bims-glumda 2025-09-07 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2025–09–07
nineteen papers selected by
Mott Given

Beyond Mean Absolute Relative Difference (MARD): Rethinking Continuous Glucose Monitoring (CGM) Evaluation for Real-World Diabetes Care.
Biases in Glucose Metrics Are Directly Related to Low Coverage of Continuous Glucose Monitoring: Insights from Diverse Populations.
Intermittent Use of Continuous Glucose Monitoring: A Practical and Culturally Relevant Strategy for India's Type 2 Diabetes Epidemic.
Glucose360: An Open-Source Python Platform with Event-Based Integration for Continuous Glucose Monitoring Data Analysis.
Efficacy of intermittently scanned continuous glucose monitoring in patients with types 1 or 2 diabetes receiving insulin therapy: a systematic review and meta-analysis.
Continuous Glucose Monitoring During Recreational Diving in Type 1 Diabetes: Navigating Clinical and Technical Uncertainties.
Wearable Diabetes Technology for Hospitalized People With Diabetes and End-Stage Kidney Disease, Peripartum State, and Steroid Use.
Effects of Continuous Glucose Monitoring on Impaired Awareness of Hypoglycemia in Older Adults With Type 1 Diabetes: A Post Hoc Analysis of the WISDM Study.
Continuous Glucose Monitoring in Primary Care: A Survey of Primary Care Providers.
Comment to 'Minimum expectations for market authorization of continuous glucose monitoring devices in Europe-"eCGM"'.
Calibrating Dexcom G7 improves its performance in the context of repetitive recreational scuba diving in people with type 1 diabetes.
Prescription distribution and inequities in diabetes care: A comparative analysis of continuous glucose monitoring access by diabetes status, ethnicity and socio-economic factors in England.
Diabetes self-management observational study investigating how CGM use impacts diabetes distress, glycaemia and functions as a technological substitute for hypoglycaemia awareness: a study protocol.
Extrapolated Time in Range and Pregnancy Outcomes in Patients with Type 1 Diabetes.
Use of a Claims-Based Algorithm to Characterize Uptake of Continuous Glucose Monitoring Among Older Adults With Type 1 and Type 2 Diabetes Meeting Medicare Coverage Criteria From 2017 to 2019.
Scoping Review-Diabetes Technology for Individuals on Kidney Replacement Therapy (Dialysis): Current Trends and Future Directions.
Identifying high glucose variability using non-glycemic factors in low continuous glucose monitoring use settings.
An Infrared Non-Invasive System for Measuring Blood Glucose: A Primary Study using Serum Samples.
Use of commercially available automated insulin delivery systems in pregnant people with type 1 diabetes.

Cureus. 2025 Sep;17(9): e91427

Beyond Mean Absolute Relative Difference (MARD): Rethinking Continuous Glucose Monitoring (CGM) Evaluation for Real-World Diabetes Care.

Matteo Acanfora, Erika Pedone, Barbara Presciuttini, Francesca Ré, Luca Acanfora.

  Continuous glucose monitoring (CGM) has transformed diabetes mellitus management, evolving from a supportive monitoring tool to a central pillar of care. For people with type 1 diabetes and many insulin-treated individuals with type 2 diabetes, CGM now directly informs treatment decisions, especially when integrated with automated insulin delivery (AID) systems. In these hybrid closed-loop systems, sensor data drives real-time insulin adjustments, meaning that accuracy is not just a matter of measurement quality; it is a matter of patient safety. However, the primary accuracy measure currently used, the mean absolute relative difference (MARD), is increasingly inadequate for guiding clinical decisions. MARD offers a single averaged number under controlled conditions, but it does not capture the timing, direction, or clinical consequences of sensor errors. This is particularly problematic in AID systems, where even minor inaccuracies may lead to inappropriate insulin dosing, increasing the risk of hypoglycemia or hyperglycemia. Given the centrality of CGM in modern diabetes care, a more comprehensive evaluation approach is urgently needed, one that reflects real-world performance, prioritizes patient safety, and addresses the diverse contexts in which CGM devices are used. This editorial presents an opinion-based perspective, proposing a four-dimensional framework for CGM evaluation beyond the traditional reliance on MARD.

Keywords:  continuous glucose monitoring (cgm); endocrinology and diabetes; mard; measurement accuracy; safety study

DOI:  https://doi.org/10.7759/cureus.91427
Diabetes Technol Ther. 2025 Sep 03.

Biases in Glucose Metrics Are Directly Related to Low Coverage of Continuous Glucose Monitoring: Insights from Diverse Populations.

