bims-glumda 2025-08-03 papers

bims-glumda

Biomed News

on CGM data in management of diabetes

Issue of 2025–08–03
sixteen papers selected by
Mott Given

Letter: Beyond Accuracy: Clinical Considerations for Personal Continuous Glucose Monitoring Use During Hospitalization.
Real-Time Continuous Glucose Monitoring in Pregnancies With Gestational Diabetes: A Randomized Controlled Trial.
Continuous glucose monitoring in gestational diabetes mellitus: hope or hype?
Continuous Glucose Monitoring Metrics and Continuous Glucose Monitoring-Based Hypoglycemia, Including Duration, in Individuals with Type 1 Diabetes Switching to Once-Weekly Insulin Icodec: A Post Hoc Evaluation of ONWARDS 6.
Satisfaction with continuous glucose monitoring and diabetes care among hospitalised patients with type 2 diabetes managed by inpatient diabetes teams.
Continuous glucose monitoring as a tool for psychological support - exploring metabolic control and psychological well-being after initial cgm implementation in adults with type 1 diabetes.
Agreement Between Fingerstick Blood Glucose and Continuous Glucose Monitor Measures Among Long-Term Care Facility Residents.
A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.
Predicting dysglycaemia in individuals with gestational diabetes immediately postpartum using continuous glucose monitoring (PREDISPOSE) in a multicentre prospective cohort study in Canada: a study protocol.
Time in Tight Range (TITR) stratified by Time Below Range (TBR) in a cohort of patients with type 1 Diabetes Mellitus and Multiple Daily Injections. A real-life study.
Associations of time in range and glycemic risk index with insulin resistance and diabetic kidney disease in patients with type 2 diabetes.
The interplay between psychological well-being, diabetes-related distress, and glycemic control: A continuous glucose monitoring analysis from a population of adolescents with type 1 diabetes.
Associations of diet composition and quality with continuous glucose monitor-derived glycemic metrics in a community-based cohort.
Mapping Barriers and Interventions to Diabetes Self-Management in Latino Youth: A Scoping Review.
Noninvasive On-Skin Biosensors for Monitoring Diabetes Mellitus.
From Control to Cure: Insights into the Synergy of Glycemic and Antibiotic Management in Modulating the Severity and Outcomes of Diabetic Foot Ulcers.

Diabetes Technol Ther. 2025 Jul 23.

Letter: Beyond Accuracy: Clinical Considerations for Personal Continuous Glucose Monitoring Use During Hospitalization.

Yadi Li, Zheng Wei, Jianlong Zhou.

DOI: https://doi.org/10.1177/15209156251362492
Diabetes Care. 2025 Jul 29. pii: dc250115. [Epub ahead of print]

Real-Time Continuous Glucose Monitoring in Pregnancies With Gestational Diabetes: A Randomized Controlled Trial.

Amy M Valent, Michaela Rickert, Christian Huerta Pagan, Lucy Ward, Emily Dunn, Monica Rincon.

OBJECTIVE: To compare the efficacy of real-time continuous glucose monitoring (CGM; intervention) with capillary blood glucose (CBG) monitoring (control) alone to achieve greater percent glucose time in range (%TIR) among pregnant individuals diagnosed gestational diabetes mellitus (GDM).
RESEARCH DESIGN AND METHODS: This was an open-label, single-center, randomized controlled trial of pregnant individuals with GDM and ≥20 weeks' gestation. Subjects were randomly assigned (2:1) to use real-time CGM plus adjunctive CBG versus CBG alone for glucose monitoring. The intervention group was instructed on the continuous use of the Dexcom G6 CGM system from enrollment to admission for delivery. The control group used CBG monitoring four times per day underwent blinded CGM approximately every 20 days throughout the study period. The primary outcome was the CGM %TIR defined as 60-140 mg/dL (3.3-7.8 mmol/L) from study enrollment until hospital admission for delivery.
RESULTS: A total of 111 participants were enrolled between February 2021 and June 2023 (n = 74 in intervention group; n = 37 in control group) with no statistical differences in demographic characteristics between the groups. The CGM group had significantly higher %TIR ±SD (93 ± 6 min vs. 88 ± 14 min at 60-140 mg/dL; P = 0.027). Among key secondary CGM metric outcomes, the intervention group had significantly higher daytime TIR with lower 24-h and daytime mean glucose and percent time >140 mg/dL compared with the control group.
CONCLUSIONS: We demonstrated a significantly higher %TIR using real-time CGM compared with CBG glucose monitoring among pregnant people with GDM. Studies are needed to determine if achieving lower CGM glucose levels can improve perinatal and neonatal outcomes.

