bims-glumda 2026-07-26 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2026–07–26
twenty-one papers selected by
Mott Given

It's a game changer in terms of diabetic management': A qualitative study of adolescents' and parents' experiences of a 6-month trial of continuous glucose monitoring in type 2 diabetes.
Trends in Glycemia Risk Index Over Time in Patients With Diabetes and Cancer Undergoing Remote Continuous Glucose Monitoring.
Continuous glucose monitoring for high-risk type 2 diabetes in the hospital: the cyber GEMS randomized controlled trial protocol.
Beyond Coverage Expansion: Exploring Persistent Barriers to CGM Utilization in the Clinical Environment.
Continuous Glucose Monitoring in Older-Old With Type 2 Diabetes Mellitus: A Narrative Review of Evidence and Recommendations.
Continuous Glucose Monitoring Metrics in Women with Type 2 Diabetes in Pregnancy: The TIMELY Observational Cohort Study.
The Evolving Landscape of Continuous Glucose Monitoring Metrics in Type 1 Diabetes: Narrative Literature Review.
Comment on Kok et al. Impact of Missing Data and Monitoring Duration on Downstream Analyses in Continuous Glucose Monitoring.
Continuous Glucose Monitoring Data Compression Using Peak-Nadir Encoding in Diabetes: Method Development and Evaluation.
Real-time continuous glucose monitoring related to reductions in inpatient and emergency department encounters and their associated costs among non-insulin-treated people with type 2 diabetes.
Variability in magnitude and direction of discordance between continuous glucose monitoring (CGM) metrics and traditional biomarkers in patients with diabetes and end-stage kidney disease (ESKD): A case series.
Performance, Safety and Usability of a Third-Generation Continuous Glucose Monitoring System in a Pediatric Population: Results From a Prospective, Multicenter Study.
Association Between Time in Range and Advanced Cardiovascular-Kidney-Metabolic Syndrome in Older Adults With Type 2 Diabetes.
Discharge Remote Monitoring Systems for Glycemic Management After Hospital Discharge.
Metabolomic signatures of glycemic control in type 1 diabetes: insights from continuous glucose monitoring.
Contemporary Diabetes Technology and the Patient Experience.
Digital phenotyping of CGM engagement reveals distinct glycemic outcomes.
Glycaemia risk index and continuous glucose monitoring metrics across menstrual cycle phases in women with type 1 diabetes using automated insulin delivery.
Numerical and Clinical Accuracy of the FreeStyle Libre 2 System: A Diagnostic Accuracy Study in Critically Ill Patients.
Piloting a Postdischarge Virtual Glucose Monitoring Program for Patients With Diabetic Foot Wound in a Safety-Net Health System.
Acute mild cold exposure with shivering reduces 24 h glucose levels in individuals with type 2 diabetes but not prediabetes.

Diabet Med. 2026 Jul 22. e70430

It's a game changer in terms of diabetic management': A qualitative study of adolescents' and parents' experiences of a 6-month trial of continuous glucose monitoring in type 2 diabetes.

Maheesha Fernando, Alexia S Peña, Ashlee King, Melissa Oxlad.

   AIM: To qualitatively explore adolescents with type 2 diabetes (T2D) using any treatment regimen and parents of such adolescents' experiences of a 6-month trial of continuous glucose monitoring (CGM) and its perceived barriers and facilitators.
METHODS: Adolescents provided with CGM sensors (Freestyle Libre 2) free of charge for 6 months and parents recruited from the outpatient paediatric diabetes clinic at the Women's and Children's Hospital, South Australia participated. Four adolescents and six parents participated in a separate focus group or a semi-structured interview within 1 month (baseline) of CGM use; three adolescents and four parents participated in a focus group after 6 months of CGM use. Data were analysed using reflexive thematic analysis.
RESULTS: We generated four themes: (1) A Convenient and Practical Tool for Adolescent Monitoring, Self-Management, Education, and Behaviour Change; (2) Enhanced Parental Diabetes Oversight and Reduced Family Emotional Burden; (3) Psychosocial, Practical, and Affordability Barriers to Adolescent CGM Use; (4) Education, Improved Adhesion, and Supportive School Environments as Facilitators of Adolescent CGM Use.
CONCLUSIONS: Adolescents with T2D and parents perceived CGM as a more acceptable and convenient tool than finger prick blood glucose monitoring. CGM benefits included facilitating education, improving self-management skills, and promoting behavioural modification. CGM was also perceived to reduce families' emotional burden associated with diabetes management. Device limitations, including technology accuracy, alarms, and adhesion issues, posed challenges for families. Equitable access and funding models were the main barriers to the wider adoption of CGM in this population within Australia.

Keywords:  adolescents; continuous glucose monitoring; sensor qualitative; teenagers; type 2 diabetes

DOI:  https://doi.org/10.1111/dme.70430
J Diabetes Sci Technol. 2026 Jul 23. 19322968261470745

Trends in Glycemia Risk Index Over Time in Patients With Diabetes and Cancer Undergoing Remote Continuous Glucose Monitoring.

Deborah A Osafehinti, Sonali Thosani, Steven P Weitzman.

