bims-glumda 2026-10-18 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2026–10–18
twenty-one papers selected by
Mott Given

Continuous glucose monitoring (CGM) systems in Poland, Europe, and beyond in 2025: principles, available technologies, and future perspectives.
Association of HbA1c with Time in Range, Time in Tight Range, Empirically Derived Continuous Glucose Monitoring Glucose Ranges, and Mean Glucose.
Guidance for continuous glucose monitor (CGM) use in Canadian hospitals.
Effectiveness of Continuous Glucose Monitoring in Non-Intensively Managed Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.
Beyond the Enzyme: Toward Integrated Design of Clinically Reliable Continuous Glucose Sensor.
Pharmacist-Led Continuous Glucose Monitoring for Prediabetes: Protocol for a Prospective Cohort Study.
Pediatric Inpatient Continuous Glucose Monitoring: Development and Implementation of a Hospital Policy for Accuracy-Validated Insulin Dosing.
Distinct insulin sensitivity profiles revealed by clustering based on continuous glucose monitoring data in people living with type 1 diabetes.
Continuous Glucose Monitoring in Non-Insulin-Treated Type 2 Diabetes.
From Clinician-Based Risk Score to Diabetes Complications: Validating the Glycemia Risk Index with the Virtual Diabetes Control and Complications Trial Continuous Glucose Monitoring Data.
Beyond the glycation gap: A multicompartment framework for HbA1c-glycemia discordance in Pediatric type 1 diabetes.
Continuous glucose monitoring for diabetes mellitus in the perioperative and intensive care setting: a prospective observational validation study✰.
Continuous Glucose Monitoring for Women with Gestational Diabetes, CORDELIA: A Multicentric Randomized Controlled Trial, Methodology and Design.
Association Between the GMI/HbA1c Ratio and Microvascular Complications in Type 1 Diabetes: A Multicenter Cross-Sectional Study.
[Standardization of quality criteria for continuous glucose monitoring systems in Argentina].
Performance of a 15-Day Continuous Glucose Monitoring System in Children and Adolescents With Diabetes.
24-Hour Movement Behavior Reallocations and Glycemic Variability in Adults With Type 1 Diabetes: A Longitudinal Isotemporal Substitution Analysis.
Evaluation of a local healthy moderate carbohydrate (LHMC) diet and structured exercise for diabetes remission in early type 2 diabetes mellitus: A nutrition intervention study from India.
AI-Enhanced Wearable Glucose Sensors: From Intelligent Sensing to Closed-Loop Management of Diabetes.
The Impact of a Low Glycemic Load Breakfast on Diurnal Glucose Profiles in Women with Gestational Diabetes Mellitus: The GLIDING Randomized Crossover Trial.
Uncovering allergen presence and accumulation in glucose monitoring systems: evidence of a "sponge effect" via validated GC-MS.

Arch Med Sci. 2026 ;22(4): 2250-2265

Continuous glucose monitoring (CGM) systems in Poland, Europe, and beyond in 2025: principles, available technologies, and future perspectives.

Oskar Kublin, Dorota Filipowicz, Mariusz Stępień.

  In recent years, continuous glucose monitoring (CGM) systems have become increasingly common and more widely available for people with diabetes. A variety of devices appearing on the market, together with their increasing integration with other tools (insulin pumps, watches, and smartphone applications), require medical personnel to have a solid basic knowledge of CGMs, continuous follow-up, updated expertise extending beyond the local market, and a future-oriented perspective. Additionally, low-quality products without proper evaluation, which do not meet the standards established by diabetes societies, become available to patients. To provide an extended background on CGM technology principles, basic knowledge of results presentation, and interpretation according to recommendations, this review presents the most common devices, along with a cost-effectiveness analysis and a critical assessment. Furthermore, future perspectives are discussed, including AI technologies and modern solutions to enhance user comfort.

Keywords:  advanced hybrid closed-loop; continuous glucose monitoring; diabetes technology; diabetes type 1; insulin

DOI:  https://doi.org/10.5114/aoms/218227
Diabetes Technol Ther. 2026 Oct 12. 15209156261496613

Association of HbA1c with Time in Range, Time in Tight Range, Empirically Derived Continuous Glucose Monitoring Glucose Ranges, and Mean Glucose.

Halis Kaan Akturk, Kagan E Karakus, Emma Mason, Zeynep Y Yilmaz, Satish K Garg, Dicle Cengiz.

   OBJECTIVE: To evaluate how continuous glucose monitoring (CGM) glucose thresholds, sampling duration, and statistical modeling influence associations between CGM-derived range metrics and HbA1c, and to compare empirically derived glucose ranges with time in range (TIR) and time in tight range (TITR).
RESEARCH DESIGN AND METHODS: Out of 8160 HbA1c-matched CGM datasets from 1584 adults, CGM data from the 14, 30, and 90 days preceding each HbA1c measurement were evaluated. Associations between HbA1c and 7790 CGM glucose ranges were assessed across varying lower and upper glucose thresholds. Linear and log-linear mixed-effects models adjusted for age and race with participant-level random intercepts were compared using root mean square error and marginal R2. Participant-level derivation (80%) and validation (20%) cohorts were used for cross-validated threshold selection and discrimination analyses for HbA1c ≤7.0%.
RESULTS: Ninety-day CGM sampling showed the strongest associations with HbA1c. Log-linear models frequently provided comparable or improved fit, particularly for glucose ranges with upper thresholds below 180 mg/dL. Stronger HbA1c associations clustered around upper glucose thresholds of 155-175 mg/dL. In validation analyses, empirically derived ranges demonstrated strong discrimination of HbA1c ≤7.0% (area under the receiver operating characteristic curve [AUC] 0.909-0.915), compared with 0.903 for TIR and 0.905 for TITR, although absolute differences were small. Mean glucose demonstrated the strongest explanatory performance for continuous HbA1c (marginal R2 = 0.74) and similarly strong discrimination (AUC 0.913).
CONCLUSIONS: CGM-HbA1c relationships are influenced by glucose range, sampling duration, and statistical modeling. Our findings reinforce TIR and TITR as robust CGM metrics with strong associations with HbA1c, while also showing that selected empirically derived glucose ranges can provide modestly stronger statistical alignment. These results support the continued use of TIR and TITR while highlighting how glucose range definition may refine interpretation of CGM-based endpoints in future research.

