bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2026–02–08
eleven papers selected by
Mott Given
  1. Correction to "Continuous glucose monitoring in early gestational diabetes improves maternal and neonatal outcomes-The Steady Sugar trial".
  2. The IDEA Framework: A Consensus-Based Model for Integrating Continuous Glucose Monitoring into Pharmacy Practice for Diabetes Care.
  3. Optimizing Continuous Glucose Monitoring Adoption in India: From Current Challenges to Future Solutions.
  4. Effectiveness of continuous glucose monitoring on maternal and neonatal outcomes in gestational diabetes mellitus: a systematic review and meta-analysis.
  5. Diabetes Monitoring in Pregnant Women with Type 1 Diabetes: Capillary Blood Glucose or Interstitial Fluid Glucose? A Case Control Study.
  6. Identification of severe hypoglycemia in adults with type 1 diabetes using CGM-based machine learning: evidence from the FGM-Japan study.
  7. The impact of continuous glucose monitoring in pharmacist-supported diabetes care: Evidence mapping through a scoping review.
  8. Effectiveness and acceptability of continuous glucose monitoring in the detection of hypoglycaemia among renal dialysis patients with diabetes mellitus: A pilot study.
  9. Safety and Feasibility of Algorithmic Continuous Glucose Monitoring-Based Titration in People with Type 2 Diabetes Using Insulin Degludec, With or Without Noninsulin Glucose-Lowering Drugs: A 16-Week Randomized Controlled Trial.
  10. Association of Time in Tight Range with Microvascular Complications in Japanese Patients with Type 2 Diabetes Mellitus: A Multicenter Cross-Sectional Study.
  11. Systematic Review of Continuous Glucose Monitor Accuracy in the Hypoglycemia Range for Non-Critical Care Ward Hospitalized People Living With Diabetes.
  1. Diabetes Obes Metab. 2026 Feb 02.
    Correction to "Continuous glucose monitoring in early gestational diabetes improves maternal and neonatal outcomes-The Steady Sugar trial".
      
    DOI:  https://doi.org/10.1111/dom.70544
  2. Can J Diabetes. 2026 Feb 02. pii: S1499-2671(26)00025-0. [Epub ahead of print]
    The IDEA Framework: A Consensus-Based Model for Integrating Continuous Glucose Monitoring into Pharmacy Practice for Diabetes Care.
    Aaron Sihota, Akshay B Jain, Alicia Chin, Walter Chow, Susie Jin, Trisha Molberg, Smita Patil, Rick Siemens, Sivajanan Sivapalan, Tim Smith, Ilana Halperin.
      
    Keywords:  consensus recommendations; continuous glucose monitoring; diabetes management; hypoglycemia prevention; pharmacist role
    DOI:  https://doi.org/10.1016/j.jcjd.2026.01.005
  3. Diabetes Ther. 2026 Feb 02.
    Optimizing Continuous Glucose Monitoring Adoption in India: From Current Challenges to Future Solutions.
    Jothydev Kesavadev, V Mohan, Shashank Joshi, Banshi Saboo, Manoj Chawla, A G Unnikrishnan, Om Lakhani, Amit Gupta, Rakesh Parikh, Abhijith Bhograj, Anuj Maheshwari, Ameya Joshi, Timor Glatzer, Sandeep Sewlikar, Abin Augustine.
      Despite revolutionizing diabetes care globally, continuous glucose monitoring (CGM) adoption in India remains limited, as a result of several economic, infrastructural, clinical, and sociocultural concerns. This narrative review aims to map unmet needs and propose practical, context-specific solutions. Continuous use of CGM remains the preferred approach for optimal glucose management and achieving long-term metabolic advantages, providing insights for proactive, data-driven, and preventive diabetes care. However, main barriers to CGM uptake include limited awareness among people with diabetes and healthcare providers, high costs, lack of reimbursement, limited device availability beyond major cities, and economic, infrastructural, and sociocultural access inequities across urban and rural populations. The psychological burden from frequent alarms, data fatigue, and stigma with noticeable or intrusive devices add to these challenges. Addressing these barriers necessitates a multifaceted strategy involving affordable, climate-adapted devices, interoperable digital ecosystems, India-specific reimbursement models, and robust educational infrastructure. The emergence of cost-effective CGM devices with a range of advanced features, such as predictive glucose algorithms and personalized pattern identification, is pivotal to this effort. These innovations improve clinical outcomes and quality of life by simplifying the user experience, addressing challenges, such as alarm fatigue while translating complex data into actionable insights, facilitating widespread CGM adoption in India.