Simon Lebech Cichosz, Niels Væver Hartvig, Thomas Kronborg, Stine Hangaard, Peter Vestergaard, Morten Hasselstrøm Jensen.

  The aim was to investigate the association between continuous glucose monitoring (CGM) data coverage and glycemic metrics. This study included over 97,000 clinical study participants and real-world data from type 1 or type 2 diabetes treated with multiple daily insulin injections, closed-loop systems, or basal-only insulin regimens. Over 35 million days of CGM data were analyzed with multilevel modeling. Low coverage was observed in 6.4%-10.1% of days and was significantly associated with lower time in range (TIR) across sources (P < 0.001). Each 1% increase in coverage was associated with a within-person increase of 0.07%-0.13% in mean daily TIR (P < 0.001). Our analysis shows that higher daily sensor coverage is significantly associated with higher daily TIR, suggesting that missing CGM data may be missing not-at-random. Although low-coverage days are included in TIR calculations, they contribute fewer measurements and may underrepresent periods of poor glycemic control, potentially leading to a systematic overestimation and bias of overall TIR.

Keywords:  bias; continuous glucose monitoring; flash glucose monitoring; gaps; glycemic control; missing data; missing not-at-random (MNAR); time in range

DOI:  https://doi.org/10.1177/15209156251376007
Sci Diabetes Self Manag Care. 2025 Sep 02. 26350106251366655

Intermittent Use of Continuous Glucose Monitoring: A Practical and Culturally Relevant Strategy for India's Type 2 Diabetes Epidemic.

Keshavi Killi, Aparna Kuna, Dilip Kumar Kandar.

DOI: https://doi.org/10.1177/26350106251366655
Diabetes Technol Ther. 2025 Sep 03.

Glucose360: An Open-Source Python Platform with Event-Based Integration for Continuous Glucose Monitoring Data Analysis.

Ben Ehlert, Dhruv Aron, Dalia Perelman, Yue Wu, Michael P Snyder.

  Background and Aims: Continuous glucose monitoring (CGM) devices provide real-time actionable data on blood glucose levels, making them essential tools for effective glucose management. Integrating blood glucose data with food log data is crucial for understanding how dietary choices impact glucose levels. Despite their utility, many CGM applications lack integration with other external services, such as food trackers, and do not generate useful glycemic variability (GV) metrics or advanced visualizations. Existing solutions vary in functionality: some are proprietary, many require additional user programming or custom preprocessing to meet diverse research needs, and few have created solutions to connect CGM data with external services. Recent reviews highlight gaps such as insufficient postprandial analytics, absence of composite indices, and inadequate tools for nontechnical users. Methods: Glucose360 and commonly used alternative CGM applications and tools were compared by calculating GV metrics on 60 participant datasets and by contrasting their general applications for research workflows. Results: To address limitations, we developed Glucose360, featuring (1) an open-source python framework for event-based CGM data integration and analysis; (2) automated calculation of glucose metrics specific for meals and exercise events and other short-interval events; and (3) a user-friendly web application, designed for users with minimal programming experience and accessible at vurhd2.shinyapps.io/glucose360/. Discussion: Overall, Glucose360 provides a holistic analysis pipeline that is useful for both individuals and researchers to track and analyze CGM data. The source code for Glucose360 can be found at github.com/vurhd2/Glucose360.

Keywords:  Python package; continuous glucose monitoring; glucose data analysis; glucose lifestyle management; glycemic variability; open-source software

DOI:  https://doi.org/10.1177/15209156251374711
Diabetol Metab Syndr. 2025 Aug 31. 17(1): 366

Efficacy of intermittently scanned continuous glucose monitoring in patients with types 1 or 2 diabetes receiving insulin therapy: a systematic review and meta-analysis.

Mayra Souza Botelho, Julia Simões Correa Galendi, Mariana Andrades Fiorini Monteiro Novo, Vania Dos Santos Nunes-Nogueira.

