bims-glumda 2026-02-15 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2026–02–15
nine papers selected by
Mott Given

Simultaneous Use of Continuous Glucose Monitoring (CGM) Systems and the Remote Electrical Neuromodulation (REN) Wearable for Patients with Comorbid Diabetes and Migraine: An Interventional Single-Arm Compatibility Study.
Letter: Hypoglycemia Assessed by Continuous Glucose Monitoring: A Proposal to Define the End of a Hypoglycemic Event More Precisely.
Letter to the Editor regarding "Accuracy and Reliability of the Sinocare iCan i3 Continuous Glucose Monitoring System".
Impact of real-time continuous glucose monitoring on glycaemic control in adults with type 2 diabetes: systematic review and meta-analysis.
Future Directions for Diabetic Foot Ulcer Interventions: A Scoping Review of Continuous Glucose Monitoring based Telemedicine.
Diabetes community calls for quality standards for continuous glucose monitoring devices.
The Relationship Between Clinical Profiles, Glycemic Parameters, and Hypoglycemia in Pediatric Patients with Type 1 Diabetes.
Metabolic heterogeneity after laparoscopic sleeve gastrectomy in type 2 diabetes mellitus patients with severe obesity: insights from continuous glucose monitoring, glycemic profiles and quality of life.
AFTS: A patient-agnostic encoder-decoder architecture with directional attention for blood glucose forecasting.

J Clin Med. 2026 Jan 30. pii: 1097. [Epub ahead of print]15(3):

Simultaneous Use of Continuous Glucose Monitoring (CGM) Systems and the Remote Electrical Neuromodulation (REN) Wearable for Patients with Comorbid Diabetes and Migraine: An Interventional Single-Arm Compatibility Study.

Yara Asmar, Alit Stark-Inbar, Maria Carmen Wilson, Katherine Podraza, Christina Treppendahl, Cem Demirci, Richelle deMayo.

  Background/Objectives: Migraine and diabetes mellitus are highly prevalent chronic diseases, and their comorbidity presents management challenges, particularly when wearable medical technologies are used concurrently. Remote electrical neuromodulation (REN; Nerivio®) is an FDA-cleared non-pharmacological migraine therapy, and continuous glucose monitoring (CGM) systems are widely used in diabetes care. However, the safety and compatibility of simultaneous co-use have not yet been evaluated. This technical compatibility study aimed to assess whether REN operation affects CGM performance or interferes with glucose measurement integrity in diabetic adults. Methods: Twenty-one adults with diabetes using Dexcom G6/G7 or FreeStyle Libre 2/3 participated in a single-arm interventional study. During a 45 min session, participants operated the REN and CGM devices simultaneously on their smartphones, and the REN device was paused three times to compare CGM readings between REN ON and RED OFF conditions. The primary outcome was the mean absolute relative difference (MARDREN ON/OFF), evaluated against a prespecified 5% threshold. Statistical analysis included the Wilcoxon test, with subgroup analysis by the CGM device family. Results: The median MARDREN ON/OFF across all participants was 1.61% (IQR 0.84-2.44%), significantly below the 5% threshold (p < 0.001). All participants achieved MARDREN ON/OFF < 5%. Subgroup analyses were consistent: the median MARDREN ON/OFF was 1.70% (IQR 0.90-2.45%) for Dexcom and 1.05% (IQR 0.83-1.50%) for Abbott. No technical interference, Bluetooth disruptions, missed data transmission, or adverse events were observed. Conclusions: Simultaneous use of Nerivio® REN and CGM systems in adults with diabetes is compatible and safe, with no evidence of interference or significant deviations in glucose readings. These findings support the integrated and reliable use of REN and CGM wearables in adults with diabetes managing comorbid conditions.

Keywords:  continuous glucose monitoring; diabetes mellitus; migraine; remote electrical neuromodulation; wearable medical devices

DOI:  https://doi.org/10.3390/jcm15031097
Diabetes Technol Ther. 2026 Feb 11. 15209156261423957

Letter: Hypoglycemia Assessed by Continuous Glucose Monitoring: A Proposal to Define the End of a Hypoglycemic Event More Precisely.

Douglas B Muchmore, Peter Calhoun, Lutz Heinemann.

DOI: https://doi.org/10.1177/15209156261423957
Diabetes Ther. 2026 Feb 14.

Letter to the Editor regarding "Accuracy and Reliability of the Sinocare iCan i3 Continuous Glucose Monitoring System".

Fatih Gürbüz.



Keywords:  Accuracy; Blood Glucose Monitoring; Continuous Glucose Monitoring; Reliability

DOI:  https://doi.org/10.1007/s13300-026-01840-0
Front Endocrinol (Lausanne). 2025 ;16 1761579

Impact of real-time continuous glucose monitoring on glycaemic control in adults with type 2 diabetes: systematic review and meta-analysis.

Xia Lian, Ling Jie Cheng, Claire Jun Yi Teo, Isaac Jun Song Tan, Helen Lim, Liang Shen, Jocelyn Han Shi Chew, Wenru Wang, Rinkoo Dalan.