   BACKGROUND: Continuous glucose monitoring (CGM) is increasingly used in patients with cancer, a population in whom HbA1c may be unreliable. The Glycemia Risk Index (GRI) is a CGM-derived measure integrating hypoglycemia and hyperglycemia risk. We evaluated trends in GRI and other CGM metrics among adults followed in a remote CGM (RCGM) clinic.
METHODS: Retrospective chart review of adults (≥18 years) with diabetes and cancer seen at a comprehensive cancer center in 2024. Eligible patients had ≥2 CGM assessments (≥1 RCGM) and a baseline glucose management indicator (GMI) or HbA1c ≥8.0%. Generalized linear mixed models examined the effects of visit sequence (time) and RCGM use on GRI, GMI, average glucose, time in range (TIR), time above range (TAR), and time below range (TBR). Pre-specified conservative and liberal noninferiority margins were applied to the remote-use effect.
RESULTS: Forty-two patients (mean age 60.2 ± 10.6 years; 95% type 2 diabetes) were included. At baseline, mean GRI was 70 ± 27, GMI 8.5% ± 1.1%, average glucose 214 ± 46 mg/dL, TIR 38% ± 21%, TAR 61% ± 21%, and TBR 1% ± 1%. Across sequential assessments, GRI, GMI, average glucose, and TAR decreased, whereas TIR increased (all P < .05). Remote CGM did not predict any glycemic outcome. Under liberal margins, RCGM was noninferior to nonremote review for GRI, GMI, TIR, and TAR, and noninferior for TBR under both conservative and liberal margins.
CONCLUSIONS: Sequential CGM review was associated with improved glycemic quality in adults with diabetes and cancer. Remote CGM achieved glycemic outcomes comparable with nonremote review, supporting its use as a viable adjunct to in-person visits in the oncology setting.

Keywords:  ambulatory glucose profile; diabetes mellitus; interstitial glucose; time in range

DOI:  https://doi.org/10.1177/19322968261470745
Contemp Clin Trials. 2026 Jul 24. pii: S1551-7144(26)00197-7. [Epub ahead of print] 108411

Continuous glucose monitoring for high-risk type 2 diabetes in the hospital: the cyber GEMS randomized controlled trial protocol.

Samantha R Spierling Bagsic, Addie L Fortmann, Alessandra Bastian, Rebekah Belasco, Haley Sandoval, Suzanne Lohnes, Emily San Diego, Laura Talavera, Athena Philis-Tsimikas.

   BACKGROUND: Continuous glucose monitoring (CGM) for inpatient management of type 2 diabetes (T2D) has been supported by small pilot studies and few randomized controlled trials. The Cloud-Based Real-Time Glucose Evaluation and Management System (Cyber GEMS) trial tests whether real-time CGM can improve time in, above, and below target glycemic range, and reduce hospital acquired infections.
METHODS: This in-progress study enrolls at 2 large disproportionate-share hospitals in Southern CA. Eligible patients are ≥18 years with T2D and on subcutaneous insulin or with 2+ serum or POCT glucose ≥200 mg/dL. Participants are randomized to usual care (UC) or Cyber GEMS with real-time CGM for glucose monitoring and management. In Cyber GEMS, the CGM transmits values to three platforms for (1) remote hypoglycemia monitoring (Digital Dashboard); (2) real-time management by bedside RN on a hospital unit iPad (FOLLOW app); and (3) clinical optimization by a remote diabetes RN specialist (CLARITY). In UC, a masked CGM is utilized for outcome evaluation purposes only. The study aims to determine the effectiveness of Cyber GEMS compared to UC in improving CGM-measured % time in-range (70-200 mg/dL), hypoglycemia (<70 mg/dL) and severe hyperglycemia (>300 mg/dL), as well as reducing hospital acquired infection in N = 554 adults with T2D.
DISCUSSION: The Cyber GEMS protocol is uniquely designed to evaluate the value and utility of real-time CGM for optimizing hospital glucose management in a high-risk, underserved T2D population. The uninterrupted remote monitoring, coupled with diabetes specialist oversight, aims to maximize the use of real-time CGM data for optimal glucose management in T2D. The study is in progress and reaching a high-risk underserved population.
TRIALS REGISTRATION: NCT05307237 Study Details|Continuous Glucose Monitoring for High-Risk Type 2 Diabetes in the Hospital (Cyber GEMS)|ClinicalTrials.gov.

Keywords:  CGM; Continuous glucose monitoring; Diabetes; Glucose management; Hospital; Hospital-acquired infections; Inpatient

DOI:  https://doi.org/10.1016/j.cct.2026.108411
Diabetes Ther. 2026 Jul 23.

Beyond Coverage Expansion: Exploring Persistent Barriers to CGM Utilization in the Clinical Environment.

Consuela Coni Dennis, Victoria Bouhairie.

  Continuous glucose monitoring (CGM) improves glycemic control and reduces acute events, yet adoption remains low despite expanded coverage. Real-world evidence shows that most eligible patients do not use CGMs, highlighting a gap between access and utilization. This commentary examines key barriers, including provider knowledge gaps, administrative complexity, workflow constraints, and persistent socioeconomic inequities. We argue that coverage expansion alone is insufficient to drive uptake. Coordinated strategies that support prescriber education, streamline processes, and integrate CGM into routine care are needed. Addressing these systemic and behavioral barriers is essential to realizing the full clinical and economic benefits of CGM at scale.

Keywords:  CGM utilization; Continuous glucose monitoring; Diabetes management; Digital health; Glycemic control; Health disparities; Patient adherence; Primary care

DOI:  https://doi.org/10.1007/s13300-026-01894-0
Diabetes Obes Metab. 2026 Jul 19.

Continuous Glucose Monitoring in Older-Old With Type 2 Diabetes Mellitus: A Narrative Review of Evidence and Recommendations.

Patrice Darmon, Anne-Sophie Boureau, Bernard Bauduceau, Judith Charbit, Benjamin Bouillet, Kamel Mohammedi, Bruno Guerci, Olivier Hanon.