DOI: https://doi.org/10.2337/dc25-0115
Diabetes Res Clin Pract. 2025 Jul 29. pii: S0168-8227(25)00403-6. [Epub ahead of print] 112389

Continuous glucose monitoring in gestational diabetes mellitus: hope or hype?

Thora Y Chai, Samuel Leathwick, Mukesh M Agarwal, David B Sacks, David Simmons.

  The screening, diagnosis and management of gestational diabetes mellitus (GDM) have evolved over time. Similarly, continuous glucose monitoring (CGM) has advanced in parallel: from intermittent to real-time monitoring, shorter to longer wear-time and poor to increased precision. Thus, CGM has replaced multiple glucose fingerstick testing in type 1 diabetes mellitus (T1D), including pregnant women with T1D. Despite its advantages, the uptake of CGM in women with GDM remains limited. Doubts persist over its cost, accuracy and optimal utilisation, besides there is paucity of evidence supporting its use in both diagnosis and management. This review summarises the current clinical evidence, benefits and limitations of using CGM in pregnant women with GDM. Like T1D, only larger pointed studies and randomised controlled trials will clarify the value of CGM in GDM.

Keywords:  Continuous glucose monitoring; Diagnosis; Early GDM; Early pregnancy; Gestational diabetes mellitus; Glucose thresholds; HbA1c; Large-for-gestational-age; Late GDM; Oral glucose tolerance test; Perinatal complications; Pregnancy outcomes; Prognosis; Small-for-gestational-age

DOI:  https://doi.org/10.1016/j.diabres.2025.112389
Diabetes Technol Ther. 2025 Jul 18.

Continuous Glucose Monitoring Metrics and Continuous Glucose Monitoring-Based Hypoglycemia, Including Duration, in Individuals with Type 1 Diabetes Switching to Once-Weekly Insulin Icodec: A Post Hoc Evaluation of ONWARDS 6.

Thomas Danne, Susanne Engberg, Concetta Irace, Maiken Ina Siegismund Kjaersgaard, David C Klonoff, Chantal Mathieu, Sara Kehlet Watt, David Russell-Jones.

  Background: Post hoc evaluation of ONWARDS 6 assessed continuous glucose monitoring (CGM) metrics and CGM-based hypoglycemia with once-weekly insulin icodec (icodec) and once-daily insulin degludec (degludec) in adults with type 1 diabetes. Methods: Open CGM data were collected throughout ONWARDS 6. During weeks 0-4, 22-26, and 48-52, time in range (TIR; 3.9-10.0 mmol/L), time above range (TAR; >10.0 mmol/L), and time below range (TBR; <3.9 and <3.0 mmol/L) were assessed by treatment day after icodec injection or degludec titration. Rates of CGM-based clinically significant hypoglycemic episodes (<3.0 mmol/L for ≥15 consecutive min) and durations of CGM-based hypoglycemic episodes (<3.9 mmol/L) and CGM-based periods <3.0 mmol/L were reported (baseline to weeks 26 and 57). Results: Although rates of overall CGM-based clinically significant hypoglycemia were statistically significantly higher with icodec than degludec from baseline to week 26 and week 57, estimated rate ratios (icodec/degludec) for CGM-based clinically significant hypoglycemic episodes were lower than those estimated from self-measured blood glucose (SMBG) data from baseline to week 26 (1.38 vs. 1.88) and to week 57 (1.28 vs. 1.79). Observed percentage of TIR was highest on days 2-4 after icodec injection with a concomitant reduction in TAR and an increase in TBR. Median duration of CGM-based hypoglycemic episodes was comparable between treatment arms from baseline to week 26 (icodec: 35 min; degludec: 30 min) and to week 57 (35 min for both treatments). Median duration of CGM-based periods <3.0 mmol/L was the same for both treatments at week 26 and week 57 (25 min). Conclusion: In adults with type 1 diabetes, estimated rate ratios for CGM-based clinically significant hypoglycemia were lower than those estimated from SMBG data, although still favoring degludec with estimated rate ratios of 1.28-1.38. CGM metrics varied by treatment day after icodec injection, but median duration of CGM-based hypoglycemia was comparable between treatment arms.

Keywords:  clinical science; human; hypoglycemia; insulin therapy

DOI:  https://doi.org/10.1177/15209156251359319
Diabet Med. 2025 Jul 28. e70114

Satisfaction with continuous glucose monitoring and diabetes care among hospitalised patients with type 2 diabetes managed by inpatient diabetes teams.

Mikkel Thor Olsen, Malene Elbæk Vikner, Signe Hjejle Jensen, Louise Mathorne Rasmussen, Carina Kirstine Klarskov, Birgitte Lindegaard, Jonas Askø Andersen, Hans Gottlieb, Suzanne Lunding, Kirsten Nørgaard, Ulrik Pedersen-Bjergaard, Katrine Bagge Hansen, Peter Lommer Kristensen.

