 years, p = 0.009), and were less often waitlisted for transplantation (5/13 vs. 10/10, p = 0.005). Fasting glycaemia levels were similar between groups. Dysglycaemia was more common in haemodialysis (HD) than in peritoneal dialysis (PD) (12/14 vs. 1/9, p < 0.001). CGM showed a lower time in range (95 ± 3% vs. 98 ± 3%, p = 0.020) and a higher coefficient of variation (24% vs. 16%, p < 0.001) in those with dysglycaemia. The GCT had an 85% sensitivity and a 70% specificity for dysglycaemia detection. A two-step approach using GCT as a screening tool could avoid 40% of OGTTs while missing 15% of cases. The 5% TATR (time above tight range) revealed a good sensitivity of 92%, but unfortunately, a specificity of 12%.
CONCLUSION: The GCT may be a practical alternative for dysglycaemia screening in the dialysis population. The 5% TATR showed good sensitivity but poor specificity.

Keywords:  beta cell function; cohort study; continuous glucose monitoring (CGM); glycaemic control; type 2 diabetes

DOI:  https://doi.org/10.1111/dom.16656
Metabol Open. 2025 Sep;27 100382

Effectiveness of continuous glucose monitoring systems on glycemic control in adults with type 1 diabetes: A systematic review and meta-analysis.

Salya F Alfadli, Yazeed S Alotaibi, Maha J Aqdi, Latifah A Almozan, Zahra B Alzubaidi, Hammad A Altemani, Shaden D Almutairi, Hussain A Alabdullah, Alaa Ahmed Almehmadi, Abdulrahman L Alanzi, Ahmed Y Azzam.

   Introduction: Continuous glucose monitoring (CGM) technologies have been advancing rapidly, but evidence on their comparative effectiveness stills limited to date yet. We conducted a systematic review and meta-analysis to evaluate and investigate the impact of CGM systems on glycemic control in adults with type 1 diabetes.
Methods: We searched electronic literature databases from inception through April 30, 2025, for comparative studies investigating CGM systems with standard monitoring or different CGM technologies in adults with type 1 diabetes. Primary outcomes included HbA1c reduction, time in range (TIR), and hypoglycemia reduction. We performed random-effects meta-analyses, network meta-analysis, and subgroup analyses by baseline HbA1c and intervention duration. Evidence quality was assessed using GRADE methodology.
Results: Twenty-seven studies with total of 2975 participants were included. CGM significantly reduced HbA1c compared to standard monitoring (mean difference: 0.38 %, 95 % CI: 0.49 to -0.27 %). TIR increased by 7.9 % (95 % CI: 5.8-10.0 %), representing 114 additional minutes daily in best range. Real-time CGM showed advantages over intermittently scanned CGM for TIR (+5.63 %, P-value<0.001) and hypoglycemia reduction (-1.28 %, P-value<0.001). Automated closed-loop systems achieved the highest ranking in network meta-analysis (SUCRA = 0.92). Benefits were greater among patients with higher baseline HbA1c (>8.5 %: 0.68 % reduction in HbA1c vs. <7.5 %: 0.24 % reduction in HbA1c, P-value = 0.009).
Conclusions: CGM technologies significantly improve glycemic control in adults with type 1 diabetes, with greater benefits for those with higher baseline HbA1c. Advanced systems demonstrate progressively greater improvements, with automated closed-loop systems showing the strongest evidence of effectiveness. These findings support broader implementation of CGM technologies, with selection tailored to individual patient needs.

Keywords:  Continuous glucose monitoring; Diabetes; Glycemic control; HBA1C; Hyperglycemia

DOI:  https://doi.org/10.1016/j.metop.2025.100382
J Diabetes Sci Technol. 2025 Aug 14. 19322968251353228

CGM Data Analysis 2.0: Functional Data Pattern Recognition and Artificial Intelligence Applications.

David C Klonoff, Richard M Bergenstal, Eda Cengiz, Mark A Clements, Daniel Espes, Juan Espinoza, David Kerr, Boris Kovatchev, David M Maahs, Julia K Mader, Nestoras Mathioudakis, Ahmed A Metwally, Shahid N Shah, Bin Sheng, Michael P Snyder, Guillermo Umpierrez, Mandy M Shao, Agatha F Scheideman, Alessandra T Ayers, Cindy N Ho, Elizabeth Healey.

