bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2026–04–26
twenty-two papers selected by
Mott Given
  1. Continuous Glucose Monitoring in Adults With Diabetes Receiving Haemodialysis: Identifying Dialysis-Specific Glycaemic Patterns and Associations With Volume Status and Intradialytic Hypoglycaemia.
  2. The current role and clinical impact of continuous glucose monitoring on Canadian people living with type 2 diabetes.
  3. Time in range achieved with continuous glucose monitoring in pregnant patients with type 2 diabetes and barriers to achieving high time in range.
  4. Navigating Continuous Glucose Monitoring Adoption: Insights From Hispanic Adults With Insulin-Treated Type 2 Diabetes.
  5. Impact of Medicaid Continuous Glucose Monitor Expansion on Uptake, Glycemic Outcomes, and Engagement Among Adults With Type 2 Diabetes in a Federally Qualified Health Center.
  6. Association between Continuous Glucose Monitoring and Risk of Acute Diabetes-Related Complications in Pediatric Type 1 Diabetes Mellitus: A Nationwide Cohort Study.
  7. Time delays between fingerstick glucose measurements and correctional insulin administration in the hospital: do they really matter?
  8. Comment on Valent et al. Real-Time Continuous Glucose Monitoring in Pregnancies With Gestational Diabetes Mellitus: A Randomized Controlled Trial. Diabetes Care 2025;48:1581-1588.
  9. Updated glucose management indicator (GMI) better aligns with HbA1c than current GMI: implications for clinical practice and reporting.
  10. Pharmacy Student Confidence and Practice Readiness After Diabetes Educational Module With CGM Use.
  11. A Pre-Post Assessment of Blood Glucose Control Following Pharmacist-Led Professional Continuous Glucose Monitoring in Rhode Island Primary Care Practices.
  12. Response to Comment on Valent et al. Real-Time Continuous Glucose Monitoring in Pregnancies With Gestational Diabetes Mellitus: A Randomized Controlled Trial. Diabetes Care 2025;48:1581-1588.
  13. The role of continuous glucose monitoring for diagnosis of gestational diabetes: exploring the potential.
  14. Continuous glucose monitoring for cystic fibrosis-related diabetes: impact on quality of life and glycaemic control.
  15. Turning sensors into predictors: The power of slope to anticipate hyper-and hypoglycemia.
  16. Continuous glucose monitoring (CGM): Assessment and impact on glycemic control in children and adolescents with type 1 diabetes in Cameroon: A pilot study.
  17. Agreement Between HbA1c and Continuous Glucose Monitoring-Derived Glycemic Metrics in Adults with Cystic Fibrosis Related Diabetes.
  18. Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.
  19. The Lived Experiences of Adult Continuous Glucose Monitor Users with Type 1 Diabetes with Recurrent Severe Hypoglycemic Events and Impaired Awareness of Hypoglycemia: A Qualitative Study.
  20. Correlations Among Glycemia and Glucose Variability, Thyroid Hormones, and Albuminuria in Patients With Type 2 Diabetes Mellitus.
  21. Technology in Diabetes: A Year in Review.
  22. Technology-Enhanced Exercise Training for Cardiometabolic Syndrome: A Scoping Review.
  1. Diabetes Obes Metab. 2026 Apr 24.
    Continuous Glucose Monitoring in Adults With Diabetes Receiving Haemodialysis: Identifying Dialysis-Specific Glycaemic Patterns and Associations With Volume Status and Intradialytic Hypoglycaemia.
    Alexandros L Liarakos, Ashveer Randhay, Lalantha Leelarathna, Thomas S J Crabtree, Brett Doleman, Mohamed Tarek Eldehni, Nicholas M Selby, Maarten W Taal, Iskandar Idris, Emma G Wilmot.
       AIMS: To characterise continuous glucose monitoring (CGM)-derived glycaemic patterns across the dialysis cycle and to assess associations between CGM metrics, interdialytic weight gain (IDWG) as a marker of volume status, and intradialytic adverse events.
    MATERIALS AND METHODS: In this prospective observational study, adults with insulin-treated diabetes receiving maintenance haemodialysis underwent 2-week CGM assessment. CGM metrics were summarised for pre-dialytic, intradialytic and post-dialytic periods. Multivariable regression assessed associations between CGM metrics, HbA1c, IDWG, intradialytic hypoglycaemia and intradialytic hypotension (IDH).
    RESULTS: In total, 40 participants (age 56.6 ± 14.7 years, 60% type 2 diabetes, diabetes duration 24.5 ± 9.9 years, HbA1c 68 ± 19 mmol/mol [8.4% ± 1.7%]) contributed 11 096 CGM glucose readings and 246 haemodialysis sessions. Time in range (TIR, 3.9-10.0 mmol/L) increased from pre-dialytic to intradialytic period (36.1% vs. 60.9%, p < 0.001) and decreased post-dialysis to 17.8% (p < 0.001). Mean glucose reduced during dialysis by 32% (from 11.1 ± 3.5 mmol/L at initiation to an intradialytic nadir of 7.6 ± 2.2 mmol/L at 125 min). Lower baseline 14-day TIR, but not HbA1c or glucose level at dialysis initiation, was independently associated with higher IDWG, which was an independent risk factor for recurrent IDH. Intradialytic hypoglycaemia (20.0% of participants) was associated with higher baseline 14-day time below range (< 3.9 mmol/L) (OR 2.42 per 1% increase, p = 0.049).
    CONCLUSION: CGM identifies dialysis-specific glycaemic patterns and clinically relevant associations with IDWG and intradialytic hypoglycaemia that extend beyond HbA1c. These findings support broader evaluation of CGM in haemodialysis populations with diabetes to inform future CGM-guided strategies.