   AIMS: Continuous glucose monitoring (CGM) is increasingly recognised as a valuable tool in the hospital setting, with evidence supporting its accuracy and potential for improving glycaemic and clinical outcomes. However, patient perspectives on the use of CGM in the hospital setting remain underexplored. This study investigates patient satisfaction with CGM during hospitalisation.
METHODS: This analysis included 166 hospitalised non-intensive care unit (non-ICU) patients with type 2 diabetes from the DIAbetes TEam and Cgm (DIATEC) trial. Participants were randomised to either point-of-care (POC) glucose testing (n = 82) or CGM (n = 84) for glucose monitoring during their hospital stay and were managed by inpatient diabetes teams. At discharge, patients completed a survey developed for this specific study, assessing their satisfaction with the diabetes management, with a focus on glucose monitoring methods.
RESULTS: Overall satisfaction with the diabetes treatment during hospitalisation was similar in both groups, with 77% of patients in each group reporting being satisfied or very satisfied (p = 0.188). Regarding glucose assessment, 75% in the CGM group preferred CGM over POC glucose testing (p < 0.001). In the CGM group, 95% felt comfortable with CGM being the primary method for glucose management (p < 0.001). Approximately 5% reported discomfort from wearing the CGM, mainly due to itching from the sensor. Most patients (95%) in both groups were comfortable with their diabetes management being handled by inpatient diabetes teams (p < 0.001).
CONCLUSIONS: Satisfaction with CGM among non-ICU patients with type 2 diabetes managed by inpatient diabetes teams was high, highlighting CGM's potential to enhance patient care in the hospital setting.

Keywords:  continuous glucose monitoring; hospital; inpatient; inpatient diabetes team; patient perspective

DOI:  https://doi.org/10.1111/dme.70114
Psychiatr Pol. 2025 Jul 23. pii: 205875. [Epub ahead of print] 1-19

Continuous glucose monitoring as a tool for psychological support - exploring metabolic control and psychological well-being after initial cgm implementation in adults with type 1 diabetes.

Bartłomiej Matejko, Anna Drynda, Katarzyna Cyranka, Anna Juza, Katarzyna Nabrdalik, Hanna Kwiendacz, Paulina Szromek-Białek, Alina Strzała-Kłeczek, Aleksandra Araszkiewicz, Janusz Gumprecht, Dorota Zozulińska-Ziółkiewicz, Maciej Małecki, Tomasz Klupa.

   OBJECTIVES: The initiation of reimbursement for intermittently scanned continuous glucose monitoring (isCGM)/ continuous glucose monitoring (CGM) for those 26 and older could greatly benefit people with type 1 diabetes (PwT1D). The aim of the study was to assess changes in quality of life, metabolic control, fear of hypoglycemia and selected psychological parameters after 3 months of implementation of the isCGM/CGM in PwT1D aged 26 and above.
METHODS: The study involved 57 PwT1D from five diabetology centers. To be included in the study, each participant had to be at least 26 years old, have a minimum of two years of diabetes history. Participants completed a set of validated questionnaires including the FSH-II, DDS, PSS10, DTSQs, WHO-5, PAID, DBQ, and a sociodemographic survey. They also downloaded pump/glucometer data and underwent HbA1c measurement at the beginning and again at the end of the study.
RESULTS: PwT1D reported higher treatment satisfaction measured by DTSQs. Well-being assessment according to WHO-5 was also higher, and the level of diabetes burnout measured by DBQ, fear of hypoglycemia assessed by HFS-II significantly decreased. Diabetic distress measured by means of total score of DDS lowered. Participants scored also lower on PAID upon follow up. The HbA1c level after three months of using the CGM system was significantly lower.
CONCLUSIONS: The use of isCGM/CGM, even during relatively short observation, leads to improved quality of life, reduced fear of hypoglycemia and diabetes burnout, and lower HbA1c levels in PwT1D over the age of 26 who were naïve to this technology.

Keywords:  Quality of Life; Type 1 diabetes; continuous glucose monitoring; intermittently scanned CGM; reimbursement

DOI:  https://doi.org/10.12740/PP/OnlineFirst/205875
J Am Geriatr Soc. 2025 Aug 02.

Agreement Between Fingerstick Blood Glucose and Continuous Glucose Monitor Measures Among Long-Term Care Facility Residents.

Marzan A Khan, Medha N Munshi, Christine Slyne, Nina R Joyce, Andrew R Zullo.