  The global rise in Type 2 diabetes mellitus (T2DM) is increasingly driven by population aging; nearly one in four adults with diabetes is now aged 65 years or older. Older adults with T2DM, particularly, those on insulin, face heightened risks of hypoglycaemia, glycaemic variability and diabetes-related complications, contributing to functional decline, impaired quality of life and increased mortality. Conventional glycaemic assessment with glycated haemoglobin (HbA1c) inadequately captures clinically relevant glucose fluctuations, especially asymptomatic and nocturnal hypoglycaemia, which are common yet frequently unrecognised in this population. Continuous glucose monitoring (CGM) has emerged as a major advance in diabetes care, enabling real-time assessment of glucose trends and providing detailed metrics, such as time in range, that offer a more comprehensive picture of glycaemic control. Growing evidence links CGM use in older adults with T2DM to reductions in hypoglycaemia, improved glycaemic metrics and enhanced treatment satisfaction and quality of life. These benefits are, particularly, relevant in vulnerable subgroups, including adults aged ≥ 75 years, individuals with cognitive impairment or frailty and long-term care residents, where unrecognised hypoglycaemia and therapeutic inertia are especially prevalent. Despite growing guideline support, CGM adoption in routine care remains limited due to clinical, logistical, age-related and socioeconomic barriers. This narrative review summarises current evidence and clinical recommendations for CGM use in older adults with T2DM, focusing primarily on those aged ≥ 75 years and discusses implementation challenges and strategies to optimise its integration into individualised diabetes care.

Keywords:  Type 2 diabetes; continuous glucose monitoring; elderly; glycemic control; hypoglycaemia; long‐standing disease

DOI:  https://doi.org/10.1111/dom.71118
Diabetes Technol Ther. 2026 Jul 21. 15209156261470491

Continuous Glucose Monitoring Metrics in Women with Type 2 Diabetes in Pregnancy: The TIMELY Observational Cohort Study.

Denice S Feig, Jennifer M Yamamoto, Afshan Zahedi, Eleanor M Scott, Sonia Masuta, George Tomlinson.

   BACKGROUND: Continuous glucose monitoring (CGM) is increasingly used in pregnancy, but data on its use in women with type 2 diabetes are limited.
AIMS: To describe CGM metrics in pregnant women with type 2 diabetes and assess their association with neonatal outcomes.
METHODS: We conducted a prospective, observational cohort study of women with type 2 diabetes, enrolled before 26 weeks of gestation. Participants wore a Dexcom G6 sensor for at least 10 days per trimester. Maternal characteristics and pregnancy outcomes were collected.
RESULTS: We recruited 50 women with type 2 diabetes in pregnancy from three diabetes in pregnancy clinics. Women were enrolled at a mean of 16 weeks of gestation, 83% were non-European ethnicity and 74% wore the CGM >80% of the time from enrollment. Participants spent a mean of 73.0% of time in the pregnancy range (TIRp) (3.5-7.8 mmol/L), 25.6% above range (TARp), 1.5% below range, with a mean glucose of 6.8 (1.0) mmol/L across pregnancy. Lower TIRp, higher TARp, and higher mean glucose were significantly associated with large-for-gestational-age (LGA) infants. Mean glucose was significantly higher in those with an LGA infant from 12 weeks onward. LGA was significantly more frequent in those who spent ≤70% TIRp than in those who spent >70% TIRp (46.7% vs. 10.3%; P = 0.02). TARp >30% was significantly associated with the composite neonatal outcome. More than 20% TARp overnight was significantly associated with LGA. A 5% improvement in TIRp reduced LGA by 28% (odds ratio 0.72 [0.54, 0.90; P = 0.009]). Diabetes distress at enrollment was associated with a significantly lower TIRp and higher mean glucose throughout pregnancy.
CONCLUSIONS: Several glycemic metrics, including TIRp and mean glucose, were associated with LGA. Higher glucose levels from 12 weeks onward were seen in mothers of LGA infants. Early pregnancy or preconception glucose optimization may be necessary to improve outcomes.

Keywords:  continuous glucose monitoring; pregnancy; pregnancy complications; type 2 diabetes

DOI:  https://doi.org/10.1177/15209156261470491
JMIR Diabetes. 2026 Jul 23. 11 e92455

The Evolving Landscape of Continuous Glucose Monitoring Metrics in Type 1 Diabetes: Narrative Literature Review.

Eric Williams, Casey Rand, Alessandra Ayers, Cindy Ho, Ashley Dunova, David Klonoff, Juan Espinoza.

   Background: Continuous glucose monitoring (CGM) has transformed diabetes management and research by providing high-frequency data that address many of the limitations of hemoglobin A1c, enabling more precise clinical treatment targets and responsive trial endpoints. The richness and complexity of high-resolution time-series CGM data have spurred the development of numerous metrics for both clinical care and research applications. Beyond established metrics, there is a growing set of clinical, composite, and research-oriented measures that may support clinical decision support, intervention planning, risk stratification, and discovery-oriented research. This proliferation has created significant challenges in metric selection, interpretation, calculation, and standardization, particularly when metrics are applied across different devices, populations, software packages, and study designs.
Objective: The objective is to map the current landscape of CGM metrics and address ongoing challenges in metric selection, clinical and research interpretation, and standardization. We further sought to distinguish between metrics primarily suited for routine clinical interpretation and those designed to explore more granular or multidimensional features of glycemia in research settings.
Methods: We identified the literature focusing on the calculation, application, and interpretation of the following categories of CGM metrics: (1) standardized, (2) clinical, (3) emerging, and (4) composite. CGM metrics included in this study were identified from the 27 metrics included in the Diabetes Research Hub platform, additional published standardized and composite metrics, metrics used in established CGM analysis software, and emerging metrics identified during review. We narratively reviewed each metric's definitions, calculation methods, interpretation, clinical and research utility, and strengths and limitations. In total, 102 articles were reviewed, supporting the synthesis of 36 distinct CGM-derived metrics.
Results: The review identifies a fundamental divide in the CGM metric landscape. Standardized and clinical metrics, including time in range, mean glucose, coefficient of variation, and similar, prioritize simplicity and actionability. These metrics facilitate rapid decision-making in clinical settings but potentially mask granular glycemic fluctuations, event patterns, and discordance between average glucose values and variability. Emerging and composite metrics offer deeper insights into glycemic patterns, risk, and variability. However, many rely on specialized software or complex formulas, lack standardized thresholds or clear relationships to clinical outcomes, and do not have consensus methods of calculation and interpretation, limiting their adoption and hindering cross-study comparison.
Conclusions: While consensus exists for core clinical metrics, the lack of standardization for complex metrics hinders research replicability and clinical translation. Bridging this gap requires moving toward consensus metric definitions, open-science frameworks, and standardized code libraries. Metric selection should be guided by intended use. Clinical metrics should be well-established, interpretable, and actionable. Research metrics should be clearly described, reproducible, and linked to meaningful outcomes. This review provides a comprehensive resource for navigating the diverse spectrum of CGM metrics, clarifying their applications and limitations to support both research and clinical investigation.