    Keywords:  continuous glucose monitoring; diabetes; diabetes technologies; dialysis; haemodialysis
    DOI:  https://doi.org/10.1111/dom.70808
  2. Can J Diabetes. 2026 Apr 16. pii: S1499-2671(26)00071-7. [Epub ahead of print]
    The current role and clinical impact of continuous glucose monitoring on Canadian people living with type 2 diabetes.
    Jeremy Gilbert, Sonja M Reichert, Tammy Cadieux, Peter Senior.
       OBJECTIVE: To present a summary of recent evidence describing the clinical and economic impact of continuous glucose monitoring (CGM) in the care of people living with type 2 diabetes mellitus (T2DM).
    QUALITY OF EVIDENCE: Outcomes of CGM use in T2DM was searched using PubMed and Google Scholar, using specific inclusion and exclusion criteria to select evidence. Preference was given to randomized controlled trials, real-world observational studies and meta-analyses. Guidelines, consensus statements and systematic reviews were also considered.
    MAIN MESSAGE: An overall favorable trend was seen in support of people living with T2DM using CGM in addition to their regular therapies. CGM improves glycemic outcomes with a significant difference in change from baseline for hemoglobin A1c (A1c), time in range (TIR), time above range (TAR), time below range (TBR), and glycemic variability-all when compared to traditional self blood glucose monitoring. Patient satisfaction favored CGM use, with overall cost-efficiency improved as well. The Canadian healthcare system may benefit from CGM use with decreased hospitalizations and related costs.
    CONCLUSION: The value of integrating CGM to enhance the care for Canadians living with T2DM as a component of comprehensive care should be recognized. Structural barriers, including provincial inequalities in coverage for devices and access to care currently pose a barrier for many in this population.
    Keywords:  basal insulin; continuous glucose monitoring device; multiple daily injections of insulin; non-insulin therapy; type 2 diabetes mellitus
    DOI:  https://doi.org/10.1016/j.jcjd.2026.04.007
  3. Am J Obstet Gynecol MFM. 2026 Apr;pii: S2589-9333(25)00253-8. [Epub ahead of print]8(4): 101856
    Time in range achieved with continuous glucose monitoring in pregnant patients with type 2 diabetes and barriers to achieving high time in range.
    Annkay Alexander, Amber Sanders, Claire McIlwraith, Brian Brocato, Ashley Battarbee.
      
    DOI:  https://doi.org/10.1016/j.ajogmf.2025.101856
  4. J Diabetes Res. 2026 ;2026(1): e7474846
    Navigating Continuous Glucose Monitoring Adoption: Insights From Hispanic Adults With Insulin-Treated Type 2 Diabetes.
    Diana Soliman, Giuliana Arevalo, Rodolfo J Galindo, Benjamin Churba, Keilecia G Malden, Daniel E Jimenez, Francisco J Pasquel, David A Baidal, Ashby F Walker.
       OBJECTIVE: Hispanic individuals are disproportionately affected by type 2 diabetes (T2D) and face access limitations in diabetes technology utilization. Despite proven benefits, continuous glucose monitoring (CGM) use remains low among Hispanic adults with insulin-treated T2D. This study used a social-ecological model (SEM) framework to identify societal/policy, interpersonal/community, and individual level barriers to CGM access and adoption within this population.
    METHODS: Two focus groups were conducted in Spanish at the University of Miami (UM) with Hispanic adults (n = 16) with T2D. Inclusion criteria were age ≥18 years, HbA1c ≥8%, ≥1 daily insulin injection, and no CGM use in the past 2 years. The initial focus group was conducted to identify barriers to CGM initiation. At the end of the focus group, participants were provided with real-time CGMs for 30 days of use. After completing the wear period, the same participants returned for a follow-up focus group to explore factors related to CGM adoption and acceptance. Focus groups were analyzed using a thematic analysis, systematically coding and categorizing key concepts and ideas expressed by participants.
    RESULTS: The mean age was 59.68 ± 13.37 years, and baseline HbA1c was 9.78 ± 1.14. Key barriers included high device costs, limited insurance coverage, alarm fatigue, and lack of culturally concordant provider guidance. Facilitators for CGM use included manufacturer discounts, peer modeling, and the desire to avoid fingersticks. After a 30-day CGM trial, most participants reported improved dietary awareness, glycemic control, and a strong desire for continued use.
    CONCLUSION: This pilot study provides novel insights into the experiences of the Hispanic population and highlights the complex interplay of societal, interpersonal, and individual-level factors influencing CGM use. Tailored interventions addressing these barriers are crucial for improving CGM utilization in this population.
    Keywords:  continuous glucose monitoring (CGM); hispanic adults; social–ecological model; type 2 diabetes mellitus (T2DM)
    DOI:  https://doi.org/10.1155/jdr/7474846
  5. J Prim Care Community Health. 2026 Jan-Dec;17:17 21501319261433345
    Impact of Medicaid Continuous Glucose Monitor Expansion on Uptake, Glycemic Outcomes, and Engagement Among Adults With Type 2 Diabetes in a Federally Qualified Health Center.
    Walter Solorzano, Ligaya Docena Scarlett, Giuliana Perini Villanueva, Kathyana Santiago Mangual, Cynthia Santana, Bryan Escobar, Angelique Rubio, Nicholas J Jackson, Marielle Tavares, Joseph Borrell, Beatrice Brumley, Tannaz Moin, Estelle Everett.
       BACKGROUND: Continuous glucose monitors (CGMs) improve outcomes for adults with type 2 diabetes yet use remains low in underserved populations. California's 2022 Medicaid coverage expansion aimed to reduce access barriers, but its impact in safety-net settings is not well understood.