Keywords:  HbA1c; continuous glucose monitoring; glycemic metrics; time in range; time in tight range; type 1 diabetes

DOI:  https://doi.org/10.1177/15209156261496613
Can J Diabetes. 2026 Oct 15. pii: S1499-2671(26)00372-2. [Epub ahead of print]

Guidance for continuous glucose monitor (CGM) use in Canadian hospitals.

Julie L V Shaw, Davor Brinc, Angela W S Fung, Robyn L Houlden, Annie Garon-Mailer, Lisa Maks, Sarah Moore-Vasram, Leta C Philp, Atoosa Rezvanpour, Cathy J Sun, Vinita Thakur, Allison A Venner, Li Wang.

  People living with diabetes and healthcare providers are increasingly advocating for the option to continue use of their personal continuous glucose monitoring (CGM) devices during hospital admission to promote continuity of care. Although no CGM devices are currently approved by Health Canada for inpatient use, CGM use in ambulatory settings has been shown to improve glycemic outcomes and patient experience compared with capillary glucose monitoring. Publications in recent years have demonstrated that CGM use in specific populations can be safe and may improve glycemic control while reducing hypoglycemia risk. Accordingly, hospitals must determine how to safely and practically integrate CGM into inpatient clinical practice. This article provides practical guidance for the use of CGM in Canadian hospitals for inpatient glucose monitoring.

Keywords:  Automated Insulin Delivery; Continuous glucose monitoring; Diabetes mellitus; Glucose monitoring; Hospitalization; Point of care testing

DOI:  https://doi.org/10.1016/j.jcjd.2026.09.009
J Diabetes Sci Technol. 2026 Oct 14. 19322968261489265

Effectiveness of Continuous Glucose Monitoring in Non-Intensively Managed Type 2 Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Ayman Al Hayek, Wael M Al Zahrani, Haifa F Alotaibi, Manal El Jammal, Mohammed A Al Dawish.

   BACKGROUND: The effectiveness of continuous glucose monitoring (CGM) in adults with type 2 diabetes (T2D) not receiving intensive insulin therapy remains incompletely established, particularly regarding glycemic metrics beyond glycated hemoglobin (HbA1c).
METHODS: We conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating real-time CGM (rtCGM) or intermittently scanned CGM (isCGM) in adults with T2D managed with non-intensive insulin regimens or non-insulin therapies. Databases were searched from inception to February 2026. Primary outcomes included HbA1c, mean glucose concentration, time in range (%TIR), time above range (%TAR), time below range (%TBR), body mass index (BMI), and patient-reported outcomes. Random-effects meta-analyses were performed using Stata 17. Risk of bias was assessed using the Cochrane Risk-of-Bias tool, version 2, and certainty of evidence was evaluated using Grading of Recommendations Assessment, Development and Evaluation (GRADE).
RESULTS: Twenty-five RCTs were included. Continuous glucose monitoring significantly reduced HbA1c (mean difference [MD] -0.34, 95% confidence interval [CI], -0.46 to -0.23), mean glucose concentration (MD -13.97 mg/dL, 95% CI, -23.13 to -4.81), and %TAR (MD -6.75%, 95% CI, -10.81 to -2.70), while significantly increasing %TIR (MD +7.85%, 95% CI, 4.32-11.38). No significant effects were observed for BMI (MD -0.16 kg/m2, 95% CI, -0.45 to 0.12) or %TBR (MD -0.11%, 95% CI, -0.31 to 0.08). Benefits were generally more pronounced in non-insulin-treated populations. Patient-reported outcomes were heterogeneous but suggested improved treatment satisfaction and glucose-monitoring experience with CGM. Certainty of evidence was moderate across outcomes.
CONCLUSIONS: Continuous glucose monitoring probably improves glycemic control in adults with T2D not receiving intensive insulin therapy, particularly by reducing hyperglycemia and improving TIR, with limited effects on hypoglycemia or body weight.

Keywords:  continuous glucose monitoring; flash glucose monitoring; glycemic control; intermittently scanned continuous glucose monitoring; meta-analysis; randomized controlled trials; real-time continuous glucose monitoring; time in range; type 2 diabetes

DOI:  https://doi.org/10.1177/19322968261489265
J Diabetes Sci Technol. 2026 Oct 12. 19322968261496305

Beyond the Enzyme: Toward Integrated Design of Clinically Reliable Continuous Glucose Sensor.

Ariel M Lorenzo, Claudette Mine Lumibao, Winnie Alejo, Rema Ariola, Jerick Jay Briones.



Keywords:  continuous glucose monitoring; direct electron transfer; glucose biosensors; glucose oxidoreductases; sensor integration

DOI:  https://doi.org/10.1177/19322968261496305
JMIR Res Protoc. 2026 Oct 15. 15 e105275

Pharmacist-Led Continuous Glucose Monitoring for Prediabetes: Protocol for a Prospective Cohort Study.

Kevin Cowart, Raechel T White, Nicholas W Carris, Benedicta O Ansong, Alyssa Hinden, Gwendolyn Clayton, John Petrilli, Eric Coris.

   BACKGROUND: Prediabetes represents a critical intervention window to reduce progression to type 2 diabetes. The current standard of care for treatment of prediabetes is weight loss and lifestyle modification, which are both highly effective, although limited by real-world adherence. It is well recognized that continuous glucose monitoring (CGM) improves glycemic and behavioral outcomes in people with diabetes, although outcomes among people with prediabetes are not well described.
OBJECTIVE: The aim of this study is to evaluate the impact of pharmacist-led CGM on glycemic control and health-related behaviors in adults with prediabetes.
METHODS: This study includes a prospective pharmacist-led CGM cohort and a matched retrospective usual-care cohort. Adults aged 18 to 70 years with prediabetes (hemoglobin A1c [HbA1c] 5.7%-6.4%) will be eligible for the prospective cohort if they have a compatible smartphone and no CGM use in the prior 6 months. Participants will receive CGM (Stelo glucose biosensor; Dexcom) and diabetes self-management education and support over 12 weeks. The primary outcome is the change in HbA1c at 12 weeks, compared between groups. Secondary outcomes include CGM-derived metrics, changes in Summary of Diabetes Self-Care Activities scores and 36-Item Short Form Health Survey scores, and CGM-related adverse effects.
RESULTS: This study was funded in 2026. Recruitment is ongoing, and no participants had been enrolled at the time of writing. The planned sample size is 40 participants: 20 prospective CGM participants and 20 retrospective controls. Outcome data are not yet available. The study is expected to be completed in July 2027, and the results are anticipated to be disseminated in December 2027.
CONCLUSIONS: This study seeks to evaluate the glycemic impact, behavior change, and safety of pharmacist-led CGM for prediabetes in primary care.
TRIAL REGISTRATION: ClinicalTrials.gov NCT07529366; https://tinyurl.com/33bv7u8c.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/105275.