Keywords:  CGM; continuous glucose monitoring; diabetes mellitus; diabetes research; glycemic variability; hemoglobin A1c; narrative review; time-series glucose data

DOI:  https://doi.org/10.2196/92455
Diabetes Care. 2026 Aug 01. 49(8): e149

Comment on Kok et al. Impact of Missing Data and Monitoring Duration on Downstream Analyses in Continuous Glucose Monitoring.

Niels Væver Hartvig, Morten Hasselstrøm Jensen, Simon Lebech Cichosz.

DOI: https://doi.org/10.2337/dc26-0935
JMIR Biomed Eng. 2026 Jul 20. 11 e91959

Continuous Glucose Monitoring Data Compression Using Peak-Nadir Encoding in Diabetes: Method Development and Evaluation.

Clara Bender, Line Davidsen, Søren Schou Olesen, Simon Cichosz.

   Background: Continuous glucose monitoring (CGM) generates high-frequency time-series data, creating challenges for efficient storage, transmission, and analysis.
Objective: This study aimed to develop and evaluate a CGM-specific compression method that achieves high compression ratios while preserving signal fidelity and clinically relevant glycemic metrics.
Methods: We introduce a content-based encoding approach (PN+) that represents CGM profiles using physiologically salient landmarks: glucose peaks and nadirs and a small set of optimally selected support points. Reconstruction is performed using piecewise cubic Hermite interpolation. PN+ was evaluated against peaks and nadirs only, uniform downsampling, piecewise aggregate approximation, and autoencoder-based compression. Performance was assessed across multiple compression ratios using 2 complementary datasets: 40,000 synthetic CGM profiles and real-world CGM data from a randomized crossover trial (558 days from 30 patients). Performance was evaluated using compression ratio, mean absolute error, and R2 between original and reconstructed CGM-derived clinical metrics.
Results: At a compression ratio of 13 (22 points per 24-hour profile), PN+ achieved substantially lower reconstruction error than comparator methods (mean absolute error=0.77 vs 2.75-3.45) and consistently higher R2 values across glycemic metrics. Improvements were most pronounced for excursion-sensitive measures such as mean amplitude of glycemic excursions, where PN+ reduced error by more than 4-fold compared with downsampling, piecewise aggregate approximation, and autoencoders. These performance advantages were preserved in heterogeneous real-world data. Encoding and decoding required less than 0.2 seconds per profile, supporting practical scalability.
Conclusions: PN+ enables robust CGM data compression by explicitly preserving physiologically meaningful glucose dynamics. The method outperforms generic compression techniques in reconstructing clinically relevant metrics while maintaining low computational overhead, making it well suited for large-scale CGM storage, interoperability, and downstream analytics.

Keywords:  CGM; compression; continuous glucose monitoring; data; diabetes; encoding; reconstruction; signal

DOI:  https://doi.org/10.2196/91959
J Manag Care Spec Pharm. 2026 Jul 21. 1-8

Real-time continuous glucose monitoring related to reductions in inpatient and emergency department encounters and their associated costs among non-insulin-treated people with type 2 diabetes.

Katia Hannah, Poorva Nemlekar, Gregory J Norman.

BACKGROUND: The use of real-time continuous glucose monitoring (RT-CGM) is well established to support people with type 2 diabetes (T2D) in achieving adequate glycemic control. However, health care resource utilization (HCRU) studies have previously tended to focus on individuals with T2D who are receiving treatment with insulin.
OBJECTIVE: To examine the impacts of RT-CGM on inpatient and emergency department (ED) HCRU in non-insulin-treated people.
METHODS: This retrospective study analyzed US administrative claims data from Optum's Clinformatics Data Mart database between September 1, 2016, and December 31, 2024. Continuous glucose monitoring (CGM)-naive individuals with T2D who initiated a Dexcom G-series RT-CGM between September 1, 2017, and December 31, 2023, were included (index date: first RT-CGM claim). Change in the number of all-cause and diabetes-related encounters by service location (inpatient and ED) and the mean change in associated medical costs were assessed over a 6-month pre-index period (baseline) and in 2 consecutive 6-month segments post-index (0-6 months and 7-12 months). Stratification by baseline HCRU encounter frequency unique to service location included the following: nonutilizers, zero baseline encounters; low utilization, 1 to 2 baseline encounters; high utilization, 3 or more baseline encounters.
RESULTS: The analysis included 4,463 people with T2D. Decreases were observed in the numbers of inpatient and ED encounters among those using such encounters in the baseline period. Those considered that low utilizers (1-2 baseline encounters) experienced a 66% decrease in inpatient encounters and 63% decrease in ED encounters, whereas high utilizers (≥3 encounters) experienced a 67% decrease in inpatient encounters and 68% decrease in ED encounters. These decreases coincided with significant reductions in associated costs.
CONCLUSIONS: People with T2D who were not receiving insulin treatment and have had recent inpatient or ED encounters had lower observed HCRU after the initiation of RT-CGM with Dexcom G-series systems.