   BACKGROUND: Monitoring glucose levels is crucial for managing glycemic control. Methods include self-monitored blood glucose (SMBG), continuous glucose monitoring (CGM), and intermittently scanned continuous glucose monitoring (isCGM).
OBJECTIVE: To assess the efficacy of isCGM versus SMBG in individuals with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) on insulin therapy.
METHODS: We conducted a systematic review including randomized controlled trials involving patients over 4 years old with T1DM or T2DM on multiple daily insulin regimens, comparing isCGM to SMBG. The outcomes analyzed were HbA1c (%), time below the target glucose range (TBR), patient satisfaction (DTSQ), device-related adverse events, time in range (TIR), and hypoglycemic events. Searches were performed in MEDLINE, EMBASE, and CENTRAL. Two independent reviewers screened studies, assessed the risk of bias, and extracted data. The meta-analyses employed a random-effects model, and the certainty of evidence was evaluated via the GRADE system.
RESULTS: Seventeen studies with 1,860 participants were included. The isCGM demonstrated a moderate certainty of evidence for reducing HbA1c (Mean difference [MD]: -0.25%, 95% confidence interval [95% CI]: -0.39- -0.10%; I²: 82.6% 13 studies; 1,482 patients) and enhancing patient satisfaction (MD: 4.5, 95% CI: 2.18- 6.82; I²: 92.9%; 10 studies; 1,150 patients). Meta-regression revealed that intervention duration was a significant moderator of HbA1c reduction. isCGM also favored a reduction in TBR, with an MD of -0.15% (95% CI: -0.23- -0.07%; I²: 96.7% 8 studies; 1,094 patients; low certainty). Mild device-related adverse events were more common in the isCGM group (Relative risk: 2.69, 95% CI: 1.5- 4.81; I²: 0%; 7 studies; 991 participants; moderate certainty). The overall frequency of participants who discontinued isCGM due to cutaneous adverse events was 1% (95% CI: 0-6%; 7 studies; 533 participants). No clear effects were observed for TIR (MD: 0.02%, 95% CI: -0.05- 0.1%; I²: 79.6%; 11 studies; 1,318 patients; very low certainty) or hypoglycemic episodes.
CONCLUSIONS: Compared with SMBG, isCGM reduces HbA1c, enhances patient satisfaction, and reduces TBR. However, it may increase the incidence of mild device-related adverse events. No definitive effects were observed on the TIR or hypoglycemia frequency.
PROSPERO REGISTRATION: CRD42024562805.

Keywords:  Blood glucose self-monitoring; Continuous glucose monitoring; Diabetes mellitus, type 1; Diabetes mellitus, type 2; Intermittently scanned continuous glucose monitoring

DOI:  https://doi.org/10.1186/s13098-025-01935-x
Diabetes Metab Syndr Obes. 2025 ;18 3089-3092

Continuous Glucose Monitoring During Recreational Diving in Type 1 Diabetes: Navigating Clinical and Technical Uncertainties.

Djordje S Popovic, Theocharis Koufakis, Dimitrios Patoulias, Anca Pantea Stoian, Nikolaos Papanas.

  Recreational diving with self-contained underwater breathing devices is gaining popularity worldwide as a sport and leisure activity. People living with type 1 diabetes mellitus (PLT1D) are no exception, although historically diabetes mellitus, especially insulin-treated, has been described as an absolute contra-indication for diving. However, based on observational data collected by the Divers Alert Network, the presence of background diabetes mellitus became only a relative contraindication for those without significant co-morbidities or long-term complications. Regarding diving activities among PLT1D, the primary concern is the risk of hypoglycaemia, especially in those with impaired awareness. Furthermore, symptoms consistent with hypoglycaemia could be confused with those originating from other factors related to diving. Although avoidance of hypoglycaemia is imperative among PLT1D practicing diving, the risk of severe hyperglycaemia should also be minimised. Continuous glucose monitoring (CGM) nowadays represents the standard of care for PLT1D, but its accuracy during diving activities is still a matter of debate. This commentary aims to summarize the existing data on accuracy, durability, and underwater performance of different CGM devices among PLT1D who engage in diving, and to call for additional research in the field. Based on available results, the application of real-time CGM still requires extreme caution since none of the existing systems has so far met the standards for accurate use in underwater conditions. Further improvements of contemporary CGM devices, validated through large-scale trials, are necessary before their widespread implementation among PLT1D practicing diving. Such advances should further enhance safety during this popular activity.

Keywords:  continuous glucose monitoring; diving; type 1 diabetes mellitus

DOI:  https://doi.org/10.2147/DMSO.S538152
J Diabetes Sci Technol. 2025 Sep 03. 19322968251364276

Wearable Diabetes Technology for Hospitalized People With Diabetes and End-Stage Kidney Disease, Peripartum State, and Steroid Use.

Shubham Agarwal, Andrew P Demidowich, Diana Soliman, Guillermo E Umpierrez, Rodolfo J Galindo.

