bims-glumda 2026-09-13 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2026–09–13
sixteen papers selected by
Mott Given

Anticipatory Communication About Diabetes Technology in Schools: An Inoculation Theory Approach.
Continuous glucose monitoring devices in hospitalized pediatric patients.
Conflicting evidence for continuous glucose monitoring in gestational diabetes: current challenges and the imperative for individual participant data meta-analysis.
Real-World Data from U.S. Commercial Users of the 365-Day Implantable Eversense Continuous Glucose Monitoring System, Including with the Twiist Automated Insulin Delivery System Integration.
Pediatric Inpatient Continuous Glucose Monitor Accuracy by Sensor Wear Day, Hospital Day, and Glucose Rate of Change.
Continuous glucose monitoring using the FreeStyle Libre Pro iQ in presymptomatic type 1 diabetes.
Can continuous glucose monitoring-derived glycemic variability predict retinal neurodegeneration earlier than HbA1c in patients without clinically apparent retinopathy?
American Association of Clinical Endocrinology Consensus Statement: Use of Diabetes Technology for Management of Adults with Diabetes.
Parental Preferences for Continuous Glucose Monitoring Devices in Children with Type 1 Diabetes: A Pilot Discrete Choice Experiment with Sensitivity Analysis of Decision Consistency.
Preserved cardiac vagal tone is associated with nocturnal glycaemic stability.
Postpartum Glycaemic Phenotype and Continuous Glucose Monitoring at 4-6 Years After Gestational Diabetes Defined by Different Diagnostic Criteria.
Interventions to reduce diabetes-related distress among adults with type 1 or type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials.
Single-dose dexamethasone increases perioperative glycemic variability in older patients with diabetes undergoing lung surgery: a continuous glucose monitoring-based randomized controlled trial.
Exploratory association of OGTT area under the curve with early-night glycemic patterns and pharmacotherapy use in gestational diabetes mellitus.
Complexity analysis of physiological signals in the wearable era: New insights into chronic diseases and aging.
Comparison of somatic development, nutritional status, control of disease, and frequency of autoimmune comorbidities in Polish and Ukrainian children with type 1 diabetes.

J Diabetes Sci Technol. 2026 Sep 06. 19322968261484919

Anticipatory Communication About Diabetes Technology in Schools: An Inoculation Theory Approach.

Josh Compton.



Keywords:  continuous glucose monitoring; diabetes technology; health communication; inoculation theory; schools; type 1 diabetes

DOI:  https://doi.org/10.1177/19322968261484919
Crit Rev Clin Lab Sci. 2026 Sep 05. 1-11

Continuous glucose monitoring devices in hospitalized pediatric patients.

Isaiah K Mensah, Christopher W Farnsworth.

  Continuous glucose monitoring (CGM) has revolutionized the landscape of diabetes management both in adults and pediatrics. CGM devices are now standard-of-care for pediatric diabetes management and are increasingly used in hospitalized patients. In the outpatient setting, studies show increasing analytical and clinical performance of CGM devices with improved diabetes outcomes. However, there are several inpatient factors that impact the accuracy of CGM devices relevant to hospitalized patients. The pediatric population is also the most vulnerable, and changes in management based on a false CGM reading can cause adverse events. Therefore, it is imperative to critically assess the accuracy and clinical performance of CGM devices in hospitalized pediatric patients. In this review, we assess the literature and summarize recent studies on the accuracy of CGM devices in pediatric inpatients, discuss regulatory requirements for their use, safety considerations, and procedures for confirmatory testing using standard-of-care glucose tests.

Keywords:  CGM; glucose; pediatrics

DOI:  https://doi.org/10.1080/10408363.2026.2722682
BMC Med. 2026 08 27. pii: 476. [Epub ahead of print]24(1):

Conflicting evidence for continuous glucose monitoring in gestational diabetes: current challenges and the imperative for individual participant data meta-analysis.

Ina Geerts, Catherine Yu, Nina Embo, Katrien Benhalima.

   BACKGROUND: The incidence of gestational diabetes mellitus (GDM) is rising along with rates of obesity and type 2 diabetes. GDM is associated with an increased risk of various short- and long-term complications for both mother and child, including type 2 diabetes. Managing GDM requires a multidisciplinary approach that includes dietary guidance, promoting regular physical activity, and performing self-monitoring of blood glucose (SMBG). Continuous glucose monitoring (CGM) has transformed pregnancy care in women with type 1 diabetes and is increasingly being proposed as a strategy to improve glycaemic management in GDM. By capturing postprandial glucose excursions, glycaemic variability, and time in range, CGM provides a more detailed picture of glycaemia and has raised expectations of improved metabolic control and pregnancy outcomes.
MAIN BODY: Despite these theoretical advantages, evidence for CGM in GDM remains conflicting. More recently, several large randomized controlled trials (RCT's) show conflicting data: some studies show modest improvements in glycaemic measures, whereas others report no clear benefit for key maternal or neonatal outcomes, leaving the clinical value and cost-effectiveness of CGM unclear. A major limitation is the absence of validated CGM-based glycaemic targets specific to GDM, and current guidelines offer little direction beyond conventional SMBG guidelines. Future research should prioritize adequately powered large RCT's representing a broad population, and, importantly, individual participant data meta-analyses to reconcile inconsistent findings, identify subgroups most likely to benefit, establish pregnancy-specific CGM thresholds, and evaluate the impact on both obstetric outcomes and long-term postpartum metabolic risk.
CONCLUSIONS: This ongoing debate underscores the need to critically appraise the role of CGM in GDM, summarize results from completed RCT's and meta-analyses, recognize key methodological and clinical evidence gaps, and outline the steps required for CGM to become fully integrated into standard GDM care.