DOI: https://doi.org/10.18553/jmcp.2026.26112
Diabetes Res Clin Pract. 2026 Jul 18. pii: S0168-8227(26)00362-1. [Epub ahead of print] 113442

Variability in magnitude and direction of discordance between continuous glucose monitoring (CGM) metrics and traditional biomarkers in patients with diabetes and end-stage kidney disease (ESKD): A case series.

Yunyao Lin, James Ling, Risa Ozaki, Sze Kit Yuen, Cheuk Chun Szeto, Jack Kc Ng, Elaine Chow.

  In four patients with diabetes and end-stage kidney disease, glycated hemoglobin A1c (HbA1c) showed marked, time-varying discordance with continuous glucose monitoring (CGM)-derived glucose management indicator, ranging from - 2.1% to + 6.2%. Anemia, erythropoiesis-stimulating therapy, iron disturbances, hemoglobinopathy, transfusion and glycemic variability contributed, supporting CGM metrics for safer assessment and treatment adjustment.

Keywords:  Continuous Glucose Monitoring; Diabetes; Dialysis; Glucose Management Indicator; glycated hemoglobin A1c(HbA1c)

DOI:  https://doi.org/10.1016/j.diabres.2026.113442
J Diabetes Sci Technol. 2026 Jul 19. 19322968261463536

Performance, Safety and Usability of a Third-Generation Continuous Glucose Monitoring System in a Pediatric Population: Results From a Prospective, Multicenter Study.

Fengyun Wang, Frank Flacke, Shuxia Ding, Wenxian Oyang, Haiying Wu.

   BACKGROUND: A proprietary continuous glucose monitoring (CGM) system that uses third-generation sensor technology has previously been shown to exhibit stable, single-digit mean absolute relative difference (MARD) and 15-day wear life in adults with diabetes.
METHOD: This was a prospective, single-arm study of pediatric participants aged 2 to 17 years that were enrolled at 3 clinical centers. Participants wore 2 sensors, one on each side of the abdomen, and were randomized to assessment of device performance on days 1 and 2, days 7 to 9 or days 15 and 16. Device performance across a range of metrics was assessed by comparison with venous blood glucose values obtained using a laboratory reference device. Per-protocol results are reported for the sensor with the inferior MARD.
RESULTS: The per-protocol set comprised 75 participants, of whom 16 were aged 2 to 5 years. The overall MARD was 8.89%, and MARDs at days 1 and 2, 7 to 9 and 15 and 16 were 8.65%, 8.70% and 9.30%, respectively. DTS error grid analyses showed that 100.0% of data pairs fell in clinically acceptable zones A+B. True alarm rates for hypoglycemia and hyperglycemia were high, at 98.6% and 98.8%, respectively. Mean sensor wear life was 14.4 days, and participant/guardian assessments of sensor usability revealed high satisfaction with respect to system assembly, sensor insertion and overall comfort. No device-related or skin-related adverse events were reported.
CONCLUSIONS: In a pediatric population, the novel CGM system demonstrated accurate and stable performance across its 15-day wear life and showed high usability.

Keywords:  continuous glucose monitor; mean absolute relative difference (MARD); pediatrics; sensor accuracy; wear life

DOI:  https://doi.org/10.1177/19322968261463536
Diabetes Obes Metab. 2026 Jul 22.

Association Between Time in Range and Advanced Cardiovascular-Kidney-Metabolic Syndrome in Older Adults With Type 2 Diabetes.

Hang Su, Jiaying Ni, Jinghao Cai, Wei Zhu, Yufei Wang, Jian Zhou, Jingyi Lu, Xiaojing Ma.

   AIMS: Cardiovascular, kidney and metabolic diseases are pathophysiologically interrelated and are conceptualised within the cardiovascular-kidney-metabolic (CKM) syndrome framework. However, evidence linking continuous glucose monitoring (CGM) to CKM syndrome remains limited. This study examined the association between time in range (TIR), the core CGM metric, and advanced CKM syndrome.
MATERIALS AND METHODS: A total of 2497 adults aged ≥ 60 years with type 2 diabetes were included. CKM syndrome was defined according to the American Heart Association Presidential Advisory, with stages 3-4 classified as advanced CKM syndrome.
RESULTS: Participants with advanced CKM syndrome exhibited significantly lower TIR levels than those with non-advanced CKM syndrome (p < 0.001). After multivariable adjustment, each 1-standard deviation decrease in TIR was independently associated with higher odds of advanced CKM syndrome (OR 1.28, 95% CI 1.16-1.42). Restricted cubic spline analyses demonstrated a linear inverse association between TIR and advanced CKM syndrome, with the estimated OR approaching unity at approximately 70%. The prevalence of advanced CKM syndrome increased progressively across TIR categories of > 70%, 50%-70% and ≤ 50% (p for trend < 0.001). Although TIR levels of 50%-70% exceed the currently recommended target of > 50% for older adults, this range remained associated with higher odds of advanced CKM syndrome compared with TIR > 70% (OR 1.40, 95% CI 1.12-1.75). Higher TIR was not associated with increased hypoglycemia exposure.
CONCLUSIONS: Lower TIR was associated with advanced CKM syndrome, supporting the potential value of CGM-derived TIR in evaluating multisystem cardiovascular-kidney-metabolic burden in older adults with type 2 diabetes.