  New methods of continuous glucose monitoring (CGM) data analysis are emerging that are valuable for interpreting CGM patterns and underlying metabolic physiology. These new methods use functional data analysis and artificial intelligence (AI), including machine learning (ML). Compared to traditional metrics for evaluating CGM tracing results (CGM Data Analysis 1.0), these new methods, which we refer to as CGM Data Analysis 2.0, can provide a more detailed understanding of glucose fluctuations and trends and enable more personalized and effective diabetes management strategies once translated into practical clinical solutions.

Keywords:  CGM; artificial intelligence; diabetes; machine learning; pattern analysis

DOI:  https://doi.org/10.1177/19322968251353228
Diabet Med. 2025 Aug 09. e70119

Effect of switching from intermittently scanned to real-time continuous glucose monitoring on glycaemic outcomes in adults with type 1 diabetes: A real-world, Canadian retrospective study.

Lisa Chu, Alexander Abitbol.

   AIMS: This study investigated the real-world clinical outcomes of switching from intermittently scanned continuous glucose monitoring (isCGM) to real-time CGM (rtCGM) in adults with type 1 diabetes (T1D) from a large Canadian speciality care population.
METHODS: This retrospective observational study examined data from January 1, 2018, through July 31, 2023, in the Canadian LMC Diabetes Registry. The analysis measured 6-12-month change in HbA1c in adults with T1D who switched from isCGM to rtCGM and compared changes to a propensity score-matched isCGM cohort. Changes in number of hypoglycaemic events, CGM metrics, body weight, and total daily dose (TDD) of insulin were also evaluated at 6-12-month follow-up.
RESULTS: The full T1D rtCGM switch cohort comprised of 136 adults (mean: age 43 years, diabetes duration 20.9 years, baseline HbA1c 67 mmol/mol [8.2%]). For the full cohort, HbA1c was significantly lower at follow-up compared to baseline (∆-7 mmol/mol [∆-0.6%], p < 0.001). The propensity score-matched subset (n = 84) of these participants had a greater HbA1c reduction compared to the matched isCGM cohort (n = 84; adjusted mean difference, 5 mmol/mol [0.5%]; p = 0.002). The matched rtCGM switch subset had significantly higher time in range 3.9-10.0 mmol/L and lower time above range >10.0 mmol/L, time below range <3.9 mmol/L, and mean glucose compared to the isCGM cohort. There were no significant differences in hypoglycaemic events, body weight, and insulin TDD between the matched cohorts.
CONCLUSIONS: This real-world analysis of adults with T1D showed that switching from isCGM to rtCGM use led to significant improvements in HbA1c and CGM metrics.

Keywords:  Canada; HbA1c; continuous blood glucose monitoring; hypoglycaemia; type 1 diabetes

DOI:  https://doi.org/10.1111/dme.70119
Sensors (Basel). 2025 Aug 04. pii: 4788. [Epub ahead of print]25(15):

Evaluating Insulin Delivery Systems Using Dynamic Glucose Region Plots and Risk Space Analysis.

Klavs W Hansen, Mia Christensen, Sanne Fisker, Ermina Bach, Bo M Bibby.

  Simultaneous values of glucose rate of change (RoC) and glucose can be presented in a dynamic glucose region plot, and risk spaces can be specified for (RoC, glucose) values expected to remain in the target range (glucose 3.9-10.0 mmol/L) or leave or return to the target range within the next 30 min. We downloaded continuous glucose monitoring (CGM) data for 60 days from persons with type 1 diabetes using two different systems for automated insulin delivery (AID), A (n = 65) or B (n = 85). The relative distribution of (RoC, glucose) values in risk spaces was compared. The fraction of all (RoC, glucose) values anticipated to remain in the target range in the next 30 min was higher with system A (62.5%) than with system B (56.8%) (difference 5.7, 95% CI (2.2-9.2%), p = 0.002). The fraction of (RoC, glucose) values in the target range with a risk of progressing to the above range (glucose > 10.0 mmol/L) was slightly lower in system A than in B (difference -1.1 (95% CI: -1.8--0.5%, p < 0.001). Dynamic glucose region plots and the concept of risk spaces are novel strategies to obtain insight into glucose homeostasis and to demonstrate clinically relevant differences comparing two AID systems.

Keywords:  automated insulin delivery; continuous glucose monitoring; dynamic glucose region plots; glucose rate of change; risk space analysis; type 1 diabetes

DOI:  https://doi.org/10.3390/s25154788
Sensors (Basel). 2025 Jul 26. pii: 4647. [Epub ahead of print]25(15):

Incorporating Uncertainty Estimation and Interpretability in Personalized Glucose Prediction Using the Temporal Fusion Transformer.