Keywords:  continuous glucose monitoring; diabetes prevention; health behavior; pharmacist; prediabetes; primary care

DOI:  https://doi.org/10.2196/105275
Diabetes Technol Ther. 2026 Oct 12. 15209156261489912

Pediatric Inpatient Continuous Glucose Monitoring: Development and Implementation of a Hospital Policy for Accuracy-Validated Insulin Dosing.

Ming Yeh Lee, Hector I Ortega, Christopher Chow-Parmer, Karen Belanger, Sheridan Jones, Victor Ritter, Whitney Chadwick, Julie J Lee, Kailee Kingston, Cristal Suarez, Mark McGovern, David M Maahs, Priya Prahalad, Sejal Shah, Rayhan Lal, Michael S Hughes.

   OBJECTIVE: We assessed the safety, clinical accuracy, glycemic outcomes, user outcomes, and implementation of a pediatric hospital-wide continuous glucose monitor (CGM) policy.
RESEARCH DESIGN AND METHODS: We used the Model for Improvement to develop a pediatric hospital policy supporting CGM-based insulin dosing with accuracy validation using capillary finger-stick blood glucose (FSBG) and then retrospectively evaluated the program's clinical effectiveness and implementation outcomes with the Simplified Implementation Logic Model to connect contextual determinants, support strategies, and outcomes.
RESULTS: From September 2024 to October 2025, 60 people with diabetes used the CGM policy in 93 hospital encounters, including 46.7% (28/60) people with type 1 diabetes and 38.7% (36/93) encounters with automated insulin delivery use. The most used CGMs were Dexcom G7 (49.5%) and Abbott Libre 3 or 3 Plus (31.2%). Accuracy validation using the %20/20 criteria was successful in 81.5% of attempts, and the mean absolute relative difference was 12.6%, with 1207 paired CGM and reference FSBG values. Nurses responded appropriately after 97.8% (218/223) of failed CGM validation attempts. CGM time in range (70-180 mg/dL) was 54.8%, and time in level 2 hypoglycemia (<54 mg/dL) was 0.8% for the 58 out of 93 encounters with complete CGM data downloads. Nurses preferred using CGM with policy support instead of FSBG for insulin dosing (adjusted P = 0.046). Factors contributing to nursing preference included ease of use, system integration, and the ability to learn the system quickly.
CONCLUSIONS: We translated an inpatient CGM policy from an adult to pediatric hospital setting, supporting high levels of protocol adherence, clinical accuracy, safety, and improved experiences for clinicians. Program evaluation informs connections between contextual determinants, support strategies, and outcomes of implementing a hospital CGM program. These data offer a roadmap for implementing pediatric hospital CGM at other centers.

Keywords:  CGM; implementation evaluation; inpatient; pediatric diabetes; policy

DOI:  https://doi.org/10.1177/15209156261489912
Front Endocrinol (Lausanne). 2026 ;17 1963929

Distinct insulin sensitivity profiles revealed by clustering based on continuous glucose monitoring data in people living with type 1 diabetes.

Svjatoslavs Kistkins, Anastasija Luganceva, Sergejs Lobanovs, Timurs Mihailovs, Aleksejs Fedulovs, Leonora Pahirko, Valdis Pīrāgs, Othmar Moser, Harald Sourij, Jelizaveta Sokolovska, Dmitrijs Bliznuks.

   Background: Continuous glucose monitoring (CGM) has improved glycemic management in Type 1 Diabetes Mellitus (T1DM). However, interpretation of CGM data remains challenging. CGM data clustering may support individualized management and identify insulin resistance.
Aim: This study aimed to cluster CGM data based on interstitial glucose levels (2.2-27.8 mmol/L) and glucose variability, and to compare the identified clusters with biochemical and anthropometric markers of insulin sensitivity.
Methods: CGM data from 75 T1DM patients and 20 subjects without diabetes were analyzed using Uniform Manifold Approximation and Projection (UMAP) for dimension reduction, followed by K-means clustering. Estimated glucose disposal rate (eGDR) was calculated to assess insulin sensitivity.
Results: Seven clinically distinct CGM phenotypes were identified: Normoglycemia-in-Diabetes (N), Normoglycemia-in-Non-Diabetes (No), Mild Hyperglycemia (MiH), Moderate Hyperglycemia (ModH), Severe Hyperglycemia (SeH), Hypoglycemia-Associated Normoglycemia (HAN), and Hypoglycemia-Associated Hyperglycemia (HAH). The SeH cluster demonstrated the highest median average glucose level (13.83 [13.07;14.12] mmol/L), while HAH exhibited the highest median coefficient of variation (50 [44;52]%). The lowest median average glucose level was observed in HAN (6.14 [5.95;6.17] mmol/L). A marginally significant difference in ALT levels was observed between SeH and No (p=0.07). eGDR differed significantly between SeH/HAN (p=0.001), ModH/HAN (p=0.019), and MiH/HAN (p=0.043), with marginally significant differences between HAN/HAH (p=0.063). Triglycerides differed significantly between HAN/SeH (p=0.029), HAN/MiH (p=0.024).
Conclusion: This exploratory CGM-based clustering approach identified phenotypically distinct T1DM subgroups with differing insulin sensitivity profiles. These preliminary findings require validation in larger independent cohorts. If confirmed, such phenotyping may support individualized diabetes management and identification of insulin resistance.

Keywords:  cluster analysis; continuous glucose monitoring; diabetes mellitus; insulin resistance; personalized medicine; type 1

DOI:  https://doi.org/10.3389/fendo.2026.1963929
N Engl J Med. 2026 Oct 14.