   Objective: To evaluate the effectiveness of real-time continuous glucose monitoring compared with self-monitoring of blood glucose in adults with type 2 diabetes, focusing on glycaemic control, cardiometabolic outcomes, and patient-centred measures.
Methods: Randomised controlled trials published in English with study intervention period ≥12 weeks, which compared real-time continuous glucose monitoring with self-monitoring of blood glucose in adults with type 2 diabetes were included in this systematic review. Analyses were conducted using Review Manager version 9.6. Risk of bias was evaluated using the Cochrane risk-of-bias tool. The Grading of Recommendations Assessment, Development and Evaluations approach was used to assess certainty of evidence.
Data Sources: The search was conducted across PubMed, CINAHL, Web of Science, the Cochrane Library databases and ClinicalTrials.gov from inception to July 2025.
Results: This systematic review was reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Eleven studies which compared real-time continuous glucose monitoring (n=437) with self-monitoring of blood glucose (n=352) were included. Real-time continuous glucose monitoring use was associated with a significant reduction in HbA1c (mean difference=-0.20%), improved time-in-range (mean difference=7.41%), reduced time-above-range (mean difference=6.93%) and reduced time-below-range (mean difference=0.26%). Glucose variability was significantly lower (mean difference=-1.06%) and users demonstrated greater improvements in readiness for diabetes self-management (standardised mean difference=0.69). No significant differences were observed in cardiometabolic or psychosocial outcomes.
Conclusion: Real-time continuous glucose monitoring improves glycaemic control and self-management capacity compared with self-monitoring of blood glucose in adults with type 2 diabetes. These findings support the integration of real-time continuous glucose monitoring into routine clinical care, particularly for individuals requiring intensive glucose monitoring and tailored self-care support.
Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42025625444.

Keywords:  glycaemic control; real-time continuous glucose monitoring; self-management of diabetes; self-monitoring blood glucose; type 2 diabetes

DOI:  https://doi.org/10.3389/fendo.2025.1761579
Can J Diabetes. 2026 Feb 06. pii: S1499-2671(26)00031-6. [Epub ahead of print]

Future Directions for Diabetic Foot Ulcer Interventions: A Scoping Review of Continuous Glucose Monitoring based Telemedicine.

Clara Bender, Peter Vestergaard, Simon Lebech Cichosz.

   BACKGROUND: Non-adherence to diabetes treatment leads to persistent hyperglycemia, a key driver of non-healing diabetic foot ulcers (DFUs). Continuous glucose monitoring (CGM) and telemedicine have independently improved glycemic control, HbA1c, and time in range. This study reviews the various components of telemedicine and CGM to gain insight that can contribute to future directions for enhancing DFU interventions.
METHOD: a scoping review was conducted in PubMed, Embase, CINAHL, and Scopus.
RESULTS: 16 studies were included. Aggregated, three main implication areas, one with subdivisions were identified: 1) Components in a remote treatment package, a) The telemedicine term, b) The specialized healthcare professional, c) Monitoring health data, and d) Supervision and feedback on monitored data, 2) Improved glycemic control with remote treatment, and 3) Future directions for DFU interventions.
CONCLUSION: Selected components of telemedicine and CGM may be utilized in future DFU interventions but needs to be tested in a future feasibility study.

Keywords:  continuous glucose monitoring; diabetic foot; telemedicine

DOI:  https://doi.org/10.1016/j.jcjd.2026.01.008
Lancet Reg Health Eur. 2026 Mar;62 101598

Diabetes community calls for quality standards for continuous glucose monitoring devices.

Francesco Giorgino, Tadej Battelino, Stefano Del Prato, Rahab Hashim, Sabine E Hofer, Sufyan Hussain, Kasia Karpinska, Tom Melvin, Eric Renard, Campbell Hutton, Jannet Svensson, Bart Torbeyns, Petra Wilson, Chantal Mathieu.

DOI: https://doi.org/10.1016/j.lanepe.2026.101598
J Clin Med. 2026 Jan 30. pii: 1112. [Epub ahead of print]15(3):

The Relationship Between Clinical Profiles, Glycemic Parameters, and Hypoglycemia in Pediatric Patients with Type 1 Diabetes.

Andreea Morar-Stan, Luminița Dobrotă, Anișoara Răduțu, Carmen Daniela Domnariu.