Antonio J Rodriguez-Almeida, Carmelo Betancort, Ana M Wägner, Gustavo M Callico, Himar Fabelo, On Behalf Of The Warifa Consortium.

  More than 14% of the world's population suffered from diabetes mellitus in 2022. This metabolic condition is defined by increased blood glucose concentrations. Among the different types of diabetes, type 1 diabetes, caused by a lack of insulin secretion, is particularly challenging to treat. In this regard, automatic glucose level estimation implements Continuous Glucose Monitoring (CGM) devices, showing positive therapeutic outcomes. AI-based glucose prediction has commonly followed a deterministic approach, usually with a lack of interpretability. Therefore, these AI-based methods do not provide enough information in critical decision-making scenarios, like in the medical field. This work intends to provide accurate, interpretable, and personalized glucose prediction using the Temporal Fusion Transformer (TFT), and also includes an uncertainty estimation. The TFT was trained using two databases, an in-house-collected dataset and the OhioT1DM dataset, commonly used for glucose forecasting benchmarking. For both datasets, the set of input features to train the model was varied to assess their impact on model interpretability and prediction performance. Models were evaluated using common prediction metrics, diabetes-specific metrics, uncertainty estimation, and interpretability of the model, including feature importance and attention. The obtained results showed that TFT outperforms existing methods in terms of RMSE by at least 13% for both datasets.

Keywords:  artificial intelligence; deep learning; explainable AI; glucose prediction; mHealth; personalized medicine; transformers

DOI:  https://doi.org/10.3390/s25154647
IEEE J Biomed Health Inform. 2025 Aug 14. PP

Privacy Preserved Blood Glucose Level Cross-Prediction: An Asynchronous Decentralized Federated Learning Approach.

Chengzhe Piao, Taiyu Zhu, Yu Wang, Stephanie E Baldeweg, Paul Taylor, Pantelis Georgiou, Jiahao Sun, Jun Wang, Kezhi Li.

Newly diagnosed Type 1 Diabetes (T1D) patients often struggle to obtain effective Blood Glucose (BG) prediction models due to the lack of sufficient BG data from Continuous Glucose Monitoring (CGM), presenting a significant "cold start" problem in patient care. Utilizing population models to address this challenge is a potential solution, but collecting patient data for training population models in a privacy-conscious manner is challenging, especially given that such data is often stored on personal devices. Considering the privacy protection and addressing the "cold start" problem in diabetes care, we propose "GluADFL", blood Glucose prediction by Asynchronous Decentralized Federated Learning. We compared GluADFL with eight baseline methods using four distinct T1D datasets, comprising 298 participants, which demonstrated its superior performance in accurately predicting BG levels for cross-patient analysis. Furthermore, patients' data might be stored and shared across various communication networks in GluADFL, ranging from highly interconnected (e.g., random, performs the best among others) to more structured topologies (e.g., cluster and ring), suitable for various social networks. The asynchronous training framework supports flexible participation. By adjusting the ratios of inactive participants, we found it remains stable if less than 70% are inactive. Our results confirm that GluADFL offers a practical, privacy-preserved solution for BG prediction in T1D, significantly enhancing the quality of diabetes management.

DOI: https://doi.org/10.1109/JBHI.2025.3573954
Eur J Pediatr. 2025 Aug 15. 184(9): 555

Feasibility of continuous glucose monitoring in children with diabetic ketoacidosis: an exploratory observational study.

Verónica Izquierdo, Nerea Afonso-Bouza, Eva María Montoto-Méndez, Graciela Gómez-Silva, Marcos Pazos-Couselo, Antonio Rodríguez-Nuñez.