Continuous Glucose Monitoring in Non-Insulin-Treated Type 2 Diabetes.

CONNECT Study Group

BACKGROUND: Continuous glucose monitoring (CGM) has been shown to be beneficial in persons with type 1 diabetes and others with insulin-treated type 2 diabetes, but its role in the treatment of persons with type 2 diabetes not being treated with insulin has needed further study.
METHODS: In a 26-week trial conducted at 22 primary care practices in the United States, we randomly assigned adults with type 2 diabetes who were not using insulin to either CGM or routine care (control). The primary outcome was the glycated hemoglobin level at 26 weeks. Key CGM-measured secondary outcomes were tested hierarchically to control the type I error rate.
RESULTS: A total of 145 participants were assigned to the CGM group, and 138 to the routine-care group. Participants ranged in age from 21 to 84 years. The mean (±SD) glycated hemoglobin level decreased from 8.8±1.3% at baseline to 7.2±1.1% at 26 weeks in the CGM group and from 8.7±1.2% to 8.0±1.4% in the routine-care group (adjusted mean difference, -0.9 percentage points; 95% confidence interval [CI], -1.1 to -0.6; P<0.001). The mean percentage of time that the CGM-measured glucose level was in the glucose-level range of 70 to 180 mg per deciliter was 21 percentage points higher (95% CI, 16 to 26) with CGM than with routine care (P<0.001). The between-group difference in the percentage of time that the glucose level was below 54 mg per deciliter was -0.17 percentage points (95% CI, -0.27 to -0.11; P<0.001 for noninferiority); the difference in the percentage of time that the glucose level was below 70 mg per deciliter was -0.20 percentage points (95% CI, -0.43 to -0.09; P<0.001 for noninferiority; P = 0.004 for superiority). No severe hypoglycemia events were reported.
CONCLUSIONS: Among adults with type 2 diabetes that was not being treated with insulin and was being managed in a primary care setting, the use of CGM led to a greater reduction in the glycated hemoglobin level and to a lower risk of hyperglycemia than routine care. (Funded by Dexcom; CONNECT ClinicalTrials.gov number, NCT06601166.).

DOI: https://doi.org/10.1056/NEJMoa2608571
J Diabetes Sci Technol. 2026 Oct 14. 19322968261489629

From Clinician-Based Risk Score to Diabetes Complications: Validating the Glycemia Risk Index with the Virtual Diabetes Control and Complications Trial Continuous Glucose Monitoring Data.

Mohammadreza Ganji, Benjamin Lobo, Anas El Fathi, Chiara Fabris, Boris Kovatchev.

   BACKGROUND: The glycemia risk index (GRI) is a validated continuous glucose monitoring (CGM)-derived metric of overall glycemic risk. Hemoglobin A1c (HbA1c) has been the gold-standard metric of glycemic control since the Diabetes Control and Complications Trial (DCCT). This study evaluates the relationship of GRI with long-term diabetes complications and compares its performance with HbA1c within the Virtual DCCT.
METHODS: The Virtual DCCT reconstructed CGM traces from HbA1c values and quarterly 7-point capillary glucose profiles collected during the original DCCT. Glycemia risk index values were computed from 14 days of CGM data. Rates of retinopathy progression were calculated across deciles of GRI and HbA1c. Poisson regressions quantified the relationship between each metric and complication risk. Receiver operating characteristic (ROC) curves evaluated the ability of GRI and HbA1c to discriminate between the DCCT intensive and conventional treatment groups.
RESULTS: Increased GRI was associated with higher rates of retinopathy progression (β=0.03, P < .001, D2=0.97). Comparable results were observed using HbA1c for retinopathy progression (β=0.47, P<.001, D2=0.93). The glycemia risk index also demonstrated separation between the intensive and conventional treatment groups, with an ROC area of 0.91 (95% CI, 0.90-0.93) compared to 0.88 (95% CI, 0.86-0.90) for HbA1c.
CONCLUSIONS: Glycemia risk index demonstrated a significant association with retinopathy progression within the Virtual DCCT framework. The relationship observed between GRI and retinopathy was comparable to that obtained using HbA1c. These findings extend the validation of GRI beyond clinician-based assessment and support its potential utility as a CGM-derived metric for glycemic risk assessment and diabetes complications.

Keywords:  Virtual DCCT; continuous glucose monitoring; glycemia risk index; machine learning; type 1 diabetes

DOI:  https://doi.org/10.1177/19322968261489629
Clin Chim Acta. 2026 Oct 15. pii: S0009-8981(26)02080-2. [Epub ahead of print] 122898

Beyond the glycation gap: A multicompartment framework for HbA1c-glycemia discordance in Pediatric type 1 diabetes.

Meiling Wang, Cunming Lv.

  HbA1c is analytically standardized but biologically indirect: the measured value integrates glucose exposure through erythrocyte survival, age distribution, intracellular glucose handling, hemoglobin chemistry, and assay behavior. Continuous glucose monitoring (CGM) has made this indirection clinically visible by revealing recurrent disagreement between laboratory HbA1c and sensor-derived glycemia in children and adolescents with type 1 diabetes. This focused narrative review reframes pediatric HbA1c-glycemia discordance as a measurement-biology problem rather than a single 'glycation gap.' We separate three non-equivalent residual constructs, organize the evidence across glucose exposure, extracellular protein glycation, and erythrocyte-dependent glycation, and introduce a trait-state-measurement decomposition of discordance. We distinguish glycated albumin from fructosamine, separate CGM analytical error from interstitial-glucose physiology and temporal representativeness, and grade mechanistic claims as established, supported-but-incomplete, or hypothesis-generating. Direct pediatric evidence confirms that discordance is common and partly persistent, but mechanistic adjudication remains limited because most studies measure only two domains. We therefore propose a hypothesis-localization framework - not a validated diagnostic or therapeutic algorithm - in which analytical validity and temporal alignment precede triangulation. The central aim is explainable disagreement: understanding why valid measurements differ before allowing the difference to influence care.