    Keywords:  Adherence; Alarm fatigue; CGM in India; Continuous glucose monitoring; Diabetes; Diabetes stigma; Glucose predictions; Glycaemic variability; Reimbursement; Technological innovation
    DOI:  https://doi.org/10.1007/s13300-026-01842-y
  4. BMC Pregnancy Childbirth. 2026 Jan 30.
    Effectiveness of continuous glucose monitoring on maternal and neonatal outcomes in gestational diabetes mellitus: a systematic review and meta-analysis.
    Renuka Suvarna, Sahana Shetty.
      
    Keywords:  CGM; GDM; Maternal outcomes; Neonatal outcomes; SMBG
    DOI:  https://doi.org/10.1186/s12884-026-08663-8
  5. Nutr Metab Insights. 2026 ;19 11786388251408962
    Diabetes Monitoring in Pregnant Women with Type 1 Diabetes: Capillary Blood Glucose or Interstitial Fluid Glucose? A Case Control Study.
    Chaima Jemai, Yosra Htira, Amal Salem, Zohra Hadj Ali, Olfa Lajili, Imen Hedfi, Sarra Ben Amara, Faika Ben Mami.
       Background: Type 1 diabetes mellitus is associated with adverse maternal and neonatal outcomes. We aimed to evaluate the impact of CGM use on glycemic control and neonatal and maternal outcomes.
    Methods: This was a single-center study with prospective longitudinal data collection of pregnant women with T1DM allocated to 1 of 2 monitoring methods: Capillary blood monitoring and interstitial fluid glucose monitoring.
    Results: A total of 30 patients were enrolled. The average age was 31.26 ± 3.39 years, with an average gestational age of 9.4 ± 3.63 weeks at the first consultation. The average diabetes duration was 15.6 ± 7.36 years, with a mean preconception HbA1c of 8.67 ± 0.95%. The average BMI was 25 ± 2.88 kg/m2, and the average weight gain throughout pregnancy was 8.26 ± 5.84 kg. There was a substantial decrease in TBR compared to the control group. The control group had a slightly greater rate of pregnancy-induced hypertension, toxemia, eclampsia, and premature labor (33%, 13%, 7%, and 40%, respectively) than the CGM group (26%, 7%, 0%, and 26%). The differences were not statistically significant. Furthermore, the control group had a greater rate of preterm birth, neonatal hypoglycemia, NICU admission, and congenital abnormalities (27%, 40%, 46%, and 6.7%, respectively) than the CGM group (20%, 33%, 33%, and 0%, respectively), with no significant differences. The rates of macrosomia (20%), LGA (13%), neonatal respiratory distress (33%), and stillbirth (7%) were comparable between the groups. However, hydramnios occurred slightly more frequently in the CGM group (46% vs 40% in the control group).
    Conclusion: Early implementation and sustained use of CGM in pregnant women with T1DM may optimize glucose control and mitigate maternal-fetal risks.
    Keywords:  capillary glucose monitoring; continuous glucose monitoring; glycemia; pregestational diabetes; pregnancy; type 1 diabetes mellitus
    DOI:  https://doi.org/10.1177/11786388251408962
  6. Diabetol Int. 2026 Apr;17(2): 21
    Identification of severe hypoglycemia in adults with type 1 diabetes using CGM-based machine learning: evidence from the FGM-Japan study.
    Naoki Sakane, Yushi Hirota, Akane Yamamoto, Junnosuke Miura, Hiroko Takaike, Sari Hoshina, Masao Toyoda, Nobumichi Saito, Kiminori Hosoda, Masaki Matsubara, Atsuhito Tone, Satoshi Kawashima, Hideaki Sawaki, Tomokazu Matsuda, Masayuki Domichi, Akiko Suganuma, Seiko Sakane, Takashi Murata.
       Background: Severe hypoglycemia (SH) in adults with type 1 diabetes mellitus (T1DM) is associated with significant morbidity and mortality; however, its underlying causes are often complex and multifactorial. Improved tools to identify individuals at a high risk of SH are critically needed. In this study, machine learning techniques were applied to continuous glucose monitoring (CGM) data to identify distinguishing features between individuals with and without SH episodes.
    Methods: We analyzed data from the real-world study of adults with T1DM enrolled in the FGM-Japan study. Eleven machine learning algorithms using continuous glucose monitoring (CGM) metrics were applied to identify SH and assess the relative importance of the contributing features. The CGM metrics included mean glucose/GMI, time above range (TAR > 250 and > 180 mg/dL), time in range (TIR 70-180 mg/dL), time below range (TBR < 70 and < 54 mg/dL), coefficient of variation (%CV), and glycemic risk index (GRI). The model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, precision, recall, and F1 score.