Keywords:  cardiovascular‐kidney‐metabolic syndrome; comorbidity; continuous glucose monitoring; older adults; time in range; type 2 diabetes

DOI:  https://doi.org/10.1111/dom.71143
Chronic Dis Transl Med. 2026 May 28.

Discharge Remote Monitoring Systems for Glycemic Management After Hospital Discharge.

Nirali Shah, Camilla Levister, Riana Jumamil, Carol Levy, Margaret Crawford, Christian Hicks, Selassie Ogyaadu, Aslihan Ipek, Abigail Tamru, Madeleine Rouviere, Leah Kaplan, Ying Xu, Harsimran Singh, Daniel Cherñavvsky, Grenye O'Malley.

In this feasibility study of the use of continuous glucose monitoring (CGM) after hospital discharge, CGM use was well accepted with high satisfaction scores.Transplant and high-severity cohorts were not meeting glycemic targets immediately after discharge.This study adds to the limited literature on postdischarge glycemic care by demonstrating that CGM integration into telehealth diabetes care is feasible and by identifying areas for future research.

DOI: https://doi.org/10.1002/cdt3.70055
J Endocrinol Invest. 2026 Jul 20.

Metabolomic signatures of glycemic control in type 1 diabetes: insights from continuous glucose monitoring.

Sara de Lope Quiñones, Manuel Luque-Ramírez, Alejandra Quintero Tobar, José Manuel Ruiz Cánovas, Beatriz Dorado Avendaño, Hector F Escobar-Morreale, Lía Nattero-Chávez.

   PURPOSE: This study aimed to investigate the relationship between serum metabolomic profiles and continuous glucose monitoring (CGM) metrics in adults with type 1 diabetes (T1D), given that glycaemic control differences influence distinct metabolic pathways.
METHODS: In this cross-sectional study, 325 adults with T1D were evaluated. CGM metrics were derived from 14-day recordings. Participants were stratified by achievement of clinical glycaemic targets [time in range (TIR70-180) > 70%, coefficient of variation (CV) < 36%, and time below range (TBR < 70) < 5%] into "on-target" and "off-target" groups. Serum metabolomic profiles were quantified using proton nuclear magnetic resonance spectroscopy (1 H-NMR).
RESULTS: Among the 325 participants (46% female; mean age 41 ± 14 years; diabetes duration 20 ± 12 years), 57 (18%) achieved all clinical glycaemic targets. These patients had higher concentrations of glutamine, valine, and isoleucine, and lower lactate levels. TIR70-180 correlated negatively with lactate, Glyc B, and Glyc B H/W. Mean glucose was positively associated with IDL-C, IDL-TG, LDL-P, small LDL-P, Glyc A H/W, and lactate, and negatively with glutamine and acetone. Hypoglycaemia metrics were associated with small LDL-P, while glucose variability correlated with alanine [β: - 0.026 (95% CI: - 0.057 to - 0.008); P = 0.013]. In logistic regression analyses adjusted for duration of T1D, glutamine [Exp(B) = 0.993 (95% CI: 0.987-0.999), P = 0.022] and lactate [Exp(B) = 1.004 (95% CI: 1.001-1.007, P = 0.003] were significantly associated with glycaemic control.
CONCLUSIONS: Serum metabolomic profiles reflect CGM-derived glycaemic metrics in T1D, highlighting their potential role as biomarkers for a refined assessment of metabolic control.

Keywords:  Continuous glucose monitoring; Metabolomics profile; Proton nuclear magnetic resonance spectroscopy; Type 1 diabetes mellitus

DOI:  https://doi.org/10.1007/s40618-026-02973-6
JAMA Netw Open. 2026 Jul 01. 9(7): e2624260

Contemporary Diabetes Technology and the Patient Experience.

Estelle M Everett, Erin Shaw, Bryan Escobar Barrios, Tannaz Moin, Lauren E Wisk.

Importance: Use of insulin pumps, continuous glucose monitors (CGMs), and automated insulin delivery (AID) systems has increased substantially in type 1 diabetes (T1D) care. Although these technologies improve glycemic outcomes, their broader impact on patients' daily lives and psychosocial well-being remains incompletely understood.
Objective: To identify psychosocial and other emerging dimensions of contemporary diabetes technology use among adults with T1D.
Design, Setting, and Participants: This qualitative study used thematic analysis of free-text survey responses collected between August 1, 2024, and February 28, 2025, from adults (aged ≥18 years) with T1D receiving care within a single, large, academic health system in the US. Participants represented a range of ages, diabetes duration, and age at onset; most were users of CGMs and AID systems.
Results: Of 5650 individuals who were invited to participate in the study, 945 eligible patients responded to the survey and 535 (mean [range] age, 48 [18 to ≥70] years; 282 [52.8%] female) provided free-text responses regarding the impact of diabetes technology on daily life that were included in the qualitative analysis. The median (range) diabetes duration was 25 (0 to ≥31) years. Overall, 508 (95.0%) were using CGMs and 369 (69.0%) were using insulin pumps. Participants described diverse experiences with modern diabetes technology, reflecting both benefits and burdens. In addition to established psychosocial themes, several novel concerns were identified: environmental impact from device-related waste, travel-related stress due to supply logistics and inconsistent airport security procedures, distress related to premature device failures and challenges navigating manufacturer and insurance replacement processes, and apprehension about digital security. These structural and societal factors were described as meaningful contributors to overall technology experience.
Conclusions and Relevance: In this study of adults with T1D, contemporary diabetes technology affected more than glycemic control; environmental sustainability, administrative burden, travel logistics, and digital trust represented emerging dimensions of technology-dependent care. Addressing these concerns through patient-centered design, streamlined system processes, and transparent cybersecurity protections may enhance the long-term sustainability and acceptability of advanced diabetes technologies.