Keywords:  Continuous glucose monitoring; Fructosamine; Glycated albumin; Glycation gap; HbA1c; Pediatric type 1 diabetes

DOI:  https://doi.org/10.1016/j.cca.2026.122898
Br J Anaesth. 2026 Oct 12. pii: S0007-0912(26)00628-8. [Epub ahead of print]

Continuous glucose monitoring for diabetes mellitus in the perioperative and intensive care setting: a prospective observational validation study✰.

Casper Pedersen, Aslak B Johansen, Annelotte Philipsen, Kirsten Nørgaard, Theis S Itenov, Jonas P Eiberg, Lars N Jørgensen, Henrik Palm, Christian S Meyhoff, Eske K Aasvang.

   BACKGROUND: In-hospital diabetes mellitus management currently relies on intermittent glucose monitoring with point-of-care (POC) testing, rather than continuous glucose monitoring (CGM). Most studies on CGM have focused on its benefits and accuracy in the outpatient setting, in contrast to the hospital setting, where the accuracy may be different.
METHODS: In this prospective observational study (NCT06297850), we assessed the accuracy of CGM (Dexcom G7, Dexcom Inc.) compared with POC monitors in people with diabetes mellitus requiring glucose-lowering medication undergoing surgery or admission to the ICU. The primary outcome was agreement between CGM and POC measurements, defined as median absolute relative difference (MARD). Clarke error grid (CEG) and Bland-Altman analyses were used to quantify the accuracy. Secondary analyses assessed agreement during periods of hypoperfusion, defined as a mean arterial pressure of <65 mm Hg, infusions with vasopressors, or reduced peripheral perfusion index.
RESULTS: In 58 participants (mean [standard deviation] age 71 [11]yr; 34% female), the median MARD was 10.9% (5.1-19.4%); 1186 of 1212 paired POC and CGM measurements (98%) were within clinically acceptable ranges (CEG zones A and B). MARD was 4.5% higher (95% confidence interval 2.3-6.7%) during periods of hypoperfusion. Given that hypoglycaemia (<4 mM) did not occur, no paired readings were obtained. Bland-Altman analysis showed similar CGM and POC measurements, with a mean difference of -1 mM (95% limits of agreement -5.6 to 3.4 mM).
CONCLUSIONS: For the vast majority of interstitial glucose measurements, CGM was accurate in people with diabetes mellitus. Although overall performance was good, caution may be warranted when interpreting CGM data during periods of impaired peripheral perfusion.
CLINICAL TRIAL REGISTRATION: NCT06297850.

Keywords:  continuous glucose monitoring; critical illness; diabetic care; hypoperfusion; perioperative care

DOI:  https://doi.org/10.1016/j.bja.2026.08.014
J Clin Med. 2026 Sep 29. pii: 7581. [Epub ahead of print]15(19):

Continuous Glucose Monitoring for Women with Gestational Diabetes, CORDELIA: A Multicentric Randomized Controlled Trial, Methodology and Design.

Ina Geerts, Catherine Yu, Niels Bochanen, Ellen Heyns, Inge Van Pottelbergh, Astrid Morrens, Peter Coremans, Jean-Christophe Philips, Tiphaine Carton, Sara Vandewalle, Joke Marlier, Inge Van Boxelaer, Linsey Winne, Kathleen Bollaerts, Dahae Lee, David Simmons, Arianne Sweeting, Annouschka Laenen, Chantal Mathieu, Katrien Benhalima.

  Background/Objectives: Gestational diabetes mellitus (GDM) is associated with increased short- and long-term risks for both mother and child. Screening and treatment between 24 and 30 weeks' gestation reduces adverse pregnancy outcomes, while emerging evidence suggests that earlier diagnosis and treatment (<20 weeks') in high-risk populations may further improve neonatal outcomes. Currently, self-monitoring of blood glucose (SMBG) remains the standard of care for management but provides only intermittent glycemic data and limited insight into overall glucose patterns. Real-time continuous glucose monitoring (rt-CGM) has transformed management in pregnancies complicated by type 1 diabetes but has shown conflicting results in GDM; it is thus unclear whether similar benefits may extend to women with GDM, including women with early GDM. Methods: The Continuous Glucose Monitoring for Women With Gestational Diabetes (CORDELIA) study is an ongoing, large, open-label, multicenter randomized controlled trial conducted across 14 centers in Belgium and two centers in Australia. Women diagnosed with GDM are randomized in a 1:1 ratio to either rt-CGM (intervention group) or standard care with SMBG (control group). Both women with early GDM diagnosed before 20 weeks' gestation and those diagnosed between 24.0 and 29.6 weeks' gestation are included. Participants attend the following visits: baseline visit at GDM diagnosis, an additional visit at 20.0-23.9 weeks' (if early GDM), 31.0-33.6 weeks' and 36.0-38.6 weeks', and a postpartum oral glucose tolerance test (OGTT) assessment (6.0-23.6 weeks after delivery). At each visit, clinical assessment, HbA1c, and (blinded) CGM are evaluated, alongside validated patient-reported outcome questionnaires. The primary objective is to compare the incidence of a composite of adverse pregnancy outcomes between the rt-CGM and SMBG groups. The primary outcome is a composite of adverse pregnancy outcomes including preterm delivery <37 weeks, LGA [customized percentiles according to Gestation Related Optimal Weight chart (GROW)], neonatal hypoglycemia requiring intravenous dextrose, neonatal intensive care unit (NICU) admission > 24 h, neonatal respiratory distress, stillbirth or neonatal death, phototherapy, birth trauma, and shoulder dystocia. Secondary outcomes include maternal glycemia, insulin use, pregnancy and neonatal outcomes, glycemic variability, patient-reported outcomes, and prespecified secondary analyses according to timing of GDM diagnosis and maternal BMI. Trial Registration: ClinicalTrials.gov: NCT06310356. First posted: 15 March 2024.

Keywords:  continuous glucose monitoring; early gestational diabetes; gestational diabetes mellitus; pregnancy outcomes

DOI:  https://doi.org/10.3390/jcm15197581
Diabetes Obes Metab. 2026 Oct 15.

Association Between the GMI/HbA1c Ratio and Microvascular Complications in Type 1 Diabetes: A Multicenter Cross-Sectional Study.