    Results: Data from 264 adults with T1DM were analyzed. Across the models, XGBoost showed the highest AUC, significantly outperforming logistic regression, k-NN, and SVM but performed marginally below Naive Bayes. The F1-score analysis showed that logistic regression and neural networks provided a better balance between precision and recall. The model using four CGM variables (TBR < 70, %CV, GMI, and GRI) achieved the highest AUC of 0.794.
    Conclusions: XGBoost offers strong overall discrimination; however, simpler models exhibit better F1 performance. Features like 'TBR', '%CV', 'GMI,' and 'GRI' were key features, suggesting their usefulness in identifying individuals at risk for adverse glycemic events.
    Trial registration: Clinical Trial Registry No. UMIN000039376.
    Supplementary Information: The online version contains supplementary material available at 10.1007/s13340-025-00872-4.
    Keywords:  Continuous glucose monitoring; Machine learning; Severe hypoglycemia; Type1 diabetes
    DOI:  https://doi.org/10.1007/s13340-025-00872-4
  7. J Am Pharm Assoc (2003). 2026 Feb 03. pii: S1544-3191(26)00019-1. [Epub ahead of print] 103034
    The impact of continuous glucose monitoring in pharmacist-supported diabetes care: Evidence mapping through a scoping review.
    Joyce Y Lee, Daniella Chan, Manroop Samra, Marian Tan, Julie Nguyen.
       BACKGROUND: The adoption of continuous glucose monitoring (CGM) in diabetes care is rapidly expanding, offering opportunities to enhance glycemic management. As accessible healthcare providers, pharmacists are increasingly called upon to support patients in the use of digital health tools like CGM. However, the impact of CGM integration on pharmacist-involved diabetes services has not been systematically examined.
    OBJECTIVES: This scoping review aimed to map the breadth of available evidence on the impact of CGM on pharmacist-managed diabetes services and to identify gaps in the existing literature.
    METHODS: This scoping review was conducted using the five-stage methodological framework. Publications in English were searched in PubMed, Scopus, and CINAHL from inception through October 2025. Key search terms included "CGM," "continuous glucose monitor," "pharmacist," "pharmacy practice," and "pharmacist-led". Articles were included if they involved pharmacist participation in CGM-related interventions. Studies that lacked pharmacist involvement were excluded.
    RESULTS: Of the 87 articles identified, 20 met the inclusion criteria. The studies employed various designs, with A1C being the most reported clinical outcome. Significant A1C reductions associated with CGM-integrated pharmacist diabetes services ranged from -0.4% to -2.9%, compared to reductions of -0.5% to -0.8% in CGM-integrated care without pharmacists' involvement. Reporting of CGM-related metrics varied across the studies and included time in range, time above range, time below range, average interstitial glucose levels, and glucose variability. Nonclinical outcomes were generally positive with only 8 studies addressing the humanistic or economic aspects of CGM-integrated pharmacist diabetes services.
    CONCLUSION: This scoping review highlighted emerging but heterogeneous use of CGM metrics in CGM-integrated pharmacists' services in diabetes care. While reported outcomes were consistently positive, most studies focused on clinical parameters, particularly A1C. Future research should place greater emphasis on evaluating humanistic and economic outcomes of CGM on pharmacist-involved diabetes services.
    DOI:  https://doi.org/10.1016/j.japh.2026.103034
  8. J Diabetes Complications. 2026 Jan 16. pii: S1056-8727(26)00012-7. [Epub ahead of print]40(3): 109267
    Effectiveness and acceptability of continuous glucose monitoring in the detection of hypoglycaemia among renal dialysis patients with diabetes mellitus: A pilot study.
    Si Hui Evangeline Tan, Priscilla Juay Qi Gan, Ester Yeoh, Allen Yan Lun Liu.
       BACKGROUND: Hypoglycaemia remains a prevalent and dangerous complication of diabetes management in hospitalised dialysis patients, contributing to increased morbidity, mortality, and healthcare burden. This study evaluates the diagnostic performance, clinical applicability, and user acceptability of continuous glucose monitoring (CGM) in this vulnerable inpatient population.