Keywords:  Continuous glucose monitoring; Gestational diabetes mellitus; Individual participant data meta-analysis; Pregnancy; Technology

DOI:  https://doi.org/10.1186/s12916-026-05191-2
Diabetes Technol Ther. 2026 Sep 08. 15209156261486125

Real-World Data from U.S. Commercial Users of the 365-Day Implantable Eversense Continuous Glucose Monitoring System, Including with the Twiist Automated Insulin Delivery System Integration.

Francine Kaufman, Ishaan Jain, Shaoling Han, Colleen Mdingi.

   BACKGROUND: The Eversense 365 Continuous Glucose Monitoring (CGM) System is the first implantable, 1-year CGM approved in the United States and Europe. In February 2026, Eversense 365 became available in the United States with the twiist automated insulin delivery (AID) pump and twiist loop algorithm. While clinical trial performance has been reported, this article describes the real-world experience with the Eversense 365 CGM system using open-loop therapies and with the twiist AID system.
METHODS: Deidentified sensor glucose (SG) data from the Eversense Data Management System were analyzed for the first 12,360 sensors used with open-loop therapies. Analysis included mean SG, glucose management indicator (GMI), percent in glycemic ranges and achieving hypoglycemia targets, and median transmitter wear time. Performance across the full 365-day duration and between the first and second 180-day periods was evaluated. For the twiist AID system, analysis included 153 sensors with >30 days following twiist pairing.
RESULTS: For the 365 CGM system in open-loop, the mean age was 57 years. A mean of 43,225 (±32,394) CGM readings per sensor were available. Mean SG was 161 mg/dL, and GMI was 7.16%. Mean percent time < 54 mg/dL was 0.6%, <70 mg/dL 2.7%, 70-180 mg/dL (time in range, TIR) 66.2%, >180 mg/dL 31.2%, and >250 mg/dL 9.8%. Median transmitter wear time was 93%. Glycemic outcomes remained stable across the first and second 180-day periods. For users of the twiist + Eversense 365 AID system, mean SG was 145 mg/dL, GMI 6.78%, and TIR 76.1%, with 2.3% <70 mg/dL and 0.5% <54 mg/dL, and 99% median transmitter wear time.
CONCLUSION: In this large real-world dataset, the 365-day CGM system demonstrated high adherence and favorable glucometrics sustained over extended wear. Early data from the twiist + Eversense 365 system support integration of the implantable CGM within an AID system to support consistent and reliable insulin delivery.

Keywords:  365-day CGM; Type 1 diabetes; Type 2 diabetes; adherence; continuous glucose monitoring; glucometrics; implantable sensor; real-world data; time in range (TIR); twiist AID

DOI:  https://doi.org/10.1177/15209156261486125
Diabetes Technol Ther. 2026 Sep 10. 15209156261486139

Pediatric Inpatient Continuous Glucose Monitor Accuracy by Sensor Wear Day, Hospital Day, and Glucose Rate of Change.

Jessica L Ruiz, Amy B Stein, Alexander Wheelock, Bennett Stewart, Allison S Bernique, Emily Jost, Katharine C Garvey, Christina M Astley, Erin C Cobry.

   BACKGROUND: Continuous glucose monitoring (CGM) improves glycemic outcomes but inpatient use in the United States is not FDA approved, despite the potential need for frequent glycemic monitoring during hospitalization. We sought to assess CGM accuracy in the pediatric hospital setting and to evaluate the impact of potential modifiers of accuracy, including sensor wear day, hospitalization day, and glucose changes.
METHODS: In this retrospective cross-sectional accuracy study among youth and young adults with diabetes hospitalized at two pediatric centers, reference point-of-care (POC) capillary glucose values were compared with Dexcom G7 CGM glucose readings (paired within 5 min). Accuracy was assessed using standard metrics, including mean absolute relative difference (MARD) and Parkes error grids, overall, and stratified by sensor wear day, hospital day, and CGM glucose rate of change.
RESULTS: We analyzed 544 POC-CGM glucose pairs from 68 participants with diabetes aged 2-22 years (mean 12.4 ± 5.8 years old, 58.8% female, 66.2% White, 8.8% Hispanic) during 80 hospital encounters. The overall MARD was 12.5%. Accuracy was comparable on sensor wear day 1 and days 2-6 (MARD 12.3% vs 13.6%, respectively) and was best on wear days 7-10 (MARD 10.6%). Accuracy improved from hospital day 1 (MARD 13.7%) to hospital days 2-4 and 5-30 (MARD 10.4% and 12.5%, respectively). Overall and on wear day 1, almost all glucose pairs (99%) fell within low-risk Parkes error grid zones A and B. Accuracy was best with a flat [-1 to 1 mg/(dL·min)] rate of change (MARD 11.5%-11.9%) and was reduced with rapidly rising or falling [beyond -2 or 2 mg/(dL·min)] CGM values (MARD 16.6%-18.4%).
CONCLUSIONS: In this pediatric hospital CGM accuracy study, MARD was within a favorable range of <14% overall and throughout sensor wear and hospitalization. Reduced accuracy with rapidly changing glucose highlights the need to incorporate trend arrows into hospital CGM protocols.