  Diabetic ketoacidosis (DKA) is a life-threatening complication of diabetes and a leading cause of Pediatric Intensive Care Unit (PICU) admissions. The use of continuous glucose monitoring (CGM) during the acute and critical phase of DKA has been rarely explored and remains uncertain due to concerns about accuracy and utility in a setting where frequent capillary glucose measurements are standard practice. Data was collected from medical records of patients admitted to the PICU with new-onset DKA as the initial presentation of type 1 diabetes (T1D). Mean absolute relative difference (MARD) and Clarke Error Grid (CEG) analysis were used to assess CGM accuracy. Data from 19 patients (mean age 9.9 ± 3.4 years) were included. Within the first 48 h, 16 hypoglycemic episodes were recorded, with CGM detecting 14 episodes and capillary glucose detecting two. A total of 238 matched pairs of capillary and CGM interstitial glucose values were analyzed. Statistical analysis found capillary glucose values significantly higher than interstitial values (p < 0.001). The overall MARD was 14.5% and CEG analysis indicated 89.1% of matched pairs within zones A and B.
CONCLUSIONS: CGM might be a useful point-of-care tool that provides valuable information that may help clinicians to make timely management decisions. The ability of CGM to indicate trends in glucose fluctuations could be its main clinical advantage, particularly in anticipating and preventing potentially dangerous hypoglycemic events, thereby optimizing patient management and safety.
WHAT IS KNOWN: • DKA emergencies require close glucose monitoring. Standard methods, such as capillary glucose monitoring or venous blood glucose measurements, have some limitations in terms of comfort, frequency, and trend detection. • CGM is currently rarely used in PICU or DKA due to a lack of clinical trials, resulting in uncertainty about its accuracy in pediatric DKA. Additionally, CGM has not been FDA-approved for use in inpatients and to manage diabetes emergencies.
WHAT IS NEW: • CGM may benefit children with DKA from the onset. • DKA management in PICUs by showing glucose trends and enabling hypoglycemia to be detected early, supporting timely interventions, reducing workload, and minimizing patient discomfort through fewer capillary punctures.

Keywords:  Children; Continuous glucose monitoring; Critical Care; Diabetic ketoacidosis; New-onset; Type I diabetes

DOI:  https://doi.org/10.1007/s00431-025-06368-2
Endocr Pract. 2025 Aug 12. pii: S1530-891X(25)00997-8. [Epub ahead of print]

Diabetes Technology and the Older Adult: Clinical Outcomes and Implementation Strategies.

Kenyin Loo Urbina, Christine Slyne, Medha N Munshi.

  The prevalence of diabetes among older adults continues to rise. Aging brings unique challenges to the management of diabetes in older adults, as treatment goals and patients' ability to reach those goals depend on overall health status and support systems, which can change frequently in this population. In addition, hypoglycemia has severe consequences in the older population and remains a limiting factor in our ability to improve glycemic control. Recent advancements in diabetes technology-such as smart insulin pens, continuous glucose monitoring, and hybrid closed-loop insulin pump systems-offer improved glycemic control and reduced risk of hypoglycemia in all adults, although available evidence often excludes older adults with frailty or cognitive impairment. Recent studies of technology use in relatively healthy older adults have demonstrated benefits, including higher time in range, less severe hypoglycemia, and enhanced satisfaction. Careful patient selection, comprehensive education, and caregiver support are crucial to the successful use of technology by older adults with diabetes. By applying a geriatric-focused approach, which balances modern technology with the individual's functional status, cognition, and comorbidities, clinicians can optimize safety and efficacy in managing diabetes in older adults. This approach should be applied regardless of diabetes type or the patient's degree of frailty.

Keywords:  Diabetes Technology; Older adult; Type 1 Diabetes; Type 2 Diabetes

DOI:  https://doi.org/10.1016/j.eprac.2025.08.004
Clin Nutr ESPEN. 2025 Aug 12. pii: S2405-4577(25)02893-1. [Epub ahead of print]

Dietary intakes and physical activity of women with gestational diabetes are not associated with continuous glucose monitoring metrics; Secondary analysis of the DiGest trial.

Danielle L Jones, Laura C Kusinski, Lewis Griffiths, Kirsten L Rennie, Linda M Oude Griep, Claire L Meek.

   BACKGROUND: Diet and lifestyle modifications are key to managing gestational diabetes mellitus (GDM), yet current dietary recommendations lack detail. It remains unclear what the dietary intakes or physical activity of pregnant women with GDM are or to what extent these alter glycaemic control.
AIMS: To describe dietary intake, diet quality, and PA patterns in women diagnosed with GDM and assess their associations with continuous glucose monitoring (CGM) metrics.
METHODS: This secondary, cross-sectional analysis of the Dietary Intervention in Gestational Diabetes (DiGest) trial included 425 pregnant women with GDM (BMI >25 kg/m2) at 28 weeks' gestation, recruited for an 8-12-week dietary intervention. Baseline dietary intake and PA were assessed through self-reported, validated questionnaires. Diet quality was evaluated using adherence to the Dietary Approaches to Stop Hypertension (DASH) diet (score range: 8-40). A masked Dexcom G6 CGM device was worn for up to 10 days to measure mean glucose (mmol/L), coefficient of variation (%), and the percentage of time spent in, above, and below the target glucose range (3.5-7.8 mmol/L). Associations between dietary intake, DASH score, and physical activity were examined using linear regression.
RESULTS: Across 223 dietary recalls, mean (SD) intakes included energy (1571 (666) kcal); carbohydrates (157g (86)); fibre; (19g (10)); protein; (77g (34)) and fat (75g (39)). Median physical activity energy expenditure (PAEE) was 18.62 kJ/kg/d. No significant associations were found between dietary intake, diet quality, PA, and CGM metrics.
CONCLUSIONS: Women with GDM consumed a diet low in calories, carbohydrates, and fibre but high in saturated fat. PAEE was lower than the background, non-pregnant female population. Diet and PA were not associated with CGM metrics, highlighting the need for optimisation to short-term and long-term metabolic function in women with GDM.