    METHODS: We conducted a retrospective cohort study of adults with type 2 diabetes receiving care at a federally qualified health center from January 2022 to June 2023. Electronic health records assessed CGM uptake and glycemic outcomes. Telephone surveys (November 2023-February 2025) evaluated patient perceptions and engagement. Time-to-event models estimated the association between CGM initiation and achieving a ≥1% hemoglobin A1c (HbA1c) reduction. Open-ended responses were analyzed thematically.
    RESULTS: Among 256 adults, 126 (49%) initiated CGM use, with uptake increasing after Medicaid expansion. In the analytic sample (n = 230), CGM new users were associated with a higher but not statistically significant hazard of achieving a ≥1% HbA1c reduction (adjusted HR = 1.31; 95% CI: 0.87-1.97). Among survey respondents (n = 82), commonly cited benefits included improved glucose management and convenience, while engagement varied across behaviors.
    CONCLUSIONS: Medicaid coverage expansion increased CGM use in a safety-net population. High acceptability alongside variable engagement highlights the need for targeted implementation strategies to translate expanded access into equitable clinical benefit.
    Keywords:  Medicaid policy; continuous glucose monitoring; federally qualified health centers; health equity; safety-net healthcare; type 2 diabetes
    DOI:  https://doi.org/10.1177/21501319261433345
  6. Diabetes Metab J. 2026 Apr 22.
    Association between Continuous Glucose Monitoring and Risk of Acute Diabetes-Related Complications in Pediatric Type 1 Diabetes Mellitus: A Nationwide Cohort Study.
    Ji Yoon Kim, Seohyun Kim, Jae Hyeon Kim.
       Background: Evidence supporting the benefits of continuous glucose monitoring (CGM) in reducing diabetes-related complications remains scarce. This study aimed to investigate the association between CGM and diabetes-related complications, specifically diabetic ketoacidosis (DKA) and severe hypoglycemia in children and adolescents with type 1 diabetes mellitus (T1DM).
    Methods: From the Korean Nationwide Cohort (2016-2022), we included children and adolescents (aged <19 years) with T1DM who received rapid-acting insulin between 2019 and 2022. The primary outcomes were DKA and severe hypoglycemia. Adjusted hazard ratios (HRs) for the primary outcomes were compared between CGM users and non-users using Cox proportional hazards regression models. Additionally, among the CGM users, the frequencies of DKA and severe hypoglycemia were compared before and after CGM initiation using a paired t-test.
    Results: This study included 3,765 children and adolescents (2,313 CGM users and 1,452 non-users). During a median follow-up of 2.7 years, CGM users showed a lower risk of DKA (adjusted HR, 0.44; 95% confidence interval [CI], 0.35 to 0.56) and severe hypoglycemia (adjusted HR, 0.48; 95% CI, 0.29 to 0.79) than non-users. Among CGM users, the mean frequency of DKA decreased by 64%, and that of severe hypoglycemia decreased by 57% after CGM initiation (P<0.001 for both).
    Conclusion: In this nationwide cohort study, CGM was associated with a reduced risk of DKA and severe hypoglycemia in children and adolescents with T1DM.
    Keywords:  Adolescent; Child; Continuous glucose monitoring; Diabetes complications; Diabetes mellitus, type 1; Diabetic ketoacidosis; Hypoglycemia
    DOI:  https://doi.org/10.4093/dmj.2025.0794
  7. Diabetologia. 2026 Apr 22.
    Time delays between fingerstick glucose measurements and correctional insulin administration in the hospital: do they really matter?
    Kristen L Flint, Alana Fahey, Rebecca Longo, WuQiang Fan, Amy Doytchinov, Annabelle Ashley, Hui Zheng, Barbara A Steiner, Steven J Russell, Melissa S Putman.
       AIMS/HYPOTHESIS: Time delays exist between inpatient blood glucose measurements, insulin administration and meal timing. The clinical impacts of time delay on insulin dosing and hypoglycaemia risk have not been fully evaluated.
    METHODS: In this single-centre observational study, hospitalised individuals treated with insulin wore blinded Dexcom G6 Pro continuous glucose monitors (CGM) and received usual diabetes care. CGM values were matched by time to point-of-care (POC) blood glucose values and correctional insulin administration episodes. For each matched episode, time delay between POC measurement and correctional insulin administration and the difference between corresponding CGM values were calculated. Clinical impact of time delay was identified if insulin dosing would have changed with an updated glucose measurement.
    RESULTS: Across 243 participants, 2204 matched glucose-correctional insulin administration episodes were identified. Mean time delay (± SD) was 52.5 ± 37.4 min with mean absolute difference between CGM values of 1.0 ± 1.2 mmol/l. Had an updated CGM value at time of insulin administration been used, a different dose of correctional insulin may have been given in 28.4% of patient episodes.
    CONCLUSIONS/INTERPRETATION: Time delay between inpatient POC glucose measurements and correctional insulin administration varies widely and may alter insulin dosing. Future studies are needed to investigate the role of CGM in optimising insulin dosing in the hospital.
    Keywords:  Continuous glucose monitoring; Correctional insulin; Hospital; Inpatient
    DOI:  https://doi.org/10.1007/s00125-026-06737-y
  8. Diabetes Care. 2026 May 01. 49(5): e84-e85
    Comment on Valent et al. Real-Time Continuous Glucose Monitoring in Pregnancies With Gestational Diabetes Mellitus: A Randomized Controlled Trial. Diabetes Care 2025;48:1581-1588.
    Yan Jin, Yongli Jin, Guojie Zhang.