Keywords:  CGM; CGM rate of change; CGM trend arrows; accuracy; hospital technology; pediatric diabetes

DOI:  https://doi.org/10.1177/15209156261486139
Diabetologia. 2026 Sep 07.

Continuous glucose monitoring using the FreeStyle Libre Pro iQ in presymptomatic type 1 diabetes.

Andreas Weiss, Elisabeth Huber, Franziska Reinmüller, Annette Munzinger, Ezio Bonifacio, Anette-Gabriele Ziegler.

   AIMS/HYPOTHESIS: The aim of the study was to evaluate the ability of the FreeStyle Libre Pro iQ continuous glucose monitoring (CGM) system to discriminate between presymptomatic stages of type 1 diabetes and stratify progression to stage 3 type 1 diabetes. The study also aimed to compare the performance of the FreeStyle Libre Pro iQ with that of the Dexcom G6.
METHODS: From December 2023 to December 2025, 50 children and adolescents without islet autoantibodies (control participants) and 89 with early-stage (stage 1 or 2) type 1 diabetes underwent CGM with the FreeStyle Libre Pro iQ. Participants with early-stage type 1 diabetes were followed up for the development of stage 3 clinical type 1 diabetes.
RESULTS: CGM data were unavailable or incomplete for 13 participants (9%), leaving 126 (91%) for analysis (73 female, median age 10.0 years [IQR 7.9-12.8]). The CGM parameters used-namely the SD, CV, time with glucose levels above 7.8 mmol/l (140 mg/dl; TA140) and 8.9 mmol/l (160 mg/dl; TA160) and time in tight range-differed significantly across participants with no early-stage, stage 1 or stage 2 type 1 diabetes, and between participants with a single dysglycaemia abnormality and those with multiple dysglycaemia abnormalities. One or more of these parameters exceeded the 97.5th percentile of control values in 10 (22%) of the 45 individuals with stage 1 type 1 diabetes and in 13 (52%) of the 25 individuals with stage 2 type 1 diabetes (p=0.017). Two or more of the parameters exceeded the 97.5th percentile threshold in six (13%) of the individuals with stage 1 type 1 diabetes and 11 (44%) of the individuals with stage 2 type 1 diabetes (p=0.0077). The 97.5th percentile threshold for TA140 (i.e. >15%) was exceeded by none of the 45 individuals with stage 1 type 1 diabetes, 10 (40%) of the 25 individuals with stage 2 type 1 diabetes and six of the eight individuals who progressed to clinical diabetes within 1 year, identifying these individuals as rapid progressors. FreeStyle Libre Pro iQ values differed markedly from those previously observed using the Dexcom G6 in a similar cohort. Using the 97.5th percentile of values of control individuals to define CGM abnormalities enabled harmonisation across systems and supported the consistent identification of high-risk individuals. With this approach, the sensitivity for identifying those who progressed to clinical diabetes within 1 year ranged from 75% to 100% for the FreeStyle Libre Pro iQ and from 50% to 100% for the Dexcom G6.
CONCLUSIONS/INTERPRETATION: These findings support CGM as a promising tool for staging and risk stratification in early-stage type 1 diabetes, while highlighting the need for system-specific interpretation before use in therapeutic decision-making.

Keywords:  Continuous glucose monitoring; Early-stage type 1 diabetes; Glucose variability; Paediatrics; Presymptomatic type 1 diabetes; Risk stratification; Staging; Time in tight range; Type 1 diabetes

DOI:  https://doi.org/10.1007/s00125-026-06852-w
Front Endocrinol (Lausanne). 2026 ;17 1925994

Can continuous glucose monitoring-derived glycemic variability predict retinal neurodegeneration earlier than HbA1c in patients without clinically apparent retinopathy?

Yixiang Su, Guang Han, Qinghua Su.