Sandra Herranz-Antolín, María Asunción Martínez-Brocca, Gloria Cánovas-Molina, Aurora Aragón-Alonso, Miguel Brito-Sanfiel, Jose Ignacio Martínez-Montoro, Virginia Bellido, Sharona Azriel, María Del Carmen López-García, Cristina Tejera, Amparo Bartual, Verónica Perea, Pedro José Pines, Antonio J Amor, Óscar Moreno-Pérez, Rebeca Reyes-García, Gema López-Gallardo, María Durán-Martínez, Cristina Serrano, Rosa Márquez-Pardo, Noemí González-Pérez de Villar, Manuel Gargallo, Estefanía Santos, Pedro Pujante, Jessica Ares, Diego Bellido, Ignacio Conget, Fernando Gomez-Peralta.

   OBJECTIVE: To clarify whether the glucose management indicator (GMI)/glycated haemoglobin (HbA1c) ratio (GMI/HbA1c ratio) is an independent predictor of microvascular complications in Type 1 diabetes (T1D).
DESIGN AND METHODS: Multicentre, cross-sectional, observational study including subjects with T1D with at least 5 years of evolution, users of continuous glucose monitoring (CGM) with a coverage ≥ 80% 56 days prior to HbA1c. Logistic regression models were used to identify the factors independently associated with grouped microvascular complications and ocular disease.
RESULTS: As per data, 1315 participants were included. Patients were classified into tertiles based on the GMI/HbA1c ratio. High glycators were older than intermediate and low glycators (55.4 vs. 53.4 vs. 50.8 years; p < 0.001), respectively. Differences were also observed among the three groups with regard to average glucose (156.3 vs. 161.8 vs. 166.1 mg/dL; p < 0.001), time in range (66.3% vs. 62.9% vs. 59.9%; p < 0.001), time in tight range (42.9% vs. 39.9% vs. 37.1%; p < 0.001), coefficient of variation (34.5% vs. 34.9% vs. 35.6%; p = 0.023), GMI (7% vs. 7.2% vs. 7.3%; p < 0.001) and HbA1c (8.1% vs. 7.3% vs. 6.6%; p < 0.001). In the high glycators group, the prevalence of microvascular complications was higher than in the intermediate and low glycators (38.9% vs. 28.2% vs. 23.7%; p < 0.001), respectively. Also, the prevalence of ocular disease (31% vs. 20.2% vs. 19.7%; p < 0.001), nephropathy (14.9% vs. 8.3% vs. 6.2%; p < 0.001) and polyneuropathy (10.6% vs. 6.8% vs. 3.4%; p < 0.001) was higher in high glycators, The GMI/HbA1c ratio was significantly associated with the presence of grouped microvascular complications (OR 0.71; 95% CI: 0.61-0.81; p < 0.001) and ocular disease (OR 0.71; 95% CI: 0.61-0.82; p < 0.001) after adjusting for clinical ad glucometric variables.
CONCLUSIONS: The GMI/HbA1c ratio is associated with microvascular complications in this study. These results highlight the potential of this parameter in routine clinical practice for stratifying the risk of complications and for establishing individualized control goals and screening strategies.

Keywords:  GMI/HbA1c ratio; Type 1 diabetes; continuous glucose monitoring; fast glycator phenotype; microvascular complications

DOI:  https://doi.org/10.1111/dom.71385
Medicina (B Aires). 2026 ;86(5): 1260-1270

[Standardization of quality criteria for continuous glucose monitoring systems in Argentina].

Alejandro Dain, Rodrigo Carnero, Adriana Flores, María Laura Kabakian, Lorena Lequi, Matías A Ré, María Gabriela Rovira, Antonio Saleme.

Although glycated hemoglobin is the standard method for assessing glycemic control in people with diabetes mellitus (DM), this biomarker does not reflect circadian or daily glycemic variations, which means that episodes of hypoglycemia and/or hyperglycemia -which are associated with acute or chronic microvascular and macrovascular complications of DM- may go unnoticed. Continuous glucose monitoring (CGM) systems provide real-time glucose readings, allowing for the identification of trends and fluctuations throughout the day. These devices facilitate treatment decisions to optimize glucose control. Nevertheless, although CGM devices are associated with clinical benefits, limitations are recognized regarding the need for standardization, reliability, and outcomes across diverse populations and clinical settings. Our objective was to adapt the Consensus on Standardization of CGM Parameters for Latin America to Argentina using the ADAPTE method. Eleven of the existing recommendations were adopted with the addition of best practice guidelines; one recommendation was adapted to optimize its applicability; and three additional recommendations were generated based on expert opinion. The recommendations are directed at all members of the healthcare team who care for people with DM, decision-makers and health policy makers, and healthcare system funders, among others.

Keywords: Argentina; continuous glucose monitoring; diabetes mellitus
J Diabetes Sci Technol. 2026 Oct 14. 19322968261493981

Performance of a 15-Day Continuous Glucose Monitoring System in Children and Adolescents With Diabetes.

Manuela Link, Christian Denzer, Torben Biester, Jantje Weiskorn, Julian Ziegler, Franziska Liebrich, Désirée Dunstheimer, Jakob Krämer, Manuel Eichenlaub, Anne Beltzer, Martin Wabitsch, Guido Freckmann.

   BACKGROUND: The CareSens Air (CSAir) continuous glucose monitoring system is approved for use in adults in South Korea and received adults-only CE marking in early 2024. The aim of this prospective, multicenter, pivotal study in children and adolescents with insulin-dependent diabetes mellitus was to determine if the performance and safety of CSAir in these populations are comparable to those observed in adults.
METHOD: Sensors were worn for 15 days on the upper arm in children and adolescents aged 7 to 17 years and on the upper arm and/or upper buttock in children aged 2 to 6 years. Frequent capillary comparator measurements were performed during in-clinic sessions at the beginning, middle, and end of the sensor-wearing period. Point accuracy was assessed via agreement rates (AR) and mean absolute relative difference (MARD). Additional assessments included clinical point accuracy, technical reliability, and safety.
RESULTS: For subjects aged 7 to 17 years, %20/20 AR was 90.8%, and MARD was 8.9%. A total of 99.9% of values fell within Zones A and B of the Diabetes Technology Society error grid. Sensor survival probability reached 75.2%. In children aged 2 to 6 years, %20/20 ARs were 86.6% and 98.4%, and MARDs were 10.3% and 7.8% for arm- and buttock-worn sensors, respectively. No serious adverse events were reported. Mild and moderate adverse device effects comprised skin issues such as itching or erythema at the sensor application or insertion site.
CONCLUSIONS: The observed performance and safety of CSAir in children and adolescents are similar to those in adults. These data may support an extension of regulatory approval of CSAir for children aged 2 years and older.