Keywords:  continuous glucose monitoring; diet; gestational diabetes; physical activity

DOI:  https://doi.org/10.1016/j.clnesp.2025.08.007
Kaohsiung J Med Sci. 2025 Aug 13. e70090

Correction to "Effects of Insulin Glargine U300 Versus Insulin Degludec U100 on Glycemic Variability, Hypoglycemia, and Diet Evaluated by Continuous Glucose Monitoring in Type 1 Diabetes: A Retrospective Cross-Sectional Study".

DOI: https://doi.org/10.1002/kjm2.70090
Diabetol Metab Syndr. 2025 Aug 14. 17(1): 332

Impaired central thyroid hormone sensitivity is associated with time in range in patients with type 2 diabetes mellitus in the euthyroid population.

Xu Jiang, Yu Gong, Guojuan Wang, Ying Li.

   OBJECTIVE: To investigate the correlation between central thyroid hormone (TH) sensitivity and time in target glucose range (TIR) in patients with type 2 diabetes mellitus (T2DM).
METHODS: 483 enrolled inpatients with T2DM were collected with the continuous glucose monitoring (CGM) data and clinical characteristics. Thyroid stimulating hormone index (TSHI), thyrotropin-thyroxine resistance index (TT4RI) and thyroid feedback quantile index (TFQI) were calculated. The correlations between TSHI, TT4RI, TFQI and TIR were statistically analyzed.
RESULTS: The levels of FT4, TSHI, TT4RI and TFQI in TIR > 70% group were all higher compared with TIR ≤ 70% group (all P < 0.05). TSHI was positively correlated with TIR before the inflection point of 2.2 (β = 14.8, P < 0.001), and the correlation strengthened after there (β = 30.9, P < 0.001). TT4RI was positively correlated with TIR before the inflection point of 32 (β = 1.3, P < 0.001), and the correlation weakened after there (β = 0.7, P < 0.001). TFQI was not correlated with TIR before the inflection point of -0.6 (P = 0.302), but was positively correlated with TIR after there (β = 28.7, P < 0.001). For one-quartile increase in TSHI and TFQI, the odds of TIR-target (TIR > 70%) increased by 0.825 times and 1.3891 times respectively.
CONCLUSION: Decreased central TH sensitivity, namely increased TH resistance, is associated with elevated TIR, suggesting that central TH resistance maybe a protective factor for TIR.

Keywords:  Continuous glucose monitoring; Thyroid hormone sensitivity; Time in target range; Type 2 diabetes mellitus

DOI:  https://doi.org/10.1186/s13098-025-01911-5
J Diabetes Res. 2025 ;2025 5547910

Continuous Glucose Monitoring-Enhanced eConsult Improves Clinical Outcomes in Adults Living With Diabetes in a Safety Net Primary Care Setting.

Samantha M Siskind, Ryanne Dymek, Kathryn L Fantasia, Katelyn O'Brien, Devin W Steenkamp.