  Early screening for diabetic retinopathy (DR) has long relied on the detection of fundus vascular lesions. However, accumulating evidence indicates that retinal neurodegeneration may occur before overt microvascular abnormalities become clinically visible. At the stage of no clinically apparent diabetic retinopathy (NDR), glycated hemoglobin A1c (HbA1c), by virtue of its averaging nature, is unable to adequately reflect the acute metabolic stress imposed by short-term glycemic variability (GV) on the retinal neurovascular unit (NVU). The increasing use of continuous glucose monitoring (CGM) has made dynamic glycemic metrics such as time in range (TIR) and coefficient of variation (CV) clinically accessible. This review summarizes the clinical and mechanistic evidence supporting CGM-derived GV metrics in the association with early retinal injury in patients with NDR. Mechanistic studies indicate that fluctuating hyperglycemia induces mitochondrial oxidative stress more readily than sustained hyperglycemia and can activate Müller cell- and microglia-mediated neuroinflammation while disrupting tight junctions within the blood-retinal barrier. Clinical studies further show that reduced TIR and elevated CV are associated with early thinning of the retinal nerve fiber layer and reduced microvascular density, and some of these associations remain significant after adjustment for HbA1c. On this basis, we propose a dual-dimensional risk assessment strategy combining HbA1c with TIR/CV and suggest that patients with NDR who exhibit marked glycemic variability on CGM should undergo intensified monitoring. Integrating dynamic CGM metrics with optical coherence tomography (OCT) and OCT angiography (OCTA) may enable risk stratification during the NDR stage and shift the intervention window for DR forward to a critical phase for neuroprotection.

Keywords:  continuous glucose monitoring; diabetic retinopathy; early warning; glycated hemoglobin; glycemic variability; retinal neurodegeneration; time in range

DOI:  https://doi.org/10.3389/fendo.2026.1925994
Endocr Pract. 2026 Sep 08. pii: S1530-891X(26)01046-3. [Epub ahead of print]

American Association of Clinical Endocrinology Consensus Statement: Use of Diabetes Technology for Management of Adults with Diabetes.

Janet B McGill, Amy C Donihi, Halis K Akturk, Matthew Freeby, Abhinav Gupta, William B Horton, M Nauman Jadoon, Sanam Lathief, Sigfrido Miracle-Lopez, Charity Tan, Rodolfo J Galindo.

   OBJECTIVE: To provide evidence-informed guidance to assist with shared decision making in the use of advanced technology for the management of adults with diabetes mellitus.
METHODS: An international task force composed of AACE members with expertise in diabetology and endocrinology reviewed the recent evidence and developed updated guidance for advanced diabetes technology. Relevant studies were identified through a literature review process, and evidence was summarized with key practice points for use of technology in relevant populations. Consensus on the document was obtained through virtual meetings and communications with the task force.
RESULTS: The task force deliberated on areas where evidence supports the use of advanced diabetes technology in different populations of individuals with diabetes mellitus. Also discussed were best practices and implementation considerations for the successful adoption of diabetes technology by individuals with all types of diabetes and their health care professionals.
CONCLUSIONS: This consensus statement aims to provide updated information for health care professionals involved in care for adults with diabetes mellitus. It reviews current evidence that informs best practices in the use of continuous glucose monitoring devices, automated insulin-delivery systems, and other insulin delivery devices, in addition to emerging technologies such as continuous ketone monitoring.

Keywords:  automated insulin delivery; continuous glucose monitoring; continuous subcutaneous insulin infusion; diabetes; diabetes technology; glucose sensors; hybrid closed loop; insulin pumps

DOI:  https://doi.org/10.1016/j.eprac.2026.06.011
Patient Prefer Adherence. 2026 ;20 635823

Parental Preferences for Continuous Glucose Monitoring Devices in Children with Type 1 Diabetes: A Pilot Discrete Choice Experiment with Sensitivity Analysis of Decision Consistency.

Ying Liu, Junlin Huang, Congli Chen, Jin Wu.

   Background: Continuous glucose monitoring is increasingly used in pediatric type 1 diabetes management, but families may value device characteristics differently and may trade off convenience, safety-related functions, remote data access, sensor replacement burden, and cost.
Purpose: This pilot discrete choice experiment explored parental preferences for continuous glucose monitoring device attributes among Chinese families of children with type 1 diabetes and examined the robustness of preference estimates under alternative respondent-inclusion and modeling strategies.
Patients and Methods: Parents or legal guardians of children with type 1 diabetes completed an online discrete choice experiment. Each of ten core choice tasks presented two hypothetical continuous glucose monitoring devices and an opt-out option representing maintenance of the child's current monitoring strategy. Five attributes were included: measurement and calibration, low-glucose alert, remote monitoring, sensor replacement frequency, and monthly cost. The revised primary analysis excluded only responses with implausible or atypical completion times and retained respondents who failed the dominance task or consistently selected the opt-out option. Non-cost attributes were modeled categorically using effects-coded conditional logit models with cluster-robust standard errors at the respondent level. Sensitivity analyses applied alternative respondent-inclusion criteria.
Results: Among 79 initial responses, 75 respondents were included in the revised primary analysis, contributing 750 core choice tasks and 2250 alternative-level observations. Real-time remote monitoring with automatic push notification showed a positive association with device choice in the revised primary analysis, although the estimate did not reach conventional statistical significance. This attribute remained positive and statistically significant in sensitivity analyses excluding dominance-task failures, excluding consistent opt-out respondents, and applying the original strict quality-control criteria. A 14-day sensor replacement frequency was positively associated with device choice in the revised primary analysis, whereas 30-day replacement did not show a consistent additional preference advantage. Measurement/calibration, low-glucose alert functions, and monthly cost showed less stable associations across analyses. Exploratory relative-importance analysis suggested that remote monitoring may be an important preference driver. Willingness-to-pay estimates were exploratory and should be interpreted cautiously because of imprecision in the cost coefficient.
Conclusion: In this pilot study, real-time remote monitoring emerged as the most consistent positive preference signal for continuous glucose monitoring device choice among parents of children with type 1 diabetes. Preferences for sensor replacement frequency appeared nonlinear, and estimates for other attributes were less stable. These findings are exploratory and hypothesis-generating, highlighting the need for larger multicenter studies with prespecified methods to examine preference heterogeneity and willingness to pay.