   BACKGROUND: Long-term care facility (LTCF) residents with diabetes are at high risk of hypoglycemia. Continuous glucose monitoring (CGM), which measures interstitial glucose at 5-min intervals over 10-14 days, and fingerstick blood glucose (FBG) which analyzes glucose from a drop of blood, are both used to monitor glucose levels. Observational studies using electronic health record (EHR) data containing FBG measures could help to identify ways to reduce hypoglycemia risk. We first need to understand the validity of such data. Our objective was to compare EHR-based FBG measures against reference-standard CGM measures of hypoglycemia.
METHODS: We studied two cohorts of residents with diabetes in parallel. In Cohort 1, we analyzed linked CGM and Long-Term Care Data Cooperative EHR-based FBG data collected in 2023. In Cohort 2, we analyzed linked CGM and EHR-based FBG data obtained directly from LTCFs between 2022 and 2023. We defined hypoglycemia as glucose < 70 mg/dL and assessed the sensitivity and specificity of FBG versus CGM measures to detect hypoglycemia. The unit of analysis was each pair of contemporaneous FBG-CGM measures.
RESULTS: In Cohort 1, two White female residents with a mean (standard deviation [SD]) age of 81 [12.7] years generated 25 daily hypoglycemia measurements. The sensitivity and specificity were 14% and 100%, respectively, for FBG-measured hypoglycemia. Cohort 2 included 40 residents (mean [SD] age 68 [11] years, 45% females, 60% White race) who generated 425 daily measurements of hypoglycemia. The sensitivity and specificity were 13% and 99%, respectively.
CONCLUSION: EHR FBG measures of hypoglycemia had high specificity but failed to identify four out of every five hypoglycemic events among LTCF residents. Researchers and healthcare providers should assume hypoglycemia is measured with substantial errors in EHRs and account for this in their research and clinical practice.

Keywords:  continuous glucose monitoring; diabetes; electronic health records; fingerstick blood glucose; long‐term care facility

DOI:  https://doi.org/10.1111/jgs.70024
Sci Rep. 2025 Jul 29. 15(1): 27625

A multimodal deep learning architecture for predicting interstitial glucose for effective type 2 diabetes management.

Gatekeeper Consortium

  The accurate prediction of blood glucose is critical for the effective management of diabetes. Modern continuous glucose monitoring (CGM) technology enables real-time acquisition of interstitial glucose concentrations, which can be calibrated against blood glucose measurements. However, a key challenge in the effective management of type 2 diabetes lies in forecasting critical events driven by glucose variability. While recent advances in deep learning enable modeling of temporal patterns in glucose fluctuations, most of the existing methods rely on unimodal inputs and fail to account for individual physiological differences that influence interstitial glucose dynamics. These limitations highlight the need for multimodal approaches that integrate additional personalized physiological information. One of the primary reasons for multimodal approaches not being widely studied in this field is the bottleneck associated with the availability of subjects' health records. In this paper, we propose a multimodal approach trained on sequences of CGM values and enriched with physiological context derived from health records of 40 individuals with type 2 diabetes. The CGM time series were processed using a stacked Convolutional Neural Network (CNN) and a Bidirectional Long Short-Term Memory (BiLSTM) network followed by an attention mechanism. The BiLSTM learned long-term temporal dependencies, while the CNN captured local sequential features. Physiological heterogeneity was incorporated through a separate pipeline of neural networks that processed baseline health records and was later fused with the CGM modeling stream. To validate our model, we utilized CGM values of 30 min sampled with a moving window of 5 min to predict the CGM values with a prediction horizon of (a) 15 min, (b) 30 min, and (c) 60 min. We achieved the multimodal architecture prediction results with Mean Absolute Point Error (MAPE) between 14 and 24 mg/dL, 19-22 mg/dL, 25-26 mg/dL in case of Menarini sensor and 6-11 mg/dL, 9-14 mg/dL, 12-18 mg/dL in case of Abbot sensor for 15, 30 and 60 min prediction horizon respectively. The results suggested that the proposed multimodal model achieved higher prediction accuracy compared to unimodal approaches; with upto 96.7% prediction accuracy; supporting its potential as a generalizable solution for interstitial glucose prediction and personalized management in the type 2 diabetes population.

Keywords:  Deep learning; Interstitial glucose prediction; Multimodal AI

DOI:  https://doi.org/10.1038/s41598-025-07272-3
BMJ Open. 2025 Jul 30. 15(7): e103771

Predicting dysglycaemia in individuals with gestational diabetes immediately postpartum using continuous glucose monitoring (PREDISPOSE) in a multicentre prospective cohort study in Canada: a study protocol.

Sarah M Sigurdson, Katherine J Bernier, Lois E Donovan, Denice S Feig, Patricia Lemieux, Christy Pylypjuk, Garry X Shen, Depeng Jiang, Kara Nerenberg, Michelle M Chrisp, Pamela M Katz, Jamie L Benham, Jennifer M Yamamoto.