      
    DOI:  https://doi.org/10.2337/dc25-2018
  9. Diabetologia. 2026 Apr 24.
    Updated glucose management indicator (GMI) better aligns with HbA1c than current GMI: implications for clinical practice and reporting.
    Richard M Bergenstal, Yongjin Xu, Timothy C Dunn, Pratik Choudhary, Ramzi A Ajjan.
       AIMS/HYPOTHESIS: The continuous glucose monitoring (CGM)-derived glucose management indicator (GMI) is valuable to people with diabetes, and healthcare professionals and organisations for assessing overall glucose levels, optimising management plans. However, the current GMI can both over- and underestimate HbA1c, which can create clinical difficulties. Our aim was to improve the agreement between these two markers across clinically relevant ranges of glucose.
    METHODS: An updated GMI (uGMI) model based on physiological processes was evaluated using clinical trial and real-world data. The empirical relationship between average glucose (AG) and HbA1c was evaluated over 100 equal-sized data bins ordered by the sum of their rank positions. Alignments were assessed using biases in various ranges.
    RESULTS: In 18,860 individuals with 26,647 AG-HbA1c pairs, the uGMI significantly improved alignment with HbA1c and reduced the proportion of pairs with clinically significant discordance. Specifically, the regression slope of HbA1c vs GMI decreased from 1.4 to 1.0 when using uGMI, effectively eliminating proportional bias by reducing the deviation from unity (p<0.0001). Furthermore, absolute bias at HbA1c below 31 mmol/mol (5.5% in National Glycohemoglobin Standardization Program [NGSP]) and above 75 mmol/mol (9.0% NGSP) was reduced from >4.4 mmol/mol (0.4% NGSP) to ≤1.1 mmol/mol (0.1% NGSP). Consistent performance across both Abbott Freestyle Libre and Dexcom CGM devices confirmed that the uGMI is robust and device-independent, supporting its clinical utility and incorporation into standardised CGM clinical summary reports.
    CONCLUSIONS/INTERPRETATION: Compared with the CGM-derived GMI, the uGMI provides more accurate and consistent agreement with HbA1c, particularly at lower (<42mmol/mol or 6% NGSP) and higher (>58 mmol/mol or 7.5% NGSP) HbA1c levels.
    Keywords:  Continuous glucose monitoring; Glucose management indicator; HbA1c ; Proportional bias; Updated glucose management indicator
    DOI:  https://doi.org/10.1007/s00125-026-06739-w
  10. J Pharm Technol. 2026 Apr 21. 87551225261433431
    Pharmacy Student Confidence and Practice Readiness After Diabetes Educational Module With CGM Use.
    Allison Hursman, Elizabeth Monson, Allyson Luthi, Jeanne E Frenzel.
      Background: Pharmacists support diabetes technology in practice, yet formal instruction on continuous glucose monitoring (CGM) in Doctor of Pharmacy (PharmD) curricula is limited. Hands-on learning may build confidence and practice readiness for CGM-enabled care. Objective: To assess the impact of a diabetes education module, paired with short-term personal CGM use on pharmacy students' confidence, beliefs, and reflections related to diabetes care. Methods: Three cohorts of third-year pharmacy students completed pre- and post-surveys surrounding a 2-week diabetes education module delivered within a pharmacy skills laboratory. The intervention included didactic instruction and hands-on stations addressing core components of diabetes management including a personal CGM user wear experience. Quantitative analyses included t tests and analysis of variance. Student reflections were thematically analyzed. Results: Data from 148 student responses (84 pre-intervention; 64 post-intervention) were analyzed as independent samples. Belief scores demonstrated low reliability and remained stable over time (P > 0.05). In contrast, confidence scores showed high reliability and increased significantly following the intervention (mean 2.44 vs 4.50; P < 0.001), with a large effect size. Confidence differed by academic year, while belief scores did not. Qualitative analysis of 159 student responses identified themes of increased knowledge, awareness of glucose impacts, and readiness for pharmacy practice. Limitations include the single-institution setting, unpaired surveys, and reliance on self-reported, short-term outcomes. Conclusion: A diabetes education module incorporating short-term CGM use substantially improved student confidence and yielded practice-relevant insights, while beliefs remained stable. Structured hands-on CGM education may better prepare pharmacy graduates for technology-enabled diabetes care.
    Keywords:  continuous glucose monitoring; diabetes education; diabetes technology; hands-on learning; pharmacy education; skills laboratory
    DOI:  https://doi.org/10.1177/87551225261433431
  11. J Am Coll Clin Pharm. 2026 Feb;9(2): e70171
    A Pre-Post Assessment of Blood Glucose Control Following Pharmacist-Led Professional Continuous Glucose Monitoring in Rhode Island Primary Care Practices.
    Kelley Doherty Sanzen, Natalya S Salganik, Susanne M Campbell, Carolyn A Karner, Pano M Yeracaris, Stephen J Kogut.
       BACKGROUND: Professional continuous glucose monitoring (proCGM) can improve glycemic control and support medication and lifestyle adjustments in people with diabetes. In 2022, the Care Transformation Collaborative of Rhode Island launched a quality improvement initiative to implement pharmacist-led proCGM services in primary care practices. This project aimed to determine the effects of a pharmacist-led proCGM service on glycemic control, overall and by practice site, compared to baseline hemoglobin A1C (A1C) level. A secondary aim was to assess care team members' views of the program impact on patients and the practice environment.