Keywords:  caregiver preference; continuous glucose monitoring; discrete choice experiment; parental preferences; shared decision-making; type 1 diabetes; willingness to pay

DOI:  https://doi.org/10.2147/PPA.S635823
Diabetologia. 2026 Sep 09.

Preserved cardiac vagal tone is associated with nocturnal glycaemic stability.

Maria Bitsch Poulsen, Simon Lebech Cichosz, Peter Julu, Johan Røikjer, Asbjørn Mohr Drewes, Christina Brock.

   AIMS/HYPOTHESIS: Parasympathetic dysfunction is implicated in the pathogenesis of type 2 diabetes; however, its relationship with glucose regulation remains poorly understood. Thus, the aim of this study was to investigate the association between central parasympathetic function assessed as cardiac vagal tone (CVT) and continuous glucose monitoring (CGM) outcomes during sleep in individuals with and without type 2 diabetes.
METHODS: This cross-sectional study included 20 individuals without diabetes and 40 individuals with type 2 diabetes, aged 45-75 years. They were home-monitored for 72 h, comprising nocturnal recordings of ECG-derived CVT measured using the ProCVT SmartSheet and Dexcom G6 CGM blinded to participants. Mean CVT was dichotomised into 'normal' CVT (≥5.0) and 'poor' CVT (<5.0). Only individuals for whom ≥70% of the total recording was classified as valid noise-free ECG data were analysed (N=50).
RESULTS: Across all individuals, higher nocturnal CVT predicted a lower coefficient of variation in glucose (β=-0.8, p=0.030) and greater time in tight range (β=5.2, p=0.001). In individuals without diabetes, higher CVT was associated with reduced risk of hyperglycaemia (-10.2%, p=0.015), time above range (-11.8%, p=0.015) and time in moderate hyperglycaemia (-11.8%, p=0.015), and increased glucose mobility (β=0.014, p=0.029). In all individuals, poor CVT at the 15 min segment level was associated with a 1.9% increase in glucose in the subsequent period (p=0.049).
CONCLUSIONS/INTERPRETATION: Preserved CVT, indicating normal central parasympathetic tone, is associated with a stable and dynamically regulated glucose profile with reduced adverse glucose mobilisation during sleep. This may have implications for glycaemic regulation in individuals with autonomic neuropathy.

Keywords:   Glycaemic variability; Autonomic nervous system; Cardiac vagal tone; Continuous glucose monitoring; Glucose regulation; Parasympathetic nervous system; Type 2 diabetes

DOI:  https://doi.org/10.1007/s00125-026-06844-w
J Diabetes Res. 2026 ;2026(1): e7103883

Postpartum Glycaemic Phenotype and Continuous Glucose Monitoring at 4-6 Years After Gestational Diabetes Defined by Different Diagnostic Criteria.

Ulrika Andersson-Hall, Emilia Kristiansson, Sebastian Åberg, Matilda Törnqvist, Kristina Wallenius, Verena Sengpiel, Agneta Holmäng.