  Inpatient hyperglycemia remains a challenge, as conventional insulin regimens often lead to both hyperglycemia and hypoglycemia. Traditional glucose monitoring methods, such as point-of-care testing, fail to detect diurnal and nocturnal glycemic fluctuations, contributing to suboptimal control. This review examines the effectiveness of continuous glucose monitoring (CGM) and automated insulin delivery (AID) systems in managing diabetes in hospitalized patients, including those with additional challenges such as end-stage kidney disease (ESKD), pregnancy, and steroid use. In patients with ESKD, CGM has demonstrated reliable glucose measurements and improved glycemic control, particularly in those undergoing hemodialysis. It has been shown to increase time in range (TIR) and reduce hypoglycemia, with clinical accuracy verified in multiple studies. Existing evidence shows that AID systems may offer improved outcomes in this population, with increased TIR and reduced glycemic variability compared with conventional insulin therapy. Continuous glucose monitor use has been beneficial for maternal glycemic control in pregnancy, leading to lower HbA1c levels, increased TIR, reduced maternal hypoglycemia, reduced neonatal hypoglycemia, and admissions to intensive care. Limited studies have evaluated AID system use during labor. In addition, CGM helps identify postprandial hyperglycemia in patients with glucocorticoid-induced hyperglycemia, which is crucial for managing glucose fluctuations. Studies in patients receiving glucocorticoids have shown that continuous glucose monitoring improves glycemic control without significantly increasing hypoglycemic events. In conclusion, limited studies have shown the role of CGM and AID systems and their effects on glycemic outcomes in hospitalized patients with diabetes, particularly those with ESKD, in pregnancy, and those receiving glucocorticoids. These technologies used for glucose monitoring and insulin delivery could offer an alternative method of diabetes management in certain inpatient populations.

Keywords:  automated insulin delivery; continuous glucose monitor; corticosteroid; end-stage kidney disease; peripartum

DOI:  https://doi.org/10.1177/19322968251364276
Diabetes Care. 2025 Sep 03. pii: dc250971. [Epub ahead of print]

Effects of Continuous Glucose Monitoring on Impaired Awareness of Hypoglycemia in Older Adults With Type 1 Diabetes: A Post Hoc Analysis of the WISDM Study.

Anika Bilal, Fanchao Yi, Keri Whitaker, Zahra A Khan, Richard E Pratley, Anna Casu.

OBJECTIVE: Although continuous glucose monitoring (CGM) reduces hypoglycemia and may improve impaired awareness of hypoglycemia (IAH), its effectiveness in older adults at high risk remains unknown.
RESEARCH DESIGN AND METHODS: This post hoc analysis of the WISDM study focuses on CGM use over 52 weeks. IAH was assessed using the Clarke original score (Clarke-full) and its subscales, Hypoglycemia Awareness Factor (HAF) and Severe Hypoglycemia Experienced Factors (SHEF), at baseline, 26 weeks, and 52 weeks.
RESULTS: After 26 (n = 184) and 52 weeks (n = 94) of CGM use, Clarke-SHEF decreased significantly (P = 0.02 and P < 0.0001, respectively), whereas Clarke-full and Clarke-HAF remained unchanged. After 52 weeks, Clarke-full but not Clarke-HAF improved in the IAH subgroup, highlighting the importance of selecting the appropriate scoring method for IAH.
CONCLUSIONS: In older adults with type 1 diabetes, CGM improves hypoglycemia; however, its role in improving IAH is variable, depending on the scoring method. This study highlights the limitations of the Clarke score.

DOI: https://doi.org/10.2337/dc25-0971
J Gen Intern Med. 2025 Sep 02.

Continuous Glucose Monitoring in Primary Care: A Survey of Primary Care Providers.

Kailyn E Sitter, Ben Kragen, Alison J Leibowitz, Jolie B Wormwood, Bo Kim, Varsha G Vimalananda.



Keywords:  blood glucose monitoring; continuous glucose monitoring; glycemic control; primary care; survey; type 2 diabetes; wearable electronic devices

DOI:  https://doi.org/10.1007/s11606-025-09741-x
Diabetes Obes Metab. 2025 Sep 01.

Comment to 'Minimum expectations for market authorization of continuous glucose monitoring devices in Europe-"eCGM"'.

Ohad Cohen, Tim van den Heuvel, George Mallas, John Shin, Simona de Portu.

DOI: https://doi.org/10.1111/dom.70072
BMJ Open Sport Exerc Med. 2025 ;11(3): e002809

Calibrating Dexcom G7 improves its performance in the context of repetitive recreational scuba diving in people with type 1 diabetes.

Elena Gamarra, Giovanni Careddu, Andrea Fazi, Valentina Turra, Ambra Morelli, Pierpaolo Trimboli.