DOI: https://doi.org/10.1001/jamanetworkopen.2026.24260
PLOS Digit Health. 2026 Jul;5(7): e0001505

Digital phenotyping of CGM engagement reveals distinct glycemic outcomes.

Bowen Zhang, Tomoki Okuno, Emma Li, Ethan Riggins, Evie L Shen, Joleen Vansomphone, Estelle M Everett, Gregory J Norman, Donald R Miller, Peter D Reaven, Hua Zhou, Jin J Zhou.

Benefits from continuous glucose monitors (CGMs) may depend on how devices are used over time-not only how often they are used. We linked one year of device-generated CGM wear data from 2,351 U.S. Veterans to electronic health records (EHRs) to characterize real-world usage during the first year after CGM initiation. To compare longitudinal use patterns in the presence of unsynchronized sensor replacement-related gaps and intermittent interruptions, we aligned daily wear streams using a complexity-adjusted, time-adaptive optimal transport (TAOT) distance and applied spectral clustering to identify data-driven usage phenotypes. To estimate the adjusted association between CGM usage phenotypes and clinical outcomes, we used a double/debiased machine learning framework to quantify 12-month changes in time in range (ΔTIR) and mean glucose (ΔMG). We identified three reproducible patterns of CGM usage: Consistent, Fluctuating, and Low engagement. Relative to Consistent wear, Fluctuating usage was associated with worse glycemic change (ΔTIR = -3.56%, 95% CI: -4.76 to -2.36; ΔMG = +7.12 mg/dL, 95% CI: 4.91 to 9.32), and Low engagement showed larger deterioration (ΔTIR = -7.00%, 95% CI: -10.80 to -3.14; ΔMG = +14.09 mg/dL, 95% CI: 6.52 to 21.67). Notably, 73.2% of Fluctuating users still met a common "adherence" threshold (≥80% days worn), indicating that simple coverage metrics can miss clinically relevant instability. The differences in glycemic change (ΔTIR and ΔMG) between the Consistent and Fluctuating groups were most pronounced among subgroups with more intensive diabetes management needs, such as insulin pump or glucagon users, suggesting that sustained CGM usage may be particularly important when clinical management is more complex. Beyond CGM and diabetes, this work provides a generalizable framework for characterizing longitudinal usage patterns of intermittently used digital health technologies and linking derived usage phenotypes to clinical outcomes. The approach can support more precise evaluation, monitoring, and intervention design for a wide range of real-world digital health tools.

DOI: https://doi.org/10.1371/journal.pdig.0001505
Diabet Med. 2026 Jul 22. e70436

Glycaemia risk index and continuous glucose monitoring metrics across menstrual cycle phases in women with type 1 diabetes using automated insulin delivery.

Grazia Piras, Marta Bassi, Angelo Milioto, Maria Grazia Calevo, Giordano Spacco, Francesco Cocchiara, Nicola Minuto, Davide Maggi.



Keywords:  CSII; automated insulin delivery; glycaemia risk index; menstrual cycle; time in tight range; type 1 diabetes

DOI:  https://doi.org/10.1111/dme.70436
Clin Med Insights Endocrinol Diabetes. 2026 ;19 11795514261470879

Numerical and Clinical Accuracy of the FreeStyle Libre 2 System: A Diagnostic Accuracy Study in Critically Ill Patients.

Miguel Aguilar-Schotborgh, Oscar Muñoz-Velandia, Diana Cristina Henao-Carrillo, Luis Triana Moreno, Jhon Moreno Mogollon, Ana Maria Gómez.

   Background: The accuracy of the FreeStyle Libre 2 system in critically ill patients needing insulin therapy remains inadequately evaluated.
Objective: To evaluate the clinical and numerical accuracy of continuous glucose monitoring (FreeStyle Libre 2) and capillary glucometry (StatStrip) compared with central laboratory glucose in critically ill patients requiring insulin therapy.
Methods: We conducted a diagnostic accuracy study, evaluating simultaneously two index tests, the FreeStyle Libre 2 and capillary glucose, compared to the central laboratory glucose (venous or arterial) as reference standard. The study included critically ill adult patients admitted to the intensive care unit (ICU) with diabetes or stress hyperglycemia, requiring insulin therapy, and ventilatory or vasopressor support. Numerical accuracy was assessed using ISO 15197:2013 criteria and Mean Absolute Relative Difference (MARD). Clinical accuracy was evaluated using Clarke and Parkes error grid analysis.
Results: A total of 157 paired measurements were collected. FreeStyle Libre 2 showed a MARD comparable to capillary glucose (10.43% vs 7.58%; p=0.14). Neither method met ISO 15197:2013 numerical accuracy criteria. In the clinical accuracy analysis, FreeStyle Libre 2 classified 100% of measurements within zones A+B on both the Clarke and Parkes grids, whereas capillary glucose achieved 97.6% and 100%, respectively.
Conclusions: FreeStyle Libre 2 showed numerical accuracy comparable to capillary blood glucose and consistently reliable clinical performance in critically ill patients needing insulin therapy. These results support its potential as an alternative to capillary glucose monitoring in the ICU. More studies involving a greater number of hypoglycaemic events are required to confirm its effectiveness in this critical range.

Keywords:  ICU; continuous glucose monitoring; critical care; diabetes mellitus; glycemic control

DOI:  https://doi.org/10.1177/11795514261470879
J Diabetes Sci Technol. 2026 Jul 21. 19322968261469513

Piloting a Postdischarge Virtual Glucose Monitoring Program for Patients With Diabetic Foot Wound in a Safety-Net Health System.