   AIM: To characterise glycaemic outcomes 4-6 years postpartum according to gestational diabetes mellitus (GDM) diagnostic thresholds and evaluate whether continuous glucose monitoring (CGM) identifies differences not captured by conventional clinical measures.
METHODS: Women recruited before and after introduction of WHO GDM criteria were followed at 4 and 6 years postpartum. At each follow-up, participants underwent oral glucose tolerance testing (OGTT), HbA1c measurement, body composition assessment and 14-day CGM. Based on pregnancy OGTT results and the diagnostic criteria in use at the time of testing, women were classified as meeting EASD 1991 criteria (GDMOLD; higher glucose thresholds), meeting WHO 2013 criteria but not EASD 1991 without diagnosis and treatment (GDMWHO-) or meeting WHO 2013 criteria with diagnosis and treatment (GDMWHO+).
RESULTS: Women classified as GDMOLD had higher fasting glucose at both follow-ups compared with women meeting only WHO 2013 criteria, and showed greater hyperglycaemic exposure and glycaemic variability on CGM. Time above range, coefficient of variation and mean amplitude of glycaemic excursions were consistently higher in GDMOLD group, and differences remained significant after adjustment for pregnancy glucose levels. Within the WHO-defined groups, conventional clinical measures did not differ between women with and without a GDM diagnosis, whereas CGM detected modest differences in mean glucose and time above range over time. Approximately 50% of women meeting only WHO 2013 criteria had prediabetes. CGM metrics were strongly associated with OGTT-derived glucose and HbA1c but only weakly with anthropometric and blood lipid measures. BMI and body fat percentage did not differ between groups.
CONCLUSIONS: Long-term glycaemic risk aligns with diagnostic thresholds used during pregnancy. Women diagnosed by older, higher thresholds exhibit a persistently less favourable glycaemic profile. Women meeting the lower WHO 2013 glucose thresholds represent a large group with a high prevalence of prediabetes, regardless of diagnosis during pregnancy. CGM detects modest differences in free-living glycaemic patterns not apparent from conventional clinical measures.

Keywords:  Type 2 diabetes; continuous glucose monitoring; gestational diabetes; glycaemic variability; postpartum; prediabetes

DOI:  https://doi.org/10.1155/jdr/7103883
Diabetologia. 2026 Sep 11.

Interventions to reduce diabetes-related distress among adults with type 1 or type 2 diabetes: a systematic review and meta-analysis of randomised controlled trials.

Samantha B J Schipper, Thomas Karagiannis, Francesco Zaccardi, Sharon Remmelzwaal, Marieke Blom, Noa Dagan, Linda J Schoonmade, Miranda Langendam, Martin M Jensen, Walther Jensen, Norbert Hermanns, Karin Kanc, Michelle Law, Andreia Mocan, Theresa C Mohr, Maartje de Wit, Petra J M Elders, Jackie Sturt, Joline W Beulens, Jane Speight, Richard I G Holt, Femke Rutters.

   AIMS/HYPOTHESIS: Diabetes distress refers to the emotional and psychological burden specifically associated with living with and managing diabetes. We aimed to systematically identify, summarise and critically appraise the available evidence from RCTs assessing the efficacy of interventions for reducing diabetes distress among adults with type 1 or type 2 diabetes.
METHODS: We searched PubMed, the Cochrane Library, APA PsycInfo and CINAHL from inception until 23 September 2024. Studies were eligible if they were RCTs conducted in adults (aged ≥18 years) with type 1 or type 2 diabetes in which the effect of an active intervention on diabetes distress was recorded as a primary or a secondary outcome. Studies with combined populations (e.g. children plus adults) where no separate results were reported for adults were excluded. When possible, we performed a random-effects meta-analysis of the standardised mean difference (SMD) of the endpoint, diabetes distress, measured with a validated questionnaire. We conducted subgroup analyses based on baseline diabetes distress level, intervention delivery method, risk of bias assessment (using the Cochrane RoB2 tool) and trial duration. We used GRADE methodology to assess the certainty of evidence.
RESULTS: We included 248 trials, with 59 trials reporting on psychological interventions, 68 on psychoeducational interventions and 121 on miscellaneous interventions (non-psychological or non-psychoeducational, i.e. education without a psychological component, peer support without a psychological component, devices, telehealth, health behaviours and a heterogeneous group of other interventions). In total, 52 trials included participants with type 1 diabetes (including two during pregnancy), 160 included participants with type 2 diabetes, and 36 included mixed/undefined populations of adults with diabetes. The total sample size was 55,497 participants (range 12-4034). The analysed trials were judged to have either some concerns for risk of bias (94 trials) or a high risk of bias (71 trials). Compared with usual care, psychological interventions reduced diabetes distress in adults with type 1 diabetes (SMD -0.22 [95% CI -0.35, -0.08]; N=16; GRADE = low) and type 2 diabetes (SMD -0.31 [95% CI -0.50, -0.13]; N=21; GRADE = very low). Additionally, continuous glucose monitoring (CGM) or intermittently scanned glucose monitoring reduced diabetes distress in adults with type 1 diabetes, compared with standard blood glucose measurement (SMD -0.26 [95% CI -0.41, -0.11]; N=6; GRADE = moderate), while educational interventions reduced diabetes distress in adults with type 2 diabetes, compared with usual care (SMD -0.34 [95% CI -0.56, -0.11]; N=3; GRADE = low). Other comparisons, including those of psychological, psychoeducational, peer support, educational and device-based interventions with various active control interventions or usual care, did not show statistically significant effects. The results did not differ meaningfully across predefined subgroups. The certainty of evidence as assessed by GRADE methodology was moderate, low or very low in two, five and seven comparisons, respectively. No meta-analyses could be conducted for telehealth, health behaviours and the assorted mixed interventions due to heterogeneity or an insufficient number of studies.
CONCLUSIONS/INTERPRETATION: Psychological interventions reduced diabetes distress among adults with type 1 diabetes and those with type 2 diabetes, while devices reduced diabetes distress in adults with type 1 diabetes and education reduced diabetes distress in adults with type 2 diabetes. Most other interventions showed little or no clear effect.
FUNDING: European Association for the Study of Diabetes.
REGISTRATION: PROSPERO registration no. CRD42024598512.