    METHODS: A prospective pilot study was conducted involving 30 adult patients with diabetes mellitus undergoing either haemodialysis or peritoneal dialysis in an inpatient renal ward. Participants were monitored with the Dexcom G6 CGM system in parallel with routine capillary blood glucose (CBG) testing. Hypoglycaemic detection was assessed via sensitivity, specificity, positive predictive values (PPV), negative predictive values (NPV), and ROC analysis. Clinical concordance was evaluated using Bland-Altman plots, linear regression, mean absolute relative difference (MARD) and Parkes (Consensus) Error Grid analysis. Nurse and patient feedback were captured via validated questionnaires.
    RESULTS: CGM demonstrated a sensitivity of 68.8% and specificity of 97.3% for hypoglycaemia detection, with a PPV of 42.3% and a NPV of 99.1%. Subgroup analysis revealed similar trends across dialysis modalities, with slightly higher sensitivity in peritoneal dialysis patients. ROC curve analysis showed high diagnostic accuracy (area under the curve >0.95), while Bland-Altman and regression analyses confirmed strong agreement with CBG. The estimated MARD was 11.1%. Parkes (Consensus) Error Grid analysis also revealed that 98.6% (570 of 578) of CGM readings in clinically acceptable Zones A and B. Both patient satisfaction and nursing acceptance were high, supporting real-world feasibility.
    CONCLUSIONS: CGM is a safe, reliable, and well-accepted adjunct for detecting hypoglycaemia in hospitalised dialysis patients. Its high specificity and NPV make it particularly valuable for ruling out hypoglycaemia. Broader implementation may enhance safety and reduce nursing burden. Further research with larger cohorts is warranted.
    Keywords:  Continuous glucose monitoring; Diabetes; Diagnostic performance; Dialysis; Hypoglycaemia; Inpatient care; Patient safety
    DOI:  https://doi.org/10.1016/j.jdiacomp.2026.109267
  9. Diabetes Technol Ther. 2026 Feb 06. 15209156261420193
    Safety and Feasibility of Algorithmic Continuous Glucose Monitoring-Based Titration in People with Type 2 Diabetes Using Insulin Degludec, With or Without Noninsulin Glucose-Lowering Drugs: A 16-Week Randomized Controlled Trial.
    Anas El Fathi, Ralf Nass, Carol J Levy, Camilla Levister, Grenye O'Malley, Nirali A Shah, Shaziah Hassan, Cheryl Quainoo, Chaitanya L K Koravi, Taylor N Nguyen, Giulio Matteo Santini, Emma Emory, Carlene Alix, Dillon K Flanagan, David Fulkerson, Mary Clancy Oliveri, Christian Laugesen, Jonas K Lindeløv, Peter W Hansen, Marc D Breton.
       BACKGROUND: Continuous glucose monitoring (CGM) is increasing in insulin-treated type 2 diabetes (T2D). Yet, standardized CGM-based insulin titration is lacking. This study evaluated the feasibility of algorithmic CGM-based titration compared with self-monitoring blood glucose (SMBG) titration.
    METHODS: We conducted a 16-week, two-site, randomized controlled trial in adults with T2D (glycated hemoglobin 7%-9%) using degludec and adjunctive noninsulin agents, without rapid-acting insulin. Participants were assigned (2:1) to weekly algorithmic CGM-based dose changes with open CGM (EXP) or weekly SMBG-based titration with blinded CGM (CTR). Both groups received dose notifications via phone. The primary endpoint was the change in CGM-measured time in range (TIR, 70-180 mg/dL) from baseline to week 16, tested for noninferiority (-5%-percentage points [%-pt]). The trial is registered at ClinicalTrials.gov: NCT06111508.
    RESULTS: A total of 30 participants were randomized. Mean (standard deviation) TIR increased from 54.1% (22.5%) to 75.3% (19.3%) in EXP and from 50.2% (22.1%) to 55.3% (22.7%) in CTR. Mean change was +20.3%-pt versus +8.3%-pt, yielding an estimated treatment difference (EXP - CTR) of +14.6%-pt; one-sided 95% confidence interval (CI) lower bound was +4.0%-pt, exceeding the noninferiority margin (P < 0.005). Exploratory superiority analysis showed two-sided 95% CI: 1.3-27.8 (P = 0.03). CGM-measured hypoglycemia (<70 mg/dL) was low (median [interquartile range]: 0.34% [0.09-0.90] vs. 0.00% [0.00-0.41]), and level 2 episodes (SMBG <54 mg/dL) were rare (1.1 vs. 2.2 patient-year of exposure). No severe hypoglycemia or serious adverse events occurred.