  Background: There is a shortage of endocrinologists providing diabetes care. Electronic consultation (eConsult) improves access to subspecialty care, but the evaluation of CGM-enhanced eConsults in routine clinical practice has not been reported. We evaluated clinical outcomes after implementing a CGM-enhanced eConsult program in a safety-net hospital primary care clinic. Methods: We completed a retrospective observational study assessing the clinical impact of the eConsult program. Participants included 67 adults (≥ 18 years) living with diabetes, receiving primary care at Boston Medical Center (mean age 65 years, 40.3% male, 79.1% Black, and 92.5% Type 2 diabetes). Demographic, clinical, and CGM data were analyzed from the medical record and Abbott's LibreView and Dexcom's Clarity web-based applications. Descriptive outcomes within 6 months post-eConsult included time to eConsult completion, hemoglobin A1c (HbA1c) change, medication adjustments, CGM prescription rates, and CGM-derived hypoglycemic metrics. Results: Mean time to eConsult completion was 5.8 days. Endocrinologist recommendations were implemented in 86.6% of patients at the first primary care visit post-eConsult and in 94.0% of patients within 6 months. Within 6 months, HbA1c was unchanged (mean change 0.2% ± 0.4%). Relative to baseline, sulfonylurea prescription decreased 55.6%. The percentage of those prescribed basal insulin was unchanged, but basal insulin doses decreased in 41.8% of patients. Bolus insulin prescription increased 56.3% relative to baseline. Absolute CGM prescriptions increased from 2.9% at baseline to 49.3%. In 11 CGM users with sufficient CGM data for interpretation at 6 months, Level 1 hypoglycemia (54-69 mg/dL) decreased by 2% and Level 2 hypoglycemia (< 54 mg/dL) decreased by 0.7%. Conclusion: In adults living with diabetes cared for in a safety-net hospital, CGM-enhanced eConsult provides timely access to endocrinologist expertise, recommendations are widely implemented by primary care clinicians, and guideline-directed modern diabetes therapeutic use increases, including a 17-fold increase in personal CGM prescriptions.

Keywords:  continuous glucose monitoring; electronic consultation

DOI:  https://doi.org/10.1155/jdr/5547910
Swiss Med Wkly. 2025 Aug 14. 155 4665

Swiss recommendations on driving ability in patients with diabetes mellitus.

Roger Lehmann, Sandrina Bervini, Vojtech Pavlicek, Regula Wick, Barbara Lucchini, Ulrike Iten, Lia Bally.

Most people with diabetes mellitus operate motor vehicles safely without creating any meaningful risk on the road for themselves or others. A diagnosis of diabetes is, in itself, inadequate for determining a person's driving capability or safety. Diabetes-related traffic accidents are rare for most drivers with diabetes mellitus and occur less frequently than for many other diseases that can impair driving performance and that are tolerated by society. The incidence of hypoglycaemia, which impairs the ability to drive, severe retinopathy (including macular oedema) or cataract formation affecting visual acuity required to drive a motor vehicle, and peripheral neuropathy, which can severely impair sensation in the feet, is not so common as to justify restricting driving privileges for all drivers with diabetes mellitus. In recent years, several pharmacological and technological innovations have revolutionised diabetes care. Continuous glucose monitoring system (CGMS) technology has only recently become increasingly integrated into diabetes therapy. Today, except for insulin, none of the treatments recommended for type 2 diabetes mellitus causes hypoglycaemia, and the risk of hypoglycaemia with ultra-long-acting insulins is lower. As a result, recommendations for driving motor vehicles have had to be adjusted. Since hypoglycaemia is the greatest risk factor for impaired driving ability, the latest technology (CGMS coupled with hybrid closed-loop insulin pumps) can reduce the number of hypoglycaemic events and blood glucose fluctuations. In addition, HbA1c and time in target range can be improved. Patients with type 1 diabetes mellitus are now, in exceptional cases, allowed to be licensed in higher vehicle categories. With the analysis of CGMS data, an objective assessment of the frequency of hypoglycaemia is now possible; this was previously only partially possible with blood glucose logs. Patients who are treated with insulin should use a CGMS. This also applies to gestational diabetes and diabetes during pregnancy. Since these systems warn of impending hypoglycaemia, they will also improve road safety, and the safety margin for blood glucose, previously set at 5 mmol/l, can be lowered to 4 mmol/l. For CGMS users, blood glucose measurements every 2 hours while driving are no longer necessary.

DOI: https://doi.org/10.57187/s.4665
J Health Equity. 2025 ;pii: 2444002. [Epub ahead of print]2(1):

Race and ethnic disparities in insulin pump and continuous glucose monitor use between 2017 and 2024: a systematic review with a focus on health equity.

Patricia C Underwood, Kathryn Chirokas, Jordan Keels, Varsha G Vimalananda, Cherlie Magny-Normilus.