Keywords:  Continuous glucose monitoring; Diabetes distress; Meta-analysis; Psychoeducational interventions; Psychological interventions; Randomised controlled trials; Systematic review; Type 1 diabetes; Type 2 diabetes

DOI:  https://doi.org/10.1007/s00125-026-06789-0
Front Med (Lausanne). 2026 ;13 1880028

Single-dose dexamethasone increases perioperative glycemic variability in older patients with diabetes undergoing lung surgery: a continuous glucose monitoring-based randomized controlled trial.

Xiaoyi Zhang, Cheng Huang, Xiang Wang, Jun Zhang, Xiaomei Ling, Jiahao Xu, Jue Ma, Fei Zhong, Haihua Shu.

   Objectives: To investigate whether a single intraoperative dose of dexamethasone alters perioperative glycemic dynamics in older patients with type 2 diabetes undergoing thoracoscopic lung resection. Glycemic dynamics were captured using continuous glucose monitoring (CGM).
Methods: 72 patients aged ≥ 60 years with type 2 diabetes who underwent elective thoracoscopic lung resection were randomly assigned to receive either 8 mg of dexamethasone or placebo (0.9% saline) intravenously during anesthesia induction. The primary outcome was the maximum change in intraoperative blood glucose from preoperative baseline. Key secondary outcomes included CGM-derived glycemic variability (GV) metrics, including standard deviation (SD), coefficient of variation (CV), blood glucose instability index (GLI) and time-in-range measures, assessed throughout the perioperative period. Multivariable linear regression was performed to assess the independent effect of dexamethasone on glycemic outcomes after adjusting for relevant covariates. The accuracy of CGM was assessed using mean absolute relative difference and Bland-Altman analysis.
Results: The dexamethasone group exhibited greater median (IQR) maximum intraoperative glucose change: 3.6 (3.3-4.9) mmol/L vs. 3.1 (2.6-4.0) mmol/L; P = 0.009. Dexamethasone was also associated with higher intraoperative GV: SD (1.1 [1.0-1.4] mmol/L vs. 0.8 [0.7-1.0] mmol/L, P < 0.001), CV (21.9 [6.3] vs. 15.8 [6.1]; P < 0.001), and GLI (3.0 [1.7-4.1] mmol2/L2/h vs. 1.4 [0.9-2.4] mmol2/L2/h; P < 0.001). Multivariable analysis confirmed that dexamethasone independently predicted greater intraoperative glucose excursions and glycemic variability. Perioperative time-in-range metrics did not differ significantly between groups. CGM demonstrated acceptable accuracy in this surgical setting.
Conclusion: A single 8 mg intraoperative dose of dexamethasone increases maximum intraoperative glucose change and amplifies GV in older patients with diabetes. These findings reveal a previously uncharacterized dimension of dexamethasone-induced glycemic instability in this vulnerable population and highlight the need for glycemic monitoring strategies that capture transient fluctuations potentially missed by conventional intermittent measurements.
Clinical trial registration: www.chictr.org.cn, identifier [ChiCTR2300077167].

Keywords:  continuous glucose monitoring; dexamethasone; elderly; glycemic variability; type 2 diabetes mellitus

DOI:  https://doi.org/10.3389/fmed.2026.1880028
Front Endocrinol (Lausanne). 2026 ;17 1898511

Exploratory association of OGTT area under the curve with early-night glycemic patterns and pharmacotherapy use in gestational diabetes mellitus.

Jingxiang Feng, Shuyu Liu, Rongjie Lai, Zhaoyi Zhong, Yuzhi Chen, Weizhang Liang.