   Background: The use of continuous glucose monitors (CGM) in scuba diving for patients with type 1 diabetes (T1DM) shows potential but faces challenges related to accuracy. Previous research has highlighted the poor accuracy of the Dexcom G7 (DG7) in repetitive diving contexts. This study investigates the impact of calibration on the accuracy of DG7, providing valuable insights for patients and clinicians.
Materials and methods: In August 2024, 'Diabete Sommerso' organised a 4-day diving cruise around Elba Island (Italy) with 15 participants, including individuals with T1DM. Each participant with diabetes wore two DG7 sensors (one on the arm and one on the abdomen), calibrated daily and compared the results to capillary glucose (Beurer GL50Evo as the reference). Accuracy was assessed using mean absolute relative difference (MARD)/median ARD, Food and Drug Administration (FDA) integrated continuous glucose monitoring (iCGM) criteria and Surveillance Error Grid (SEG) analysis. Hypoglycaemia detection and trends were also evaluated.
Results: Eight participants with T1DM completed the study using 16 DG7 sensors with no detachments or skin reactions. Analysis of 765 sensor-capillary glucose pairs during 68 dives showed an overall MARD of 13.7%, with arm sensors (11% MARD) outperforming abdomen sensors (16%, p=0.0001). SEG analysis revealed that more than 97% of readings fell within the no-risk zone; however, the FDA's iCGM criteria for non-adjunctive use were not met.
Conclusions: Calibration improved the accuracy of DG7 in repetitive diving for patients with T1DM. However, capillary glucose checks remain essential, as non-adjunctive criteria were not met.

Keywords:  Diabetes; Glucose; Hyperbaric Medicine

DOI:  https://doi.org/10.1136/bmjsem-2025-002809
Diabet Med. 2025 Sep 03. e70130

Prescription distribution and inequities in diabetes care: A comparative analysis of continuous glucose monitoring access by diabetes status, ethnicity and socio-economic factors in England.

Samuel Seidu, John Tetteh, Setor Kunutsor, Pratik Choudhary, Kamlesh Khunti, Ramzi A Ajjan.

   BACKGROUND: Diabetes affects over 3.3 million people in England, creating a significant health and economic burden. Continuous glucose monitoring (CGM) improves diabetes management but remains unevenly accessible, especially among Black and minority groups who face onset at younger ages, higher diabetes rates and complications. Updated NICE guidelines promote CGM access for all people with T1D and certain people with T2D, yet data on prescribing patterns in England are limited. This study investigates CGM prescribing across integrated care boards (ICBs) and primary care networks (PCNs), focusing on ethnicity and deprivation, to identify and address access disparities.
METHODS: Cross-sectional analysis of publicly available data examined CGM prescribing patterns across England's PCNs, focusing on ethnicity and socio-economic factors. Data from OpenPrescribing, the National Diabetes Audit and Public Health England were analysed through descriptive and inferential statistics, including regression and Intraclass Correlation Coefficient (ICC) calculations, to assess disparities in prescribing ratio per 1000 people.
RESULTS: Significant disparities in CGM prescribing across PCNs and ICBs are identified, shaped by ethnicity, age and socio-economic factors. The mean items prescription ratio is 4.87 per 1000 people, ranging from 0.26 to 11.59. People with T1D are generally younger, with only 15.5% over 65, compared to 52.0% in T2D. White individuals represent 83.6% of T1D cases, while South Asians and Afro-Caribbeans are more prevalent in T2D (14.5% and 5.3%, respectively). ICBs with below-average CGM prescribing have a higher percentage of Afro-Caribbean and South Asian populations compared to ICBs with above-average prescribing. For T1D, Afro-Caribbean representation is 6.7 (SD:7.0) in lower-prescribing ICBs versus 2.1 (SD:2.8) in higher-prescribing ICBs, and for T2D, it is 8.4 (10.4) versus 1.8 (SD:3.4) South Asian representation in low-prescribing ICBs is 10.6 (SD:13.7) for T1D and 21.9 (SD:20.5) for T2D, compared to 3.2 (SD:4.9) for T1D and 6.5 (SD:9.7) for T2D in higher-prescribing ICBs. CGM prescribing variance attributed to ethnicity and deprivation is 46.6% in T1D and 77.3% in T2D, indicating considerable socio-demographic impact.
CONCLUSION: This study reveals significant ethnic disparities in CGM access, with Afro-Caribbean and South Asian groups facing a reduced prescribing ratio per 1000 people. Consistent NICE guideline adoption and targeted outreach are needed to improve equity in CGM access.

Keywords:  continuous glucose monitoring; diabetes disparities; ethnicity; healthcare inequity

DOI:  https://doi.org/10.1111/dme.70130
BMJ Open. 2025 Sep 02. 15(9): e103469

Diabetes self-management observational study investigating how CGM use impacts diabetes distress, glycaemia and functions as a technological substitute for hypoglycaemia awareness: a study protocol.