    METHODS: A pre-post design was employed to assess reduction in A1C level 6 months following the implementation of pharmacist-led proCGM at six primary care sites. Pharmacists placed sensors, interpreted CGM data, and initiated diabetes medication changes. Eligible adult patients had either suboptimal glycemic control, discordant A1C and self-monitoring data, high hypoglycemia risk, or were referred by a provider. Changes in A1C were assessed 3-6 months after proCGM use. Care team surveys captured perceptions of the program's impact and sustainability.
    RESULTS: Among 396 patients, mean A1C decreased from 9.36% to 8.25% (p < 0.0001). A ≥ 1% point A1C reduction was achieved in 45.2% of patients. In multivariable analysis, baseline A1C was the strongest predictor of A1C improvement. Patients not using insulin and those who adopted personal CGM after the intervention were also more likely to improve. The majority of 51 care team members who completed the survey strongly agreed the service had positive impacts on patients and staff, and a majority believed the service could be sustainable.
    CONCLUSION: Pharmacist-led proCGM services were associated with meaningful short-term A1C reductions, especially in patients with high baseline A1C not using insulin. The model was well-received by care teams and may help expand access to effective diabetes management in primary care settings.
    Keywords:  continuous glucose monitoring; diabetes mellitus; glucose; pharmacist
    DOI:  https://doi.org/10.1002/jac5.70171
  12. Diabetes Care. 2026 May 01. 49(5): e86-e87
    Response to Comment on Valent et al. Real-Time Continuous Glucose Monitoring in Pregnancies With Gestational Diabetes Mellitus: A Randomized Controlled Trial. Diabetes Care 2025;48:1581-1588.
    Amy M Valent, Lucy Ward.
      
    DOI:  https://doi.org/10.2337/dci25-0112
  13. BMC Med. 2026 Apr 21.
    The role of continuous glucose monitoring for diagnosis of gestational diabetes: exploring the potential.
    M Crowley, C Newman, F P Dunne.
      The diagnosis of gestational diabetes relies upon an oral glucose tolerance test which has established limitations and suboptimal levels of patient adherence. Despite use of different diagnostic criteria globally, rates of GDM are increasing in line with increasing rates of obesity. There is a clinical need to establish an alternative methodology to diagnose GDM. Recent studies have examined the diagnostic role of continuous glucose monitoring with particular emphasis on glucometrics that correlate with adverse pregnancy outcome and may indicate CGM-based diagnostic thresholds for GDM. Additionally, CGM metrics associated with pharmacotherapy necessity have been identified. Given this work is observational and non-interventional, more robust data in the form of randomised control trials are required. Identification of diagnostic thresholds for GDM diagnosis will likely be outcome based and rely on a large international multicentre analysis.
    Keywords:  Continuous glucose measurement; Diabetes; Diagnosis; Gestation
    DOI:  https://doi.org/10.1186/s12916-026-04879-9
  14. Diabetes Res Clin Pract. 2026 Apr 20. pii: S0168-8227(26)00193-2. [Epub ahead of print] 113274
    Continuous glucose monitoring for cystic fibrosis-related diabetes: impact on quality of life and glycaemic control.
    Renee Martini, De-Arne Samm, Ashlee Routley, Lucia Gagliardi, Sally Chapman, Emily Hopkins, Mahesh Umapathysivam, Judith Morton.
       BACKGROUND/AIMS: Data for the use of continuous glucose monitoring (CGM) in cystic fibrosis related diabetes (CFRD) is lacking. The aim of this study is to establish efficacy and safety of CGM in CFRD to improve glycemic control and quality of life.
    METHODS: A prospective single-arm trial of 3 months CGM (Libre2®) in insulin requiring CFRD. All outcomes were assessed at baseline, completion of intervention and 3 months post completion. Glycemic control was assessed by glycated haemoglobin (HbA1c) and CGM metrics. QOL assessed by Problem Areas in Diabetes (PAID).
    RESULTS: 19 subjects were recruited. Median baseline HbA1c was 8.7% (72 mmol/mol) (IQR:8-10.6%, 64-92 mmol/mol), decreasing to 7.8% (62 mmol/mol) (IQR:7.3-8.3%, 56-67 mmol/mol), (p = 0.018) at completion of intervention, and remained lower than baseline at 8.0% (64 mmol/mol) (IQR: 7.0-9.0%, 53-75 mmol/mol) at 3 months post study intervention. Median baseline PAID score was 29.0 (IQR:16.0-48.5), decreasing to 16.0 (IQR: 11.0-22.0) (p = 0.02) at completion of intervention. At 3 months post completion median increased to 19.0 (IQR 11.5-23.0). There was no increase in time spent <3.0 mmol/L before and after sensor use (0.0% vs 0.3% p = 0.50).
    CONCLUSION: CGM use in CFRD improved QOL and glycaemic control without increases in hypoglycaemia.
    Keywords:  Continuous glucose monitoring (CGM); Cystic Fibrosis Related Diabetes (CFRD)
    DOI:  https://doi.org/10.1016/j.diabres.2026.113274
  15. Biomed Phys Eng Express. 2026 Apr 22.
    Turning sensors into predictors: The power of slope to anticipate hyper-and hypoglycemia.
    Claire Chou, Joan B Soriano, Sara Lumbreras.