Keywords:  CGM accuracy; CareSens Air; children and adolescents; type 1 diabetes

DOI:  https://doi.org/10.1177/19322968261493981
Biol Res Nurs. 2026 Oct 15. 10998004261498949

24-Hour Movement Behavior Reallocations and Glycemic Variability in Adults With Type 1 Diabetes: A Longitudinal Isotemporal Substitution Analysis.

Pei Chen, Bingqian Zhu, Chang Park, Mia Cajita, Minsun Park, Lisa Sharp, Cynthia Fritschi, Ali Cinar, Laurie Quinn.

  Background: Glycemic variability (GV) is an important cardiometabolic risk marker in adults with type 1 diabetes (T1D). We estimated the effects of reallocating time among sleep, sedentary behavior, light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) on six GV outcomes in adults with T1D. Methods: This secondary analysis included 23 adults contributing 102 days with concurrent accelerometer-based activity monitoring and continuous glucose monitoring (CGM). Compositional rescaling was applied to ensure a 24-h in total. Isotemporal substitution models with linear mixed-effects regression were used to estimate associations of 30-min reallocations among behaviors (e.g., from sleep to LPA) with GV outcomes, including standard deviation of glucose (SD), coefficient of variation (CV), large amplitude of glycemic excursions (LAGE), mean amplitude of glycemic excursions (MAGE), continuous overlapping net glycemic action with a 60-min lag (CONGA-60), and time in range (TIR), while adjusting for covariates. Results: Participants had a mean age of 32.6 years, BMI of 28.2 kg/m2, and diabetes duration of 16.3 years. Reallocating 0.5 hours from sleep to sedentary time, LPA, or MVPA significantly reduced CV (estimate range: -14.4 to -15.2, all p < 0.05) and TIR (estimate range: -3.6 to -3.6, all p < 0.01). Replacing sedentary time with LPA significantly reduced LAGE (estimate = -3.4, p = 0.035). No significant associations were found for SD, MAGE, or CONGA-60. Conclusion: These findings highlight that optimizing glycemic stability in adults with T1D requires a nuanced consideration of how reallocations between sleep, sedentary time, LPA, and MVPA differentially affect GV, TIR, and LAGE.

Keywords:  glycemic control; isotemporal substitution model; physical activity; sleep; type 1 diabetes

DOI:  https://doi.org/10.1177/10998004261498949
Diabetes Metab Syndr. 2026 Oct 01. pii: S1871-4021(26)00114-1. [Epub ahead of print]20(9): 103487

Evaluation of a local healthy moderate carbohydrate (LHMC) diet and structured exercise for diabetes remission in early type 2 diabetes mellitus: A nutrition intervention study from India.

Mayura Choudhari Kale, Vedavati Bharat Purandare, Shalbha Tiwari, Jaya Aherkar, Gayatri Kulkarni, Shital Manekar, A G Unnikrishnan.

   BACKGROUND: Lifestyle interventions can promote type 2 diabetes mellitus (T2D) remission, but prospective evidence on culturally adapted Indian Local Healthy Moderate Carbohydrate (LHMC) diets are limited.
OBJECTIVE: To assess remission and metabolic changes associated with a tailored LHMC diet combined with structured physical activity in adults with early T2D.
METHODS: This prospective, single-arm interventional study included adults with T2D duration ≤2 years from two centres in Maharashtra, India (n = 87). The 6-month intervention comprised a culturally adapted, LHMC diet and daily structured exercise. Glucose-lowering medications were discontinued at intervention initiation. The primary endpoint was diabetes remission, defined as HbA1c of <6.5% measured at least 3 months after stopping glucose lowering medications. Secondary outcomes included anthropometry, biochemical and continuous glucose monitoring (CGM) measures; diet and exercise adherence were monitored.
RESULTS: Seventy-five participants completed the 6-months intervention, with an estimated remission rate of 60.9% under the missing-at-random assumption. Clinically meaningful improvements were observed in weight, waist circumference, HbA1c, and lipid profile. Higher exercise adherence was independently associated with remission, in the context of baseline reduction of approximately 500 kcal/day. CGM metrics were more favourable in the remission group.
CONCLUSION: In this single-arm cohort of adults with early T2D, a culturally tailored LHMC diet combined with consistent exercise was associated with a 60.9% remission rate and improvements in metabolic parameters. The absence of a comparator limits causal inference; therefore, findings are hypothesis-generating and warrant confirmation in controlled studies. The results support the potential of scalable, region-specific lifestyle interventions in routine care.
CLINICAL TRIAL REGISTRY NUMBER AND WEBSITE: This study is registered with Clinical Trial Registry of India. (CTRI Reg. Date 18/08/2023 CTRI Reg. No. CTRI/2023/08/056,621).
STATEMENT OF NOVELTY: This work is the first to demonstrate more than 60% diabetes remission rates in recent-onset T2D using a culturally tailored, moderate calorie (around 1200 kcals) moderate-carbohydrate Indian diet and a simple, scalable walking-based regimen, rather than very low-calorie or highly restrictive diets that dominate existing remission trials. It is also novel in prospectively evaluating exercise adherence alongside CGM-derived metrics as practical, significantly associated predictors of remission in a real-world setting, despite not being prespecified.

Keywords:  Continuous glucose monitoring; Diabetes remission; Early type 2 diabetes mellitus; Local healthy moderate carbohydrate diet; Physical activity

DOI:  https://doi.org/10.1016/j.dsx.2026.103487
ACS Sens. 2026 Oct 12.

AI-Enhanced Wearable Glucose Sensors: From Intelligent Sensing to Closed-Loop Management of Diabetes.

Bo Sun, Lim Lee Ling, Mohamad Sofian Bin Abu Talip, Shixun Zheng, Yifu Fu, Quanjin Ma, Fazliyatul Azwa Md Rezali, Cheng Cheng, Yilin Peng, Sharifah F Wan Muhamad Hatta.