   INTRODUCTION: Gestational diabetes is a common metabolic disorder in pregnancy which identifies a substantial increased risk of future diabetes. Despite this risk, many individuals are not screened for dysglycaemia in the postpartum period. Continuous glucose monitoring (CGM) is an evolving technology that provides details of an individual's glucose levels throughout the day; however, it has not yet been evaluated as a screening tool for postpartum dysglycaemia. To address this gap, this prospective cohort study will examine the use of CGM in the early postpartum period to predict the risk of maternal dysglycaemia after delivery.
METHODS AND ANALYSIS: The Predicting Dysglycaemia in Individuals with Gestational Diabetes Immediately Postpartum using CGM (PREDISPOSE) study is a prospective cohort study designed to assess the ability of a CGM device (Freestyle Libre 2) worn in the postpartum period to detect persistent dysglycaemia in individuals with gestational diabetes. The study will recruit 240 individuals with gestational diabetes. Each participant will wear the CGM immediately postpartum and before attending routine postpartum diabetes screening, consisting of a 75-gram oral glucose tolerance test (OGTT) and related blood work (haemoglobin A1c (HbA1c), complete blood count and lipid profile). The primary outcome is the accuracy of the area under the curve for all glucose measurements from the first CGM wear to detect postpartum dysglycaemia. We will perform sensitivity and specificity analyses to determine optimal CGM cut-offs to diagnose diabetes or prediabetes. Secondary outcomes include the incidence of postpartum dysglycaemia (based on 75-gram OGTT and/or HbA1c), incidence of postpartum dyslipidaemia, patient acceptability of CGM testing, data variability from CGM and cardiometabolic health outcomes diagnosed in years one, two and five after delivery.
ETHICS AND DISSEMINATION: All participating sites have received ethics approval of the current protocol and have started recruitment of participants to the study. The ethics boards that approved this study are the Biomedical Research Ethics Board at the University of Manitoba, the Conjoint Health Research Ethics Board at the University of Calgary, the Mount Sinai Hospital Research Ethics Board at Mount Sinai Hospital and the Comité d'éthique de la Recherche at Université Laval. Study results will be disseminated through conference presentations and publication in a peer-reviewed journal, regardless of study findings.
TRIAL REGISTRATION NUMBER: NCT04972955. Registration date: 28 June 2021.

Keywords:  Diabetes Mellitus, Type 2; Diabetes in pregnancy; Pregnancy; Wearable Electronic Devices

DOI:  https://doi.org/10.1136/bmjopen-2025-103771
Acta Diabetol. 2025 Jul 30.

Time in Tight Range (TITR) stratified by Time Below Range (TBR) in a cohort of patients with type 1 Diabetes Mellitus and Multiple Daily Injections. A real-life study.

Sandra Herranz-Antolín, Sofía Ramos-Garrido, Verónica Esteban-Monge, Clara Coton-Batres, María Covadonga López-Virgos, Silvia Lallena-Pérez, Miguel Torralba.

   OBJETIVE: To analyze the Time in Tight Range (TITR) (70-140 mg/dL) and assess their possible differences according to Time Below Range (TBR) in a cohort of type 1 diabetes mellitus people with Múltiple Daily Injections.
PATIENTS AND METHODS: 355 adult users of Continuous Glucose Monitoring (CGM) with at least a HbA1c during the period October 1, 2023-October 1, 2024, and glucose data in the 90 days prior were included.
RESULTS: Age 46.9 years (SD 13.6); 57.2% male; time of evolution 21.6 years (SD 12.6). Mean TITR was 38.4% (SD 14.6) and 20.3% had a TITR ≥ 50%. The correlation TITR-TIR was strong (β = 0.83; CI 95% 0.8-0.87; R [2] Adjusted 0.89; p < 0.001) and varied according to TBR [TBR < 4% group (β = 0.81; CI 95% 0.78 to 0.85; R [2] Adjusted 0.9; p < 0.001) vs. TBR ≥ 4% (β = 0.9; CI 95% 0.86 to 0.94; R [2] Adjusted 0.93; p < 0.001)]. The variables independently associated with TITR in patient with TBR < 4% were HbA1c (β = -9.58; CI 95% -10.88 to -8.29; p < 0.001) and Coefficient of Variation (CV) (β = -0.38; CI 95% -0.66 to -0.11; p = 0.007). However, in those with TBR ≥ 4% were male gender (β = 2.86; CI 95% 0.26 to 5.45; p = 0.031), HbA1c (β = -7.53; CI 95% -9.1 to -5.96; p < 0.001) and CV (β = -0.69; CI 95% -1.01 to -0.37; p < 0.001).
CONCLUSIONS: The correlation between TITR and TIR and the factors that were independently associated with TITR differ depending on the TBR.