      Objective&#xD;To show that moving from a purely level-based evaluation to a simple calculation enriched with the most recent slope (rate of change) yields meaningful, interpretable predictive gains for glycemic trajectories beyond static thresholds, based on continuous glucose monitoring (CGM) data.&#xD;&#xD;Approach&#xD;We analyzed CGM data from 16 adults in the BIG IDEAs Lab Glycemic Variability and Wearable Device dataset to forecast future glucose levels and classify hyperglycemia (≥180 mg/dL) and hypoglycemia (≤70 mg/dL). Using varying historical windows and prediction horizons, we trained regression (Lasso, Linear, Random Forest) and classification (Random Forest) models. We focused on interpretable predictors, especially current glucose and temporal slope features.&#xD;&#xD;Main results&#xD;For short-term predictions (<60 minutes), models achieved very high performance (accuracy >99.5%, recall >97%), driven mainly by the current glucose value and immediate slope. Performance declined gradually at longer horizons but remained strong; models leveraged earlier glucose values and slopes to capture diurnal patterns. Across all scenarios, slope vectors consistently ranked among the most informative predictors.&#xD;&#xD;Significance&#xD;Glucose dynamics and glycemic risk can be predicted accurately using a compact, physiologically grounded feature set that includes slope vectors. These findings empirically support the clinical relevance of biomarker velocity and motivate integrating slope-based analytics into wearables for real-time monitoring and decision-support. &#xD; &#xD.
    Keywords:  forecasting; glucose; hypoglycemia; interpretability; phyperglycemia; prediction
    DOI:  https://doi.org/10.1088/2057-1976/ae6348
  16. Arch Pediatr. 2026 Apr 20. pii: S0929-693X(26)00063-1. [Epub ahead of print]33(4): 105517
    Continuous glucose monitoring (CGM): Assessment and impact on glycemic control in children and adolescents with type 1 diabetes in Cameroon: A pilot study.
    Marguerite Edongue Hika, Marie-Ange Ngo Nkoum, Ritha Mbono, Agathe Mendomo, Sabine Baron, Suzanne Sap Ngo Um.
       BACKGROUND: Optimal glycemic control in children with type 1 diabetes (T1D) is linked to the number of self-monitoring blood glucose (SMBG) measurements they perform daily. In low-resource countries, this depends on the availability of glucose testing strips, which is often uncertain. The use of discontinuous flash monitoring is limited, and its effect on HbA1c remains unknown in our setting.
    AIM: This study aimed to examine whether intermittent use of a flash monitoring device for 14 days could improve HbA1c levels at 3 months in children and adolescents with T1D.
    METHODS: This cohort study involved 30 children with T1D aged 4-18 years, who were followed at the Mother and Child Center of the Chantal Biya Foundation in Yaounde, Cameroon. HbA1c was measured before and three months after 14 days of flash monitoring, along with glucose metrics. Flash monitoring devices were donated. Results are presented as median and interquartile range.
    RESULTS: The median age of the children was 15.5 years (11.4-16.7 years), and the median diabetes duration was 3.8 years (1.75-5.6 years). Children received a multiple daily injection regimen with a combination of human insulin and NPH insulin. During flash monitoring, the highest median interstitial glucose level was 266 mg/dl (191-327 mg/dl), recorded between 6:00 and 12:00. Hypoglycemia was rare and mostly occurred between 12:00 and 18:00. The mean time in range, above range, and below range were 26 %, 65 %, and 5 %, respectively. Appropriate glycemic control (TIR > 70 %) was observed in two patients (7 %). The mean HbA1c decreased from 10 % (8.3-12 %) at M0 to 9.3 % (8.5-11.3 %) at M3 (p < 0.01), after the use of flash monitoring for 14 days.
    CONCLUSION: Glycemic control in our study population is poor but can be improved with Flash Monitoring, even if it is discontinuous.
    Keywords:  Cameroon; Continuous glucose monitoring; Flash monitoring; Glycemic control; HbA1c; Time above range; Time below range; Time in range
    DOI:  https://doi.org/10.1016/j.arcped.2026.105517
  17. Endocr Pract. 2026 Apr 20. pii: S1530-891X(26)00954-7. [Epub ahead of print]
    Agreement Between HbA1c and Continuous Glucose Monitoring-Derived Glycemic Metrics in Adults with Cystic Fibrosis Related Diabetes.
    Ammar Ahmed, Jaspreet Batth, Qi Wang, Timothy B Vigers, Katie Larson Ode, Christine L Chan, Amir A Moheet.
       OBJECTIVE: Cystic fibrosis related diabetes (CFRD) is a prevalent complication of cystic fibrosis that requires accurate assessment of glycemic control to guide management. Whether HbA1c reliably reflects mean glycemia in adults with CFRD, particularly in the context of CGM adoption and modern CFTR modulator therapy, remains uncertain.
    METHODS: This retrospective cross-sectional study, conducted at a single CF center, evaluated adults with confirmed CFRD who had a laboratory HbA1c paired with at least 30 days of CGM data with ≥70% active sensor time during the preceding 30-90 days. Individuals with conditions that affect HbA1c reliability, such as anemia, advanced chronic kidney disease, or pregnancy, were excluded.
    RESULTS: Forty-nine adults met the inclusion criteria (mean age 43.9 ± 11.6 years; 69.4% male), with high CGM adherence (median sensor active time of 97%). Their mean HbA1c was 7.3% ± 1.1% (56 ± 12 mmol/mol), while mean GMI and mean sensor glucose were 7.6% ± 1.0% (60 ± 11 mmol/mol) and 178.6 ± 40.3 mg/dL (9.9 ± 2.2 mmol/L), respectively. HbA1c demonstrated strong correlations with GMI (r = 0.90; P < .0001) and mean sensor glucose (r = 0.90; P < .0001). Bland-Altman analysis showed a mean bias of +0.30% (GMI-HbA1c), with 95% limits of agreement from -0.65% to +1.25% and no proportional bias across the glycemic range.
    CONCLUSION: These findings indicate that HbA1c closely reflects CGM-derived mean glycemia in adults with established CFRD. While CGM metrics provide complementary clinical information, integrating both measures may improve monitoring and therapeutic decision-making in CFRD care.