Mette Juul Nitschke, Ceren Demir, Julie Maria Bøggild Brøsen, Ingrid Willaing Tapager, Kirsten Nørgaard, Peter Lommer Kristensen, Ulrik Pedersen-Bjergaard.

   INTRODUCTION: Continuous glucose monitoring (CGM) provides real-time glucose data for people with diabetes. However, detailed knowledge of its use in daily life remains limited. We aim to investigate the interaction between people with type 1 diabetes (T1D) and their CGM data and the impact of the interaction on glycaemia and diabetes distress.
METHODS AND ANALYSIS: This is a two-centre observational study of adults (n=500) with T1D using FreeStyle Libre 2. Over a period of 14 days, participants will continue their regular CGM use, record insulin doses and timing with smart insulin pens, track activity and sleep with an activity tracker, log all food intake in the LibreLink app and answer questions about quality of life and hypoglycaemia two times per day. Before the study period, the participants will complete a survey of 11 validated questionnaires assessing diabetes distress, hypoglycaemia awareness and other patient-reported outcomes (PROs). After the study period, the participants will complete two additional questionnaires assessing diabetes distress and health literacy.The collected data will be used in two substudies with the overall aims of:Substudy 1: to investigate how CGM is used in practice and the impact of the interaction on diabetes distress and glycaemia.Substudy 2: to investigate whether and how CGM functions as a technological substitute for impaired awareness of hypoglycaemia, focusing on alarm data.Endpoints will include CGM metrics, alarm data and PROs.
ETHICS AND DISSEMINATION: The Danish Data Protection Agency approved the study (P-2024-15985), and the regional committee on health research ethics has granted an ethical waiver (H-24014662). All participants have signed written informed consent forms before participating. The results will be published in an international peer-reviewed scientific journal by the study investigators and shared via www.
CLINICALTRIALS: gov. Participants who agreed to receive information about the study will be sent the results after publication.
TRIAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT06453434).

Keywords:  Diabetes & endocrinology; Digital Technology; Patient Reported Outcome Measures; Self-Management

DOI:  https://doi.org/10.1136/bmjopen-2025-103469
Diabetes Technol Ther. 2025 Sep 05.

Extrapolated Time in Range and Pregnancy Outcomes in Patients with Type 1 Diabetes.

Enio A M Santos, Tatiana A Zaccara, Cristiane F Paganoti, Rossana P V Francisco, Rafaela A Costa.

  Aims: To assess the relationship between time in range (TIR), extrapolated from self-monitoring of blood glucose (SMBG) measures, and adverse perinatal outcomes in pregnant women with type 1 diabetes (T1D). Methods: A retrospective cohort study was conducted, including singleton pregnancies that began antenatal care before 20 weeks of gestation and delivered live newborns without malformations between 2010 and 2019. Glycemic data from SMBG were categorized into TIR (63-140 mg/dL or 3.5-7.8 mmol/L), based on guidelines for real-time continuous glucose monitoring. Extrapolated TIR (eTIR) was defined as the proportion of time spent within the target range and categorized into three intervals: eTIR <50%, eTIR 50%-70%, and eTIR >70%. Clinical characteristics and obstetric outcomes were compared across these intervals. Multivariate logistic regression was used to evaluate the prediction of adverse outcomes, including preeclampsia, nephropathy, cesarean section, preterm birth, macrosomia, large for gestational age (LGA), small for gestational age (SGA), 5-minute Apgar score <7, shoulder dystocia, neonatal respiratory distress, neonatal hypoglycemia, and neonatal intensive care unit (NICU) admission. Results: Data from 140 pregnancies were analyzed. Of these, 20% had eTIR <50%, 53.6% had eTIR 50%-70%, and 26.4% had eTIR >70%. Women with eTIR 50%-70% and eTIR >70% were less likely to experience preterm birth (OR: 0.271; 95% CI: 0.094-0.786 and OR: 0.219; 95% CI: 0.058-0.826), neonatal respiratory distress (OR: 0.341; 95% CI: 0.124-0.936 and OR: 0.122; 95% CI: 0.029-0.516), and LGA infants (OR: 0.246; 95% CI: 0.084-0.719 and OR: 0.115; 95% CI: 0.028-0.469) compared with women with eTIR <50%. Conclusions: Higher eTIR values were associated with a reduced risk of preterm birth, neonatal respiratory distress, and LGA infants. For pregnant women with T1D, achieving an eTIR above 50% was sufficient to decrease the risk of these adverse outcomes, highlighting the importance of glucose control even in challenging circumstances.