    CONCLUSIONS: Using CGM and receiving algorithmic CGM-based titrations were feasible, safe, and had favorable overall glycemic metrics. Long-term impact should be confirmed in broader populations.
    Keywords:  CGM; long-acting insulin; titration algorithm; type 2 diabetes
    DOI:  https://doi.org/10.1177/15209156261420193
  10. Diabetes Technol Ther. 2026 Feb 04. 15209156251403563
    Association of Time in Tight Range with Microvascular Complications in Japanese Patients with Type 2 Diabetes Mellitus: A Multicenter Cross-Sectional Study.
    Keiichi Torimoto, Yosuke Okada, Tomoya Mita, Kenichi Tanaka, Fumiya Sato, Naoto Katakami, Hidenori Yoshii, Keiko Nishida, Shingo Nakayamada, Ryota Ishii, Masahiko Gosho, Iichiro Shimomura, Hirotaka Watada.
       BACKGROUND: To determine the correlation between time in tight range (TITR; 70-140 mg/dL) and prevalence of microvascular complications in patients with type 2 diabetes mellitus (T2DM).
    METHODS: Data of 999 patients with T2DM and negative history of cardiovascular disease were analyzed. TITR was assessed using data from a continuous glucose monitoring (CGM) system. Participants were stratified into quartiles based on TITR (Q1: ≤42.6%, Q2: >42.6 to ≤61.2%, Q3: >61.2 to ≤73.4%, Q4: >73.4%). The correlation of TITR/microvascular complications was assessed using multivariate logistic regression analysis after adjustment for potential confounders.
    RESULTS: The mean TITR was 56.8 ± 22.4%, and 51.2% of participants had at least one microvascular complication. The adjusted odds ratios for any microvascular complication across increasing TITR quartiles were 1.00 (Q1 as the reference group), 0.39 (Q2; 95% confidence interval [CI]: 0.25-0.62), 0.45 (Q3; 95% CI: 0.28-0.70), and 0.30 (Q4; 95% CI: 0.19-0.47). This indicated that the prevalence of diabetic microvasculopathies was lower in higher TITR quartiles. Similar inverse trends were observed for retinopathy, nephropathy, and peripheral neuropathy. Each 10% increase in TITR was associated with a reduced risk of each type of diabetic microvasculopathy. Receiver operating characteristic curve analysis identified 54.3% as the optimal TITR cutoff value for the identification of microvascular complications.
    CONCLUSIONS: Higher TITR was significantly associated with lower prevalence of microvascular complications in patients with T2DM. CGM-derived TITR is a potentially useful clinical metric for optimizing glycemic management and reducing the risk of microvascular complications.
    TRIAL REGISTRATION NUMBER: UMIN000032325.
    Keywords:  continuous glucose monitoring; microvascular complications; time in tight range; type 2 diabetes
    DOI:  https://doi.org/10.1177/15209156251403563
  11. J Diabetes Sci Technol. 2026 Jan 31. 19322968251412482
    Systematic Review of Continuous Glucose Monitor Accuracy in the Hypoglycemia Range for Non-Critical Care Ward Hospitalized People Living With Diabetes.
    Nicole Prince, Timothy Ramsay, Risa Shorr, Rémi Rabasa-Lhoret, Cathy J Sun.
      In-hospital standard of care for people living with diabetes (PLWD) is based on capillary blood glucose to activate hypoglycemia treatment protocols. PLWD on non-critical care wards often prefer to keep their continuous glucose monitor (CGM) on for their sense of agency. This systematic review assessed the CGM accuracy in the hypoglycemic range for these PLWD. Databases were searched from 2012 to August 2025. We included studies of adult PLWD on non-critical care wards, with CGM levels below 70 mg/dL (3.9 mmol/L) that were compared with paired reference blood glucose levels. Nine included studies reported on 465 hypoglycemic CGM and reference blood glucose pairs. The mean and median absolute relative differences ranged from 7.6% to 53.3%, and from 11.7% to 38.5%, respectively. The methods for pairing CGM with reference blood glucose varied. In eight studies, the mean absolute relative differences between hypoglycemia range CGM and paired reference blood glucose results were greater than 15%. These high mean absolute relative differences suggest that hypoglycemic range CGM results are too inaccurate to guide in-hospital diabetes therapy.
    Keywords:  continuous glucose monitor; diabetes mellitus; hypoglycemia; inpatient
    DOI:  https://doi.org/10.1177/19322968251412482
This page is being maintained by Thomas Krichel. It was last updated on 2026‒02‒08 at 0:16.