Felona Gunawan, Blessing Johnny, Binsy Easow, Smitha Mathew, Jacqueline N McNulty, Kristie Adame, Kaely Jackson, Larry S Brown, Peter A Crisologo, Uma Gunasekaran.

   BACKGROUND: Diabetic foot wounds disproportionately affect patients from ethnic minorities and lower-socioeconomic status, many of whom face barriers to accessing diabetes technology. To evaluate whether short-term virtual glucose monitoring (VGM) has the potential to improve clinical outcomes in this high-risk population, we implemented a pilot VGM program within a safety-net health system.
METHOD: We enrolled 40 hospitalized patients with diabetic foot wounds into a 3-month postdischarge VGM program that included 2 clinic visits and remote glucose monitoring every 1 to 2 weeks. Clinical outcomes were compared with a retrospective preintervention cohort of 78 similar patients.
RESULTS: Although both groups had similar HgbA1c at diagnosis (VGM 10.6 ± 1.8% vs preintervention 11.1 ± 2.0%, P = .20), the HgbA1c at 3 to 6 months was lower in the VGM cohort (7.6 ± 1.1% vs 8.5 ± 2.0%, P < .01). Wound healing occurred more frequently in the VGM participants, with 68% achieving wound closure by 3-4 months versus only 47% in the preintervention cohort (P = .04). Nonsignificant reductions in emergency department visits and hospital readmissions for wound complications or hypoglycemia were observed in the VGM versus the preintervention cohort. The VGM program allowed for more timely and frequent opportunities to adjust diabetes medications and address social barriers to care.
CONCLUSIONS: A short-term postdischarge VGM program has the potential to not only increase access to diabetes technology but also meaningfully improve clinical outcomes among patients with diabetic foot wounds in a safety-net health setting. Such program may offer a scalable strategy to reduce rates of complications and lower healthcare costs in a safety-net health system.

Keywords:  continuous glucose monitoring; diabetic foot wounds; postdischarge glucose monitoring; remote monitoring; safety-net health system

DOI:  https://doi.org/10.1177/19322968261469513
Diabetologia. 2026 Jul 20.

Acute mild cold exposure with shivering reduces 24 h glucose levels in individuals with type 2 diabetes but not prediabetes.

Dzhansel Hashim, Johanna A Jörgensen, Tineke van de Weijer, Denis P Blondin, Patrick Schrauwen, Joris Hoeks.

   AIMS/HYPOTHESIS: Repeated cold exposure with shivering has been proposed as a potential strategy to enhance glucose metabolism by increasing energy expenditure and substrate utilisation. However, acute effects/benefits of cold-induced shivering on glucose homeostasis in metabolically compromised individuals are unknown. Here, we aimed to determine whether cold exposure at two different intensities improves 24 h glucose homeostasis in individuals with prediabetes and type 2 diabetes.
METHODS: In a randomised crossover trial conducted in the South Limburg/Maastricht region of the Netherlands, men and postmenopausal women with prediabetes (n=12) and stable type 2 diabetes (n=12), aged 40-75 years, body mass index ≥27 and ≤35 kg/m2, non-smoking and sedentary, underwent two whole-body cold exposure sessions using a water-perfused suit. Session order was randomised using an online randomisation tool (randomizer.org); participants were masked to the cold exposure intensity received, but investigators were not. Sessions were designed to elicit ~1.5-fold (mild, 15°C) and ~2.5-fold (moderate, 4°C) increases in resting metabolic rate (RMR). Continuous glucose monitoring assessed interstitial glucose concentrations over 24 h periods before and after each intervention, with controlled diet and activity. Shivering was confirmed via indirect calorimetry and electromyography.
RESULTS: In both study groups and periods, RMR increased significantly vs baseline (p<0.001 for all). In prediabetes, the increase in the final 1 h of cold was 1.53 × RMR in mild and 1.94 × RMR in moderate cold. In type 2 diabetes, the increase was 1.57 × RMR and 2.09 × RMR in the final 1 h of mild and moderate cold, respectively. In prediabetes, neither mild nor moderate cold exposure altered mean 24 h glucose levels. In contrast, after mild cold exposure the type 2 diabetes group exhibited a significant reduction in mean 24 h glucose levels (-0.6 ± 0.5 mmol/l, p=0.003) and fasting glucose (-0.6 ± 0.8 mmol/l, p=0.019), as well as an increase in time in normal range (+8.8 ± 10.3%, p=0.013) and reduced time in hyperglycaemia (-10.9 ± 12.9%, p=0.014). Moderate cold did not significantly affect any of the glucose outcomes in type 2 diabetes. Baseline fasting glucose, age and ALT levels were predictors of the glucose-lowering response, suggesting greater benefits in individuals who have higher baseline glucose levels, are younger and/or have more optimal liver health, i.e. lower ALT.
CONCLUSIONS/INTERPRETATION: Acute mild cold exposure with shivering reduced 24 h glucose levels in individuals with type 2 diabetes. No changes were observed in prediabetes. The observed effects appear to depend on baseline metabolic status rather than acute substrate utilisation during cold exposure. These findings support the potential of cold exposure as an adjunct non-pharmacological therapy for type 2 diabetes, although further mechanistic studies and validation in larger cohorts are warranted.
TRIAL REGISTRATION: ClinicalTrials.gov NCT05576025 FUNDING: Dutch Organisation for Knowledge and Innovation in Health, Healthcare and Well-being (ZonMw): 09120012010062.

Keywords:  Cold; Continuous glucose monitoring; Glucose homeostasis; Lifestyle intervention; Metabolism; Prediabetes; Type 2 diabetes

DOI:  https://doi.org/10.1007/s00125-026-06809-z