Keywords:  Continuous Glucose Monitoring; Multiple Daily Injections; Time in Range; Time in Tight Range

DOI:  https://doi.org/10.1007/s00592-025-02563-7
J Diabetes Complications. 2025 Jul 24. pii: S1056-8727(25)00193-X. [Epub ahead of print]39(10): 109140

Associations of time in range and glycemic risk index with insulin resistance and diabetic kidney disease in patients with type 2 diabetes.

Zhe Yang, Baozhen Zheng, Guojing Luo, Xiaoyan Xin, Hongyun Lu.

   AIMS: Effective glycemic control is essential for preventing complications and improving quality of life in patients with type 2 diabetes mellitus (T2DM). Identifying reliable glycemic indicators for the assessment of islet function and renal complications remains a major challenge in diabetology. Time in Range (TIR) and Glycemia Risk Index (GRI), two continuous glucose monitoring (CGM)-based metrics, have recently emerged as potential tools for assessing glycemic control beyond HbA1c. This study aims to assess the predictive value of TIR and GRI for islet function impairment and diabetic kidney disease (DKD) in patients with T2DM.
METHODS: A retrospective analysis of a total of 422 patients with T2DM was performed, who were admitted to Zhuhai People's Hospital between January 2021 and December 2022. Continuous glucose monitoring (CGM) data were collected to get TIR and GRI. Additionally, the C-peptide release, random urine biochemistry analysis, and C-reactive protein (CRP) were obtained to calculate HOMA-IR, HOMA-β, ISIstumvoll index, Stumvoll 1-phase and 2-phase index, and insulin resistance. The Urinary Albumin/Creatinine Ratio (UACR) was ascertained as a diagnostic marker of DKD.
RESULTS: TIR and GRI demonstrated significant correlations with HOMA-IR, HOMA-β, and UACR; however, CRP exhibited a limited correlation with HOMA-IR and UACR. After adjustment for potential confounding factors, the odds ratios (ORs) for pancreatic β-cell function were: TIR 0.174 (95 % CI 0.051-0.592), GRI 1.010 (95 % CI 1.001-1.020). For DKD: TIR 0.182 (95 % CI 0.052-0.639), GRI 1.017 (95 % CI 1.007-1.027). TIR levels of 71 %-85 % and 41 %-70 % were associated with a 4.763-fold and 5.079-fold higher risk of insulin resistance, respectively, compared with TIR > 85 %. Similarly, GRI levels of 21-30, 31-45, and 46-100 were associated with 2.553-fold, 2.597-fold, and 3.394-fold increases in insulin resistance risk compared with GRI ≤20. Despite excluding CRP, TIR and GRI differences in DKD and islet function were significant (P < 0.05). In the regression analysis of DKD and islet function, excluding the CRP, TIR and GRI groups, the differences remained statistically significant (P < 0.05).
CONCLUSION: TIR was identified as a protective factor for pancreatic β-cell function, while GRI was associated with an increased risk of dysfunction. Furthermore, longer disease duration, higher HbA1c, elevated BMI, high GRI, and low TIR were associated with increased insulin resistance. A higher GRI and lower TIR also contributed to an elevated risk of DKD.

Keywords:  Diabetic kidney disease; Glycemia risk index; Insulin resistance; Pancreatic β-cell function; Time in range

DOI:  https://doi.org/10.1016/j.jdiacomp.2025.109140
J Diabetes Complications. 2025 Jul 26. pii: S1056-8727(25)00195-3. [Epub ahead of print]39(10): 109142

The interplay between psychological well-being, diabetes-related distress, and glycemic control: A continuous glucose monitoring analysis from a population of adolescents with type 1 diabetes.

Bruno Bombaci, Stefano Passanisi, Alessandro Longo, Sara Aramnejad, Federica Rigano, Maria Cristina Marzà, Tania Formica, Maria Pecoraro, Fortunato Lombardo, Giuseppina Salzano.

   AIMS: This study aims to explore the relationships between glucose control, psychological well-being, and diabetes-related distress in a population of adolescents with T1D.
METHODS: We conducted a cross-sectional study on adolescents with T1D attending a Pediatric Diabetes Unit. Demographic, clinical, and glycemic data were collected, including continuous glucose monitoring (CGM) metrics. Psychological well-being was assessed using the PERMA-Profiler, while diabetes-related distress was measured using the Problem Areas in Diabetes-Teen Version (PAID-T) questionnaire.
RESULTS: Among 133 enrolled adolescents, those with HbA1c ≤ 7 % exhibited significantly higher well-being scores (p = 0.007) and lower distress scores (p = 0.035). Higher time in range was positively associated with well-being (p = 0.002), while glycemic variability negatively impacted psychological outcomes (p = 0.023). Female sex (p = 0.021), longer disease duration (p = 0.022), and the absence of insulin pump therapy (p = 0.032) were significantly associated to higher diabetes-related distress.
CONCLUSIONS: Glycemic control is closely related to psychological well-being of adolescents living with T1D. The adoption of diabetes technologies may play a crucial role in reducing diabetes-related distress. Future longitudinal studies should investigate the impact of psychological interventions on CGM outcomes and overall quality of life in adolescents with T1D.