   Background: In gestational diabetes mellitus (GDM), the relationship between baseline 75-g oral glucose tolerance test (OGTT) area under the curve (AUC), subsequent continuous glucose monitoring (CGM)-derived glycemic patterns, and pharmacotherapy use remains incompletely understood. This study aimed to examine the association of OGTT AUC with 14-day CGM profiles, with particular attention to nocturnal glycemic patterns, and pharmacotherapy use under routine clinical management.
Methods: This single-center retrospective study included 64 singleton women with GDM identified from an institutional CGM registration cohort. Participants were stratified into quartiles according to baseline OGTT AUC. CGM-derived metrics were evaluated overall and across prespecified time windows. Hierarchical regression models were used to examine the associations of OGTT AUC with overall TAR and pharmacotherapy use. ROC analysis was performed as an exploratory assessment of discriminatory ability.
Results: Women in the highest OGTT AUC quartile showed less favorable CGM-derived glycemic profiles, with higher hyperglycemic exposure and greater glycemic variability, particularly during waking hours (06:00-22:00) and the early-night (22:00-02:00) period. Higher OGTT AUC was associated with greater overall TAR in linear regression models and with higher odds of pharmacotherapy use in logistic regression models. The association persisted in sensitivity models additionally adjusted for CGM-derived mean glucose, although these models were interpreted cautiously because mean glucose may lie downstream of OGTT AUC. ROC analysis yielded an AUC of 0.770, with a potential cut-off of 17.34.
Conclusions: In this exploratory CGM cohort of women with GDM, higher baseline OGTT AUC was associated with less favorable CGM-derived glycemic profiles, more apparent early-night glycemic abnormalities, and greater pharmacotherapy use under routine clinical management. OGTT AUC may help characterize subsequent glycemic burden and identify women who warrant closer glucose monitoring, but its clinical utility and candidate treatment-related thresholds require validation in larger prospective cohorts with standardized treatment-initiation criteria.

Keywords:  area under the curve; continuous glucose monitoring; gestational diabetes mellitus; glycemic variability; nocturnal glycemic patterns; oral glucose tolerance test; pharmacotherapy

DOI:  https://doi.org/10.3389/fendo.2026.1898511
Chin Med J (Engl). 2026 Sep 08.

Complexity analysis of physiological signals in the wearable era: New insights into chronic diseases and aging.

Yuan Yao, Jinghao Cai, Yaxin Wang, Jiaying Ni, Li Cao, Jingyi Lu, Jian Zhou.

   ABSTRACT: The human body is a complex and irregular system that generates diverse physiological signals. In the era of wearable technology, an increasing number of physiological signals can be continuously monitored, generating rich time series data that capture the dynamic physiological fluctuations and may reveal subtle signs of dysregulation. For example, continuous glucose monitoring (CGM) systems generate glucose time series data. As such, new metrics harnessing the time series nature of physiological signals may serve as sensitive markers of health. Of them, complexity focuses more on the dynamical characteristics of physiological signals and can reveal hidden information that linear methods may miss, allowing for the handling of nonstationary data and providing a more precise capture of individual differences. Importantly, the complexity of physiological signals may reflect the regulatory capacity, adaptability, and functional reserves of the body, which are often impaired in chronic diseases and during aging. Using CGM-derived glucose complexity as a representative example, this review discusses the clinical significance and applications of complexity in chronic diseases and aging. Finally, we outline future directions for complexity-related research, particularly regarding the roles of artificial intelligence (AI), wearable devices, and clinical translation.

Keywords:  Artificial intelligence; Complexity; Continuous glucose monitoring; Diabetes; Wearable devices

DOI:  https://doi.org/10.1097/CM9.0000000000004295
Pediatr Endocrinol Diabetes Metab. 2026 ;pii: 58170. [Epub ahead of print]32(2): 96-106

Comparison of somatic development, nutritional status, control of disease, and frequency of autoimmune comorbidities in Polish and Ukrainian children with type 1 diabetes.

Joanna Smyczyńska, Beata Mianowska, Iwona Pietrzak, Aleksandra Olejniczak, Michał Suchowiński, Kacper Kopeć, Przemysław Seliga, Urszula Smyczyńska, Agnieszka Szadkowska.

   INTRODUCTION: Te 1yp diabetes mellitus (DM1) requires lifelong insulin administration. Standards of care on children with DM1 may vary between countries. Since 2022, many war refugees from Ukraine with DM1 have continued treatment in Poland.
AIM OF THE RESEARCH: To compare Polish (PL) and Ukrainian (UA) children with DM1 with respect to methods of insulin administration, glucose monitoring, auxological development, and comorbidities, and to re-assess UA children after 1 year of stay in Poland.
MATERIAL AND METHODS: The retrospective analysis included 35 UA school-aged refugees and 70 PL children, matched with respect to sex, age, and DM1 duration.
RESULTS: Continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) were significantly more frequently used by PL children than by UA ones. Glycated hemoglobin (HbA1c) levels were lower in PL than in UA patients, in both CGM and CSII users. Patients' height standard deviation score (SDS) was significantly lower in UA than in PL children, while body mass index (BMI) SDS was significantly lower in UA patients on constant insulin doses. The incidence of overweight and obesity depended on the used centile charts (national for PL or UA children, or World Health Organization). After 1 year, more UA children used CSII and CGM, with an increase of height SDS and BMI SDS, while there was no effect on HbA1c. Vitamin D deficiency and autoimmune thyroiditis were common comorbidities.
CONCLUSIONS: Use of CSII and especially of CGM is associated with improved DM1 control and auxological development. The migration of children with DM1 was associated with modification of their treatment and challenges in proper assessment of nutritional status.

Keywords:   nutritional status; continuous glucose monitoring. ; continuous subcutaneous insulin infusion; diabetes mellitus type 1; glycated hemoglobin

DOI:  https://doi.org/10.5114/pedm.2026.162373