Keywords:  adverse maternofetal outcomes; pregnancy; self-monitoring of blood glucose; time in range; type 1 diabetes

DOI:  https://doi.org/10.1177/15209156251374706
Diabetes Care. 2025 Sep 03. pii: dc251593. [Epub ahead of print]

Use of a Claims-Based Algorithm to Characterize Uptake of Continuous Glucose Monitoring Among Older Adults With Type 1 and Type 2 Diabetes Meeting Medicare Coverage Criteria From 2017 to 2019.

Anna R Kahkoska, Virginia Pate, Richard E Pratley, Michele Jonsson-Funk, Til Stürmer.

DOI: https://doi.org/10.2337/dc25-1593
J Diabetes Sci Technol. 2025 Sep 02. 19322968251353811

Scoping Review-Diabetes Technology for Individuals on Kidney Replacement Therapy (Dialysis): Current Trends and Future Directions.

Hellena Hailu Habte-Asres, Joseph Ngmenesegre Suglo, Khuram Chaudhry, Angus Forbes, David C Wheeler, Janaka Karalliedde.

   AIM: This review aims to map the existing literature on the use of diabetes technology in people receiving dialysis, with a focus on utilization, accuracy, and effectiveness.
METHODS: A scoping review was conducted using the Joanna Briggs Institute methodology, with systematic searches of Medline, Embase, and CINAHL for studies on diabetes technologies in dialysis populations.
RESULTS: The search identified 1060 continuous glucose monitoring (CGM) and 1467 continuous subcutaneous insulin infusion or automated insulin delivery (CSII/AID) records, with 64 studies included. Eighteen studies assessed CGM accuracy, reporting mean absolute relative difference (MARD) values ranging from 8.1% to 29%, with over 97% of readings falling within Clarke error grid zones A or B. Thirteen studies compared glycemic markers, finding that HbA1c underestimated glucose by 7.3 mmol/mol, while glycated albumin showed a stronger correlation (r = 0.508). Four studies reported on dialysis effects, showing that people on automated peritoneal dialysis (APD) had lower mean glucose levels (181 ± 64 mg/dL) compared to continuous ambulatory peritoneal dialysis (CAPD) (238 ± 67 mg/dL; P < .05). Eleven studies evaluating diabetes treatment efficacy using CGM found that dulaglutide significantly reduced glucose CV from 28.1% to 19.8% (P = .003). Twenty-two studies examining glycemic outcomes reported that TIR was lower on dialysis days (80.2%, P = .02). Finally, four AID studies reported TIR improvements of up to 37.6% and a 1.5 mmol/L reduction in glucose (P = .003).
CONCLUSION: This review highlights the potential of CGM and AID to improve diabetes outcomes in people on dialysis. While their clinical utility is evident, broader access and further research are needed to optimize their use in this high-risk population.

Keywords:  AID; CGM; CSII; continuous glucose monitoring; diabetes; diabetes technology; dialysis; glycemic control; hemodialysis; insulin pump therapy; peritoneal dialysis; scoping review

DOI:  https://doi.org/10.1177/19322968251353811
Prim Care Diabetes. 2025 Aug 28. pii: S1751-9918(25)00182-2. [Epub ahead of print]

Identifying high glucose variability using non-glycemic factors in low continuous glucose monitoring use settings.

Suresh Rama Chandran, Ming Ming Teh, Hong Chang Tan, May Zin Oo, Alcey Ang Li Chang, Daphne Gardner.

   AIMS: Identifying non-glycemic factors associated with high Glucose variability (GV).
METHODS: A cross-sectional observational study recruited people with type 2 diabetes, who wore a Freestyle Libre Pro CGM.
INDEPENDENT VARIABLES: Age, sex, BMI, diabetes medication, diabetes duration, HbA1c and estimated glomerular filtration rate (eGFR). CGM-derived variables calculated included Time-in-Range (TIR, 70-180 mg/dl), below-range 1 (TBR1, <70 mg/dl), -below-range 2 (TBR2, <54 mg/dl) and -above-range (TAR, >180 mg/dl), coefficient of variation (%CV). A logistic regression model examined independent variables associated with high GV (CV ≥36 %). All analysis was done on R version 4.3.1 RESULTS: T2D cohort (n = 403), 46 % women, had median age of 61 y, BMI of 26.5 kg/m2, diabetes duration 14 y, HbA1c 7.8 %(62 mmol/mol) and creatinine of 75 µmol/L. Using sulphonylurea, premixed or basal-bolus insulin had an odds ratio (OR) of 4.7 - 5.2 for CV ≥ 36 %. Longer diabetes duration [OR 1.2], and lower eGFR [OR 1.2] were associated with higher odds and older age [OR 0.8]and higher BMI [0.8] were associated with lower odds of CV≥ 36 %. Sex and HbA1c had no association with high GV.
CONCLUSION: Nonglycemic-factors like medication type, diabetes duration and eGFR can aid in identification of high GV even in low-CGM use settings.