    Keywords:  CFTR modulator therapy; Continuous glucose monitoring; Cystic fibrosis related diabetes; Glucose Management Indicator; Hemoglobin A1c; glycemic monitoring in CFRD
    DOI:  https://doi.org/10.1016/j.eprac.2026.04.007
  18. J Cyst Fibros. 2026 Apr 23. pii: S1569-1993(26)00094-9. [Epub ahead of print]
    Machine learning analysis of continuous glucose monitoring identifies a novel dysglycemic phenotype found in most people with cystic fibrosis.
    Jiafeng Song, Jessica Alvarez, Alasdair Gent, Scott Gillespie, Ryan A Harris, Jocelyn McNeany, Tanicia Daley, Rishikesan Kamaleswaran, Arlene Stecenko.
       BACKGROUND: Cystic fibrosis related diabetes (CFRD) is a common complication in people with cystic fibrosis (PwCF), yet traditional diagnostic tools such as fasting glucose, HbA1c, and the oral glucose tolerance test (OGTT) often fail to detect early dysglycemia. Continuous glucose monitoring (CGM) generates high resolution glucose data, but analytic methods for extracting meaningful phenotypes remain limited.
    METHODS: CGM data from 82 PwCF aged 6 to 78 years were compared with 166 healthy controls (HC). Thirty-two glycemic features were extracted from 24-hour CGM segments. Uniform Manifold Approximation and Projection (UMAP) was trained using HC and CFRD data, and Silhouette scores quantified the alignment of each daily profile with these clusters. Group differences were evaluated using linear mixed effects models.
    RESULTS: UMAP showed complete separation between HC and CFRD. Mean Silhouette score values were +0.35 (95% CI: 0.31 to 0.38) for HC and -0.77 (95% CI: -0.83 to -0.71) for CFRD. PwCF classified as normal glucose tolerance (NGT) or impaired glucose tolerance (IGT) had negative Silhouette score values, -0.58 (95% CI: -0.67 to -0.49) and -0.56 (95% CI: -0.63 to -0.49), with no difference between groups.
    CONCLUSIONS: Machine learning analysis of CGM data revealed a pervasive dysglycemic phenotype in PwCF. NGT and IGT individuals showed similar glycemic profiles shifted toward the CFRD phenotype, indicating that OGTT categories underestimate early metabolic dysfunction. CGM based digital phenotyping offers a more sensitive and continuous assessment of dysglycemia and may improve early detection and risk stratification in PwCF.
    Keywords:  Continuous glucose monitoring; Cystic fibrosis; Cystic fibrosis related diabetes; Glucose dysglycemia; Machine learning
    DOI:  https://doi.org/10.1016/j.jcf.2026.04.001
  19. Adv Ther. 2026 Apr 18.
    The Lived Experiences of Adult Continuous Glucose Monitor Users with Type 1 Diabetes with Recurrent Severe Hypoglycemic Events and Impaired Awareness of Hypoglycemia: A Qualitative Study.
    Adriana Boateng-Kuffour, Caitlin S Kelly, Huyen T Nguyen, Keval Chandarana, Katherine S Chapman, Liang Chen, Emilee M Cornelius, Wendy A Wolf, William H Polonsky.
       INTRODUCTION: Although type 1 diabetes (T1D) technology has improved health outcomes for many, some people continue to experience severe hypoglycemic events (SHEs). This study reviews the history of SHEs and impaired awareness of hypoglycemia (IAH) compound risk for future SHEs, and describes the lived experiences of SHEs among adult people with T1D (pwT1D) with recurrent SHEs (≥ 2/year) and IAH who use continuous glucose monitors (CGMs).
    METHODS: In this online survey study with eligible CGM-users from the T1D Exchange Registry, participants were asked open-ended questions on the impact of SHEs on their lives, then responses were analyzed thematically. Participants reporting ≥ 2 SHEs in the last year and IAH were included in the analytic sample.
    RESULTS: Participant (n = 158) responses were coded into 12 thematic categories. A total of 82% of participants reported one or more of the following themes: Emotional and Psychological Impact of SHEs, Social/Relationships Impacts, and Attempts to Prevent and Cope. Specifically, nearly half of participants described the Emotional and Psychological Impact of SHEs (49.4%), with fear around hypoglycemia being especially prominent (e.g., "I worry I might pass out and not wake up…"). Over one-third of participants described impacts of SHEs on their Social Relationships (33.5%), including increased distress from their loved ones. Remaining themes described impacts on numerous other domains of life.
    CONCLUSION: Adult pwT1D using CGMs who had recurrent SHEs and IAH experience substantial burden in their daily lives. New therapeutic options to help this population eliminate SHEs and meet T1D treatment goals would be especially beneficial.
    Keywords:  Burden of illness; Hypoglycemia; Qualitative research; Quality of life; Severe hypoglycemia; Type 1 diabetes mellitus (T1D); Unawareness
    DOI:  https://doi.org/10.1007/s12325-026-03585-5
  20. Kaohsiung J Med Sci. 2026 Apr 22. e70221
    Correlations Among Glycemia and Glucose Variability, Thyroid Hormones, and Albuminuria in Patients With Type 2 Diabetes Mellitus.
    Na Luo, Shang-Yong Feng, Hui Chen, Dun-Min She, Yan Liu, Ying Li, Cai-Feng Yan, Zhen-Wen Zhang, Jing Chen, Xiao-Li Cai, Gao-Yu Zhao, Hui Yu, Yan Wang.