  Diabetes mellitus (DM) technology (i.e., continuous glucose monitors (CGMs) and insulin pumps) can improve clinical outcomes and use is on the rise. However, some studies highlight disparities in DM technology prescription rates across various race/ethnicity groups. Specifically, recent studies note baseline DM technology use was significantly lower for Black patients compared to their non-Black counterparts. This systematic review examined the available evidence on the association of prescription rates for DM technology (CGM and insulin pumps) use by race/ethnicity. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-analysis- Equity guidelines (PRISMA-Equity), a literature search of observational studies published between 2017-2024 was conducted using Medline, Cochrane, PubMed, CINAHL, and Embase databases. Articles were included if they reported data on DM technology use by race/ethnicity. All studies reported significant differences in DM technology use by race/ethnicity; with White non-Hispanic (WNH) patients having the highest prescription rates (average 56.3% (range 12-79%)), followed by patients that identify as Hispanic (average 28.8% (range 4-76%)), and Black (average 21.3% (range 3-52%)). Secondary analyses examining the influence of glycemic control, patient experience, and social determinants of health (SDoH) on the relationship between race/ethnicity and DM technology use were conducted. Limitations of included studies are discussed including 1) inaccurate measurements of race and ethnicity that failed to identify the contextual detail of ethnicity and 2) limited measurements of health outcomes and SDoH. Further research is needed to more accurately examine the social and environmental factors that influence the identified race/ethnicity disparities and to develop strategies that ensure equitable access to beneficial DM technology.

Keywords:  continuous glucose monitor; diabetes; diabetes technology; insulin pump; race and ethnic disparities

DOI:  https://doi.org/10.1080/29944694.2024.2444002
Ann Surg. 2025 Aug 12.

Risk of Recurrent Hypoglycemia and Long-term Survival after total Pancreatectomy: A Prospective Observational Study.

Zofia Czarnecka, Kevin Verhoeff, Alice L J Carr, Anna Lam, Peter Senior, Robin Lucciantonio, Tatsuya Kin, Andrew R Pepper, David L Bigam, Khaled Dajani, Blaire Anderson, A M James Shapiro.

   OBJECTIVE: To evaluate risk of severe hypoglycemia after total pancreatectomy (TP).
BACKGROUND: Historically, TP was feared due to loss of insulin and counter-regulatory hormones, as well as the risk of severe hypoglycemic events (SHE). While TP with islet auto-transplant (TPIAT) can preserve endocrine function, past studies reported 41% SHE incidence post-operatively. Advancements in insulin therapies and continuous glucose monitors (CGMs) have likely improved outcomes but are understudied in this population.
METHODS: This single center study analyzed TP patients from 2009-2024. CGMs (Dexcom G7) were provided for the study if patients did not have one. Demographics, survival, emergency department visits, and glycemic control were assessed.
RESULTS: Among 147 TP cases, 76 underwent TP alone and 71 TPIAT. In the TP-alone patients, two deaths (2/76; 2.63%) occurred due to hypoglycemia. Pre-operatively, TP-alone patients had higher HbA1c (7.1±2.2%) than TPIAT patients (5.9±1.3%; P<0.001). In the first month post-operatively, TP-alone patients had higher HbA1c than TPIAT-insulin dependent patients, but no difference over 10 years. Hypo/hyperglycemia-related hospital visits, median time in target range (TP: 53.5%, IQR: 36.5-68.5 vs. TPIAT insulin-dependent: 59.0%, IQR: 43.3-67.5), and glycemic variability (coefficient of variation; 31.3%, IQR 28.3-35.0 vs 32.3%, IQR 28.7-35.5) were similar between TP-alone and TPIAT-insulin dependent groups. In 14 days of CGM capture, no severe hypoglycemia was observed in TP-alone patients (<3.0 mmol/L).
CONCLUSIONS: Advancements in insulins and CGMs provide acceptable outcomes after TP without supplemental islet transplantation, and lower risk of SHE than previously reported. This encouraging data may aid surgical decision-making and patient selection for surgery.

Keywords:  continuous glucose monitor; diabetes; hypoglycemias; islet transplantation; pancreatectomy; post-operative outcomes

DOI:  https://doi.org/10.1097/SLA.0000000000006909
Can J Diabetes. 2025 Aug 12. pii: S1499-2671(25)00162-5. [Epub ahead of print]

The assessment of clinical factors influencing Glucose Management Indicator and Hba1c discordance in children with type one diabetes - one-year real-world data observation.

Grażyna Deja, Aleksandra Brudzińska, Łukasz Wybrańczyk, Rafal Deja, Przemysława Jarosz-Chobot.