Keywords:  Adolescence; Glucose metrics; Glycated hemoglobin; PAID-teen; Pediatrics; Time in range

DOI:  https://doi.org/10.1016/j.jdiacomp.2025.109142
Am J Clin Nutr. 2025 Jul 30. pii: S0002-9165(25)00443-5. [Epub ahead of print]

Associations of diet composition and quality with continuous glucose monitor-derived glycemic metrics in a community-based cohort.

Bahar Bakhshi, Naznin Sultana, Honghuang Lin, David Fei, Valeria Vallejo, Abigail Gatanti, Devin W Steenkamp, Joanne M Murabito, Nicola M McKeown, Maura E Walker, Nicole L Spartano.

   BACKGROUND: Continuous glucose monitors (CGM) offer real-time assessment of glucose levels, providing an opportunity to understand the determinants of glycemic variability.
OBJECTIVES: We aimed to cross-sectionally evaluate the associations between carbohydrate substitution, indices of diet and carbohydrate quality with CGM-derived measures in individuals without diabetes.
METHODS: Participants from the Framingham Heart Study, with ≥3 days of CGM data and ≥2 days of dietary records, were included in this analysis. CGM-derived glycemic traits were calculated using the "cgmanalysis" R package. Multivariable linear regression models were used to derive β (SE) from the relationships of carbohydrates (% energy intake (EI)), carbohydrate quality (carb-to-fiber ratio), and indices of diet quality (healthy eating index (HEI), alternate healthy eating index (AHEI), dietary approaches to stop hypertension (DASH) and alternate Mediterranean diet score (aMED)) with CGM-derived measures among all participants and stratified by glycemic status. Least square means were estimated to visualize adjusted group differences of percent time spent above 140 mg/dL across quartiles of diet and carbohydrate quality metrics.
RESULTS: We included 677 individuals in this analysis (56.9% with normoglycemia, 59.4% female, mean age 60.1y, mean glucose 117.7mg/dL). Overall, higher diet and carbohydrate quality were associated with favorable CGM-derived measures. Replacing 5% EI from protein with the equivalent from carbohydrate was associated with 0.97mg/dL higher CGM mean glucose (SE=0.47; p=0.04). The associations of diet quality with glycemic variability were typically more pronounced among those with normoglycemia, but for those with prediabetes, consuming a diet with >1g fiber for every ∼9g carbohydrates was associated with 7-10% lower time spent above 140mg/dL compared to higher carb-to-fiber ratios (p-trend<0.001).
CONCLUSION: Our findings demonstrate that carbohydrate intake and quality, in addition to overall diet quality, is associated with dynamic fluctuations in glucose levels. Future prospective analysis should examine whether glycemic variability mediates the association between diet and incident diabetes.

Keywords:  Continuous glucose monitoring; carbohydrate quality; diet quality; glycemic variability

DOI:  https://doi.org/10.1016/j.ajcnut.2025.07.026
Children (Basel). 2025 Jul 03. pii: 882. [Epub ahead of print]12(7):

Mapping Barriers and Interventions to Diabetes Self-Management in Latino Youth: A Scoping Review.

Milena de Lucca, Megan Visser, Tatiane Geralda André, Sisi Namoc Leturia, Lucila Castanheira Nascimento, Rebecca Ortiz La Banca Barber.

  Background/Objectives: Effective diabetes self-management is critical for glycemic management and well-being, yet Latino youth face unique cultural and socioeconomic barriers that are insufficiently explored in the literature. This review mapped existing evidence on diabetes self-management for Latino youth. Methods: Searches were conducted in PubMed, CINAHL, SCOPUS, Web of Science, LILACS, ERIC, and The Cochrane Library, using the gray literature and reference lists, in September 2024, following JBI guidelines. The included studies were qualitative, quantitative, and mixed-methods studies and reviews on diabetes self-management for Latinos aged 0-30 with type 1 or 2 diabetes. Studies including participants over 30 or with gestational diabetes were excluded. Two reviewers independently extracted data using a standardized table and analyzed findings using the Association of Diabetes Care & Education Specialists framework (ADCES7) for self-care behaviors: healthy eating, being active, monitoring, taking medication, problem-solving, reducing risks, and healthy coping. Results: Forty-five studies (forty from the United States) were included from 860 citations. The findings highlighted challenges in adopting diabetes-friendly diets, including cultural preferences, food insecurity, and limited resources. Physical activity improved glycemic control but was hindered by family and school obligations. Continuous glucose monitoring (CGM) enhanced outcomes, though economic barriers limited access. Family-centered education improved medication adherence, while family support strengthened problem-solving. CGMs and insulin pumps reduced complications, and culturally adapted psychological support enhanced emotional well-being and glycemic management. Conclusions: This review underscores persistent disparities in diabetes self-management among Latino youth. While the study designs and settings were heterogeneous, the findings highlight the need for culturally tailored, family-centered interventions that address structural barriers and psychosocial needs to improve care.