      Hyperglycemia, glucose fluctuations, and thyroid dysfunction contribute to the progression of diabetic nephropathy. This study aimed to investigate the associations of glycemia, glucose variability, and thyroid hormones with albuminuria in patients with type 2 diabetes mellitus (T2DM). In total, 451 T2DM patients were included. The data of continuous glucose monitoring system (CGMS)-generated indices, thyroid hormones, and the ratios of urine creatinine to urine microalbumin (URCA) were collected. There were 152 patients with normal URCA (< 30 mg/g), 230 patients with microalbuminuria (30 mg/g ≤ UACR < 300 mg/g), and 69 patients with macroalbuminuria (UACR ≥ 300 mg/g). Free triiodothyronine (FT3) was negatively correlated with hemoglobin A1C (HbA1C), glucose, and glucose variability in T2DM patients (most p < 0.05). HbA1C (p = 0.002), the standard deviation (SD) of glucose (p < 0.001), the coefficient of variation (CV) of glucose (p < 0.001), the time below range (TBR) (p = 0.002), and the mean amplitude of glycemic excursions (MAGE) (p = 0.033) were positively associated with albuminuria. Moreover, FT3 was negatively associated with macroalbuminuria (p = 0.003). According to multivariate logistic regression analyses, HbA1C, SD, and CV of glucose, the TBR, and the MAGE were independently associated with a greater risk of albuminuria after adjustment for demographics, duration of T2DM, biochemical indices, and medications for T2DM and hypertension (all p < 0.05). Moreover, the associations of HbA1C, SD, and CV of glucose, TBR, and MAGE with albuminuria were partially mediated by FT3, FT3, and TSH, but the weight of mediation was low. In conclusion, glycemia and glucose variability derived from the CGMS are correlated with a lower level of FT3, and they are positively associated with albuminuria in patients with T2DM.
    Keywords:  albuminuria; continuous glucose monitoring system; glucose variability; thyroid hormone; type 2 diabetes mellitus
    DOI:  https://doi.org/10.1002/kjm2.70221
  21. Diabetes Ther. 2026 Apr 21.
    Technology in Diabetes: A Year in Review.
    Subhankar Chatterjee, Subhodip Pramanik, Nitin Kapoor, Sanjay Kalra.
      The past year has continued the rapid evolution of diabetes technology across the monitoring, delivery, analytics, and patient-support domains. Improvements in continuous glucose monitoring (CGM) accuracy and wear-time options, widening use and regulatory expansion of automated insulin delivery (AID) systems, growth in connected insulin pens, maturation of digital therapeutics, and an influx of artificial intelligence (AI)-driven decision support tools have together shifted diabetes care toward tighter, more personalized, and more remote models of management. At the same time, device safety events, persistent affordability and access gaps, and data-interoperability and privacy challenges remind clinicians and policymakers that technology alone is not a panacea. This review summarizes the most important developments from last year (2025), highlights evidence from recent trials and regulatory actions, and discusses implications for practice and future directions.
    Keywords:  Artificial intelligence; Automated insulin delivery; Continuous glucose monitoring system; Diabetes technology; Digital therapeutics; Smart insulin pen
    DOI:  https://doi.org/10.1007/s13300-026-01871-7
  22. J Funct Morphol Kinesiol. 2026 Apr 14. pii: 153. [Epub ahead of print]11(2):
    Technology-Enhanced Exercise Training for Cardiometabolic Syndrome: A Scoping Review.
    Iosif-Alexandros Kouidis, Pantazis Deligiannis, Anastasia Theofanous, Maria Anifanti, Evangelia Kouidi.
      Background: Μetabolic syndrome (MetS)-comprises central adiposity, elevated blood pressure, dyslipidaemia, and dysglycaemia, increasing the risk of type 2 diabetes and cardiovascular disease. Exercise training improves cardiorespiratory fitness and several MetS components, but real-world effectiveness is limited by poor adherence, restricted supervision, and insufficient personalisation. Objective: This scoping review mapped the clinical intervention evidence on technology-enhanced exercise and structured physical activity relevant to MetS, while distinguishing direct MetS evidence from translational evidence. Methods: In accordance with PRISMA-ScR, we searched PubMed and extended the search to Scopus and Web of Science; a supplementary IEEE Xplore search and a post hoc Embase check were also conducted. Eligible studies were interventions using web-based delivery, wearables, telemonitoring/mobile health (mHealth), artificial intelligence (AI) coaching, virtual reality (VR)/exergaming, or continuous glucose monitoring (CGM) alongside exercise training or structured physical activity. Results: Nineteen studies met the eligibility criteria. The evidence base was weighted toward wearable/app-based feedback and telemonitoring/mHealth/web-based approaches, with fewer studies on VR/exergaming, CGM-enabled exercise, and AI coaching. Most studies were randomised or cluster-randomised, but interventions were usually short term. Across categories, technology most consistently supported adherence, self-monitoring, accountability, remote supervision, and, in selected cases, physiology-informed personalisation. Direct MetS evidence was strongest for wearables with structured feedback, telemonitoring, mHealth, and web-based delivery, whereas AI coaching and CGM were supported by adjacent translational evidence. Conclusions: Technology-enhanced exercise and structured physical activity show promising but heterogeneous and still preliminary potential for MetS management. Key limitations include short follow-up, uneven representation across categories, inconsistent reporting of exercise dose/intensity fidelity and adverse events, and limited equity and implementation outcomes.
    Keywords:  artificial intelligence; cardiometabolic risk; continuous glucose monitoring; exercise training; exergaming; metabolic syndrome; structured physical activity; telemonitoring; virtual reality; wearable devices
    DOI:  https://doi.org/10.3390/jfmk11020153
This page is being maintained by Thomas Krichel. It was last updated on 2026‒04‒26 at 0:09.