   OBJECTIVES: Published data still highlighted discordances between GMI (parameter estimating HbA1c from CGM report) and laboratory HbA1c, with reasons yet to be explored. This study aimed: to identify potential clinical factors contributing to these discordances.
METHODS: A retrospective study of 99 children aged 12.92 (SD 4.03) using CGM devices (Dexcom G6-31, Libre 2-30, Guardian 3-38) was conducted. Inclusion criteria were: type 1 diabetes, continuous use of one type of CGM (with >70% sensor activity) over the last year, quarterly visits. At each visit, we collected data: age, sex, BMI, diabetes duration, daily insulin dose, CGM report (14/90 days) and laboratory HbA1c.
RESULTS: We confirmed linear dependency between HbA1c and GMI - higher HbA1c led to more HbA1c-GMI differences. The HbA1c-GMI 90 days discordance was categorized into four thresholds: 48.7% <0.25, 20.1% in the range 0.25-0.5, 22.4% in 0.5-0.75, and 8.7% >0.75. Children with HbA1c-GMI 90 discordance <0.5% had significantly lower HbA1c (6.80 vs 7.59%), shorter T1D duration (<5 years) and more stable HbA1c (differences <0.4 between results). The analysis of participants stability, based on comparing HbA1c-GMI 90 discordances at subsequent follow-up visits confirmed the individual variability <0.25 in two-thirds of participants. Other factors were not associated with the HbA1c-GMI discordance.
CONCLUSION: One-year real-world data showed that clinically significant discordances (HbA1c-GMI 90 >0.5%) occurred in less than 30% children. Higher difference is more likely in individuals with higher HbA1c values, longer diabetes duration, and less stable glycemic control. Individual discordance HbA1c-GMI 90 is rather stable, although with varying degrees of difference.

Keywords:  CGM; GMI; HbA1c; continuous glucose monitoring systems; eHbA1c; glucose management indicator

DOI:  https://doi.org/10.1016/j.jcjd.2025.08.002
Diabetes Technol Ther. 2025 Aug 13.

Cost Analysis of the FreeStyle Libre Systems in People with Type 2 Diabetes Mellitus on Basal Insulin with Poor Glycemic Control: A Spanish Perspective.

Francisco Javier Ampudia-Blasco, Alberto de la Cuadra-Grande, Virginia Bellido, Ana María Cebrián-Cuenca, Pedro Mezquita-Raya, Juana Carretero-Gómez, Antonio-Miguel Hernández Martínez, Itziar Oyagüez, Fernando Gómez-Peralta.

  Background and Aims: FreeStyle Libre® systems are effective and convenient glucose flash monitoring (FM) devices. This cost analysis compared FM versus self-monitoring of blood glucose (SMBG) in poorly controlled (glycated hemoglobin [HbA1c] >8%) patients with type 2 diabetes (T2D) on basal insulin in Spain. Methods: A model was used to compare the costs of FM and SMBG in a 1000-patient cohort. All model inputs were sourced from scientific literature and validated by a multidisciplinary experts' group. Unitary costs were included in euros (2025), including value-added tax (VAT). The daily use of 2.5 strips (€0.57/strip) and 2.5 lancets (€0.14/lancet) was considered for SMBG according to Spanish recommendations. The events/person-year was 2.5 for severe hypoglycemic events (SHEs) (€1403.03/event), 17.02 for non-SHEs (NSHEs) (€3.92/event), and 0.0025 for diabetic ketoacidosis (DKA) (€2523.93/event). FM reduced the use of strips/lancets (-83.0%; sensor: €3.00/day) and acute events (NSHEs/SHEs: -58.0%; DKA: -68.0%). Sensitivity analyses were conducted to test robustness. Two additional scenarios were studied, including chronic diabetic complications (absolute reduction in HbA1c with FM: -1.1%) and absenteeism-related costs (reduction in absenteeism with FM: -58.4%). Results: The annual cost per patient was €3299.99 with SMBG and €2320.20 with FM. In 1000 patients, FM averted 2162 NSHEs (FM vs. SMBG: -€66,672), 1450 SHEs (FM vs. SMBG: -€2,579,224), and 1.5 DKA (FM vs. SMBG: -€6310), producing total cost savings of €979.706 compared with SMBG. All sensitivity analyses confirmed cost savings of FM versus SMBG, even when strips/lancets were free (-€442,117) or assuming a lower SHE frequency (1.4 events/patient-year; -€321,488). In 1000 patients, when considering chronic diabetic complications (SMBG: €3,745,869; FM: €2,886,785) and absenteeism (SMBG: €237,990; FM: €99,004), the annual cost savings of FM versus SMBG rose to €1,997,777. Conclusions: FreeStyle Libre could reduce acute events, chronic diabetic complications, and work absenteeism in poorly controlled patients with T2D on basal insulin, generating cost savings for the Spanish health system and society.

Keywords:  continuous glucose monitoring; cost analysis; diabetic ketoacidosis; flash glucose monitoring; hypoglycemia; type 2 diabetes

DOI:  https://doi.org/10.1177/15209156251363576