Keywords:  Latino health; adolescent; children; diabetes self-management education and support; pediatric diabetes; type 1 diabetes mellitus; type 2 diabetes mellitus

DOI:  https://doi.org/10.3390/children12070882
Nanomicro Lett. 2025 Jul 31. 18(1): 16

Noninvasive On-Skin Biosensors for Monitoring Diabetes Mellitus.

Ali Sedighi, Tianyu Kou, Hui Huang, Yi Li.

  Diabetes mellitus represents a major global health issue, driving the need for noninvasive alternatives to traditional blood glucose monitoring methods. Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers, providing innovative solutions for diabetes diagnosis and monitoring. This review comprehensively discusses the current developments in noninvasive wearable biosensors, emphasizing simultaneous detection of biochemical biomarkers (such as glucose, cortisol, lactate, branched-chain amino acids, and cytokines) and physiological signals (including heart rate, blood pressure, and sweat rate) for accurate, personalized diabetes management. We explore innovations in multimodal sensor design, materials science, biorecognition elements, and integration techniques, highlighting the importance of advanced data analytics, artificial intelligence-driven predictive algorithms, and closed-loop therapeutic systems. Additionally, the review addresses ongoing challenges in biomarker validation, sensor stability, user compliance, data privacy, and regulatory considerations. A holistic, multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.

Keywords:  Diabetes monitoring; Glucose biosensors; Multimodal sensors; Sweat biomarkers; Wearable biosensors

DOI:  https://doi.org/10.1007/s40820-025-01843-9
Int J Mol Sci. 2025 Jul 18. pii: 6909. [Epub ahead of print]26(14):

From Control to Cure: Insights into the Synergy of Glycemic and Antibiotic Management in Modulating the Severity and Outcomes of Diabetic Foot Ulcers.

Idris Ajibola Omotosho, Noorasyikin Shamsuddin, Hasniza Zaman Huri, Wei Lim Chong, Inayat Ur Rehman.

  Diabetic foot ulcers (DFUs), which affect approximately 15% of individuals with diabetes mellitus (DM), result from complex molecular disturbances involving chronic hyperglycemia, immune dysfunction, and infection. At the molecular level, chronic hyperglycemia promotes the formation of advanced glycation end products (AGEs), activates the AGE-RAGE-NF-κB axis, increases oxidative stress, and impairs macrophage polarization from the pro-inflammatory M1 to the reparative M2 phenotype, collectively disrupting normal wound healing processes. The local wound environment is further worsened by antibiotic-resistant polymicrobial infections, which sustain inflammatory signaling and promote extracellular matrix degradation. The rising threat of antimicrobial resistance complicates infection management even further. Recent studies emphasize that optimal glycemic control using antihyperglycemic agents such as metformin, Glucagon-like Peptide 1 receptor agonists (GLP-1 receptor agonists), and Dipeptidyl Peptidase 4 enzyme inhibitors (DPP-4 inhibitors) improves overall metabolic balance. These agents also influence angiogenesis, inflammation, and tissue regeneration through pathways including AMP-activated protein kinase (AMPK), mechanistic target of rapamycin (mTOR), and vascular endothelial growth factor (VEGF) signaling. Evidence indicates that maintaining glycemic stability through continuous glucose monitoring (CGM) and adherence to antihyperglycemic treatment enhances antibiotic effectiveness by improving immune cell function and reducing bacterial virulence. This review consolidates current molecular evidence on the combined effects of glycemic and antibiotic therapies in DFUs. It advocates for an integrated approach that addresses both metabolic and microbial factors to restore wound homeostasis and minimize the risk of severe outcomes such as amputation.

Keywords:  advanced glycation end products (AGEs); antibiotic therapy; antihyperglycemic agents; diabetic foot ulcer; glycemic control; macrophage polarization (M1/M2 Transition); reactive oxygen species (ROS)

DOI:  https://doi.org/10.3390/ijms26146909