  Background/Objectives: Our objective was to assess the role of clinical and continuous glucose monitoring (CGM) parameters in predicting the risk of hypoglycemia in pediatric patients with type 1 diabetes. Methods: Pediatric patients with type 1 diabetes (n = 71) at the Oradea County Clinical Emergency Hospital, Romania, who underwent CGM during their initial visit and were followed for at least 6 months with in-clinic visits every 3 months were enrolled in this study. Age, body mass index, time in range, the mean daily glucose (MDG) concentration, and the coefficient of variation (%CV) were considered as potential predictors of the risk of hypoglycemia, which was defined as the percentage of time spent below two glycemic thresholds of 3.9 and 3.0 mmol/L, corresponding to mild and clinically significant hypoglycemia, respectively. Results: Among a total of 142 glycemic profiles, the MDG concentration was significantly lower in those with hypoglycemia compared to those without, whereas %CV was significantly higher (p < 0.0001). Regression tree models identified %CV as the dominant variable for both thresholds, whereas classification tree models identified %CV as the dominant variable for clinically significant hypoglycemia and MDG for mild hypoglycemia. In profiles with a %CV of less than 36.15% and an MDG concentration greater than 7.16 mmol/L, the mean percentage of time spent below the 3.9 mmol/L threshold was 4.8%, which is close to that recommended by the American Diabetes Association guidelines. Patients younger than 7 years presented the highest frequency for both mild and clinically significant hypoglycemic episodes. Conclusions: Our study supports %CV and the MDG concentration as key factors in predicting hypoglycemia risk. Minimizing the risk of hypoglycemia in pediatric patients requires a %CV of less than 36%.

Keywords:  glycemic variability; hypoglycemia; mean daily glucose; pediatric population; type 1 diabetes

DOI:  https://doi.org/10.3390/jcm15031112
Acta Diabetol. 2026 Feb 12.

Metabolic heterogeneity after laparoscopic sleeve gastrectomy in type 2 diabetes mellitus patients with severe obesity: insights from continuous glucose monitoring, glycemic profiles and quality of life.

Michał Wysocki, Piotr Małczak, Anna Rajtar, Katarzyna Major, Piotr Major.

   BACKGROUND: Sleeve gastrectomy (SG) induces substantial metabolic improvement in patients with type 2 diabetes (T2DM), but glycemic remission remains heterogeneous. We evaluated metabolic, continuous glucose monitoring (CGM), and quality-of-life (QoL) outcomes after SG according to remission status.
METHODS: Prospective observational study of patients with severe obesity and T2DM undergoing SG that were evaluated preoperatively and at 12 months. Patients were analyzed in T2DM remission (RG) and persistent diabetes (PG) groups.
RESULTS: RG included 15, while PG 18 patients. Weight loss and excess BMI loss were comparable between groups. RG demonstrated greater improvement in fasting glucose and HOMA-IR at follow-up, while HOMA-B decreased significantly in RG but increased in PG, suggesting divergent β-cell adaptation. CGM showed significant postoperative improvement in both groups, with consistently lower mean glucose and fewer hyperglycemic readings in RG. Hypoglycemia indices increased in both groups. QoL improved substantially across BAROS and SF-36 domains, with more pronounced physical improvements; between-group differences in QoL were modest despite distinct metabolic trajectories.
CONCLUSIONS: SG provided meaningful metabolic and quality-of-life benefits, particularly in patients achieving remission, suggesting potential benefits of earlier surgical referral before advanced β-cell deterioration limits the potential for metabolic recovery, and highlighting the value of CGM for individualized postoperative de-escalation of therapy.

Keywords:  Beta-cell function; Continuous glucose monitoring; Diabetes remission; Quality of life; Sleeve gastrectomy; Type 2 diabetes mellitus

DOI:  https://doi.org/10.1007/s00592-026-02668-7
J Biomed Inform. 2026 Feb 11. pii: S1532-0464(26)00022-5. [Epub ahead of print] 104998

AFTS: A patient-agnostic encoder-decoder architecture with directional attention for blood glucose forecasting.

Yu Chen, Henghong Lin, Zhijin Wang, Jinmo Tang, Yaohui Huang, Xiufeng Liu, Senzhen Wu.

  Accurate blood glucose forecasting remains challenging due to inter-patient heterogeneity and complex glycemic dynamics. We present AFTS (Adaptive Feature Time Series), a patient-agnostic deep learning architecture combining a bidirectional LSTM encoder-decoder with cascaded Directional Representation (DR) modules. These modules introduce a specialized axis-wise attention mechanism that processes temporal and feature dimensions separately, designed to disentangle trend evolution from latent feature magnitude. We evaluated AFTS on two real-world CGM datasets (KDD18 and CDD23) against twenty baseline models, including advanced Transformers and RNN variants. Under a rigorous patient-wise 80/20 split, AFTS achieved an MAE of 7.02 mg/dL (KDD18) and 7.39 mg/dL (CDD23) at a 30-minute prediction horizon. The results demonstrate that AFTS is numerically competitive with state-of-the-art architectures while offering a distinct mechanism for hierarchical feature refinement. By isolating the encoder-decoder backbone and DR modules in ablation studies, we confirm that the axis-wise attention mechanism contributes specifically to minimizing prediction error in complex glycemic scenarios. These findings establish AFTS as a robust architectural candidate for patient-agnostic forecasting, effectively balancing the capture of short-term fluctuations and long-term trends.

Keywords:  Adaptive feature time series; Blood glucose; Continuous glucose monitoring; Deep learning; Diabetes management; Patient-agnostic; Prediction

DOI:  https://doi.org/10.1016/j.jbi.2026.104998