Keywords:  Coefficient of variation; Diabetes medication; Glucose variability; Time-in-range; Type 2 diabetes

DOI:  https://doi.org/10.1016/j.pcd.2025.08.008
J Biomed Phys Eng. 2025 Aug;15(4): 385-392

An Infrared Non-Invasive System for Measuring Blood Glucose: A Primary Study using Serum Samples.

Ramin Jokari, Zahra Mahyari, Mohammad Javad Moulodi, Seyyed Mohammad Fatemi Ghiri, Hadi Tajalizadeh, Ali Loloee Jahromi, Alireza Nakhostin, Gholamreza Abdollahifard, Hossein Parsaei.

   Background: Diabetes is a global concern, with an estimated 2 million individuals expected to be affected by the condition by 2024. Non-invasive glucose monitoring devices can greatly enhance patient care and management.
Objective: This study aimed to develop an instrument capable of non-invasively measuring blood glucose levels using an infrared transmitter and receiver, with data processing performed by a dedicated processor.
Material and Methods: This analytical study develops a glucometer that incorporates a power supply, a light source, a light detector, a sampler, and signal processing components to enable non-invasive glucose measurements. The instrument was calibrated using sugar solution samples with known glucose concentrations. It was then tested using serum samples from diabetic patients with accuracy, which was evaluated using Clarke's grid analysis.
Results: Testing of the designed glucometer revealed that 83% of the serum samples fell within zone A of Clarke's grid analysis, indicating high accuracy. The remaining 17% of samples were classified in zone B, with no samples falling in zones C, D, or E.
Conclusion: The developed glucometer demonstrated higher accuracy in measuring glucose concentrations above 200 mg/dl. Despite the use of serum samples in this experiment, 83% of the results were located in zone A leads to the capability of non-invasively measuring blood glucose levels. Further studies are required to validate the device's accuracy in a larger population and assess its utility in clinical practice.

Keywords:   Blood Glucose; Blood Glucose Self-Monitoring; Continuous Glucose Monitoring; Diabetes; Glucometer; Non-Invasive Blood Glucose Measurement

DOI:  https://doi.org/10.31661/jbpe.v0i0.2305-1618
Diabetes Res Clin Pract. 2025 Sep 01. pii: S0168-8227(25)00468-1. [Epub ahead of print] 112454

Use of commercially available automated insulin delivery systems in pregnant people with type 1 diabetes.

Angela Q Pham, Ildiko Lingvay, Nicole Ahmadi, Patricia C Santiago-Munoz, Marconi Abreu.

   AIMS: Automated insulin delivery (AID) systems are first-line therapy for type 1 diabetes, but commercially available AIDs in the United States are not approved for pregnancy. We aimed to compare glycemic control achieved during pregnancy by people with type 1 diabetes using AIDs versus standard of care therapy (multiple daily injections and sensor augmented pump therapy).
METHODS: This was a retrospective cohort study of people with type 1 diabetes who used a continuous glucose monitor (CGM) during pregnancy. The primary outcome was time in range (TIR); time below range (TBR), time above range, and glucose standard deviation were secondary outcomes. Outcomes were compared using analysis of covariance.
RESULTS: 38 people were included: 21 treated with AIDs and 17 with standard of care. The mean antenatal TIR in the AID group was 68.5 ± 12.9 % compared to 55.7 ± 16.7 % (adjusted mean difference 7.9 %, 95 % CI: 0.8 to 15.0, p = 0.03). The AID group achieved a lower TBR (1.7 ± 1.3 % vs 3.0 ± 2.8 %, p = 0.03), and lower glucose standard deviation (37.2 ± 8.0 vs 45.5 ± 8.9, p = 0.02) than standard of care.
CONCLUSIONS: In this real-world study, off-label AID use during pregnancy improved TIR while decreasing TBR. While awaiting commercially available AIDs with pregnancy algorithms, standardized approaches to optimizing current systems are needed.

Keywords:  Automated insulin delivery; Omnipod 5; Pregnancy; Tandem Control-IQ; Time in range; Type 1 diabetes

DOI:  https://doi.org/10.1016/j.diabres.2025.112454