  Wearable glucose sensors enable continuous monitoring of glycemic dynamics, yet their clinical utility is constrained by signal instability, physiological delay, and limited predictive capability. Artificial intelligence (AI) has been increasingly integrated to address these limitations. This review summarizes recent advances in AI-enhanced wearable glucose sensors, with a focus on the evolution of sensing technologies and the role of AI across three main aspects: calibration, glucose prediction, and wearable closed-loop control. In calibration, AI-based approaches for improving short-term signal reliability and compensating long-term drift are reviewed. In prediction, methods ranging from continuous glucose monitoring (CGM)-based forecasting to multimodal sensor fusion and noninvasive sensing are summarized, including both continuous glucose estimation and event-oriented detection of hypo- and hyperglycemia. The integration of sensing, prediction, and insulin delivery in wearable closed-loop artificial pancreas is also discussed. Finally, the remaining challenges and future directions are discussed, highlighting the potential of AI-enhanced wearable glucose sensors to support more reliable and integrated diabetes management.

Keywords:  artificial intelligence; closed-loop glucose control; diabetes management; glycemic-event prediction; multimodal sensor fusion; wearable continuous glucose monitoring

DOI:  https://doi.org/10.1021/acssensors.6c02471
Am J Clin Nutr. 2026 Oct 10. pii: S0002-9165(26)00387-4. [Epub ahead of print] 101578

The Impact of a Low Glycemic Load Breakfast on Diurnal Glucose Profiles in Women with Gestational Diabetes Mellitus: The GLIDING Randomized Crossover Trial.

Jessica Burk, Glynis P Ross, Stephen Colagiuri, Grant D Brinkworth, Pennie Taylor, Emily Dunn, Synneva Hagen-Lillevik, Marie-France Hivert, Adrienne Gordon, Teri L Hernandez, Arianne Sweeting.

   BACKGROUND: Medical nutrition therapy is first-line treatment in gestational diabetes (GDM) management, yet evidence-based approaches remain lacking. In women with GDM, increased morning insulin resistance often results in postprandial (breakfast) hyperglycemia, potentially leading to increased 24-h glycemic variability (GV).
OBJECTIVE: In a short-term randomized crossover control trial, we compared the effects of a low glycemic load (GL) breakfast (LGL-B) to a high GL breakfast (HGL-B) on 1-h postprandial breakfast glucose (PPG) and 24-h GV (coefficient of variation [%CV]) in women with GDM.
METHODS: Women were provided an LGL-B (245 kcal; 10.9g carbohydrate) and HGL-B (247 kcal; 43.4g carbohydrate) in random order for 7 days, separated by a 7-day washout. Fasting blood was drawn on Days 1, 8, 15 and 22 (pre/post 7-day interventions) and blinded continuous glucose monitoring was undertaken. Breakfast 1-h PPG and %CV were analyzed using mixed effect models to compare between intervention effects with Bonferroni adjustments.
RESULTS: Of 32 women with GDM randomized (median 34.2 years, BMI 28.1 kg/m2, 27 weeks' gestation), 20 women completed both 7-day interventions and had ≥48-h CGM data for each breakfast intervention. Compared to an HGL-B, an LGL-B had lower 1-h PPG (HGL-B: mean 7.5 mmol/L [95% CI 7.2, 7.8]; 134 mg/dL [129, 140]; LGL-B: 5.0 mmol/L [4.7, 5.2]; 89 mg/dL [84, 94], p<0.001) and 24-h %CV (HGL-B: 20% [18, 21]; LGL-B: 17% [15, 18], p<0.001). There were no detectable differences between interventions for fasting lipids, ketones, satiety scores and physical activity.
CONCLUSIONS: In women with GDM, an LGL-B was associated with lower breakfast PPG and 24-h %CV. Targeting breakfast may be a simple dietary strategy to improve glycemia and reduce morning bolus insulin requirements.
TRIAL REGISTRATION: Australian and New Zealand Clinical Trials Registry (Identifier: ACTRN12623000425695) URL: https://anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12623000425695.

Keywords:  Breakfast; Coefficient of Variation; Continuous glucose monitoring; Gestational diabetes; Glycemic variability; High glycemic load; Low glycemic load; Postprandial glucose

DOI:  https://doi.org/10.1016/j.ajcnut.2026.101578
Anal Chim Acta. 2026 Nov 22. pii: S0003-2670(26)01129-3. [Epub ahead of print]1424 346179

Uncovering allergen presence and accumulation in glucose monitoring systems: evidence of a "sponge effect" via validated GC-MS.

Asia Saorin, Sarah Watson, Colin P Hawkes, John F Bourke, Niamh M O'Boyle.

   BACKGROUND: Despite the clinical benefits associated with the use of continuous and flash glucose monitoring systems (GMS), they are frequently associated with dermatological adverse effects, most notably allergic contact dermatitis (ACD). Chemical analysis of devices is often the only means to confirm the presence of suspected sensitizers or detect emerging allergens in these products. Although previous research efforts lead to the identification of some main allergens such as acrylates and colophony compounds, new allergens continue to emerge and the presence of known allergens in devices cannot be excluded. However, no validated quantitative analytical methods for these compounds in GMS have been reported.
RESULTS: A quantitative gas chromatography-mass spectrometry (GC-MS) method was developed and validated, with a focus on optimizing the extraction from the devices. An untargeted screening workflow was incorporated to detect additional potentially relevant allergens. Targeted analysis enabled quantification (14 compounds) or estimated abundance analysis determination (5 compounds) of relevant allergens. The method was applied to unused and used Dexcom G7 and associated adhesive patches. Different allergens were detected and quantified including isobornyl acrylate, methyl dehydroabietate, and isocyanates. Other compounds were only detected in used devices, such as cetyl alcohol, isopropyl palmitate and isopropyl myristate.
SIGNIFICANCE: The analysis revealed the presence of known and new allergens in medical devices for diabetes. Several allergens were present in unused devices, but others were detected only in used devices. These additional compounds likely accumulated from daily usage, leading to what we defined as the "sponge effect".

Keywords:  Allergic contact dermatitis; Diabetes; Extractables; GC-MS; Glucose monitoring systems; Sensitizers; Validation

DOI:  https://doi.org/10.1016/j.aca.2026.346179