bims-glumda Biomed News
on CGM data in management of diabetes
Issue of 2025–05–25
sixteen papers selected by
Mott Given
  1. Minimum requirements for continuous glucose monitors: What does it mean?
  2. Continuous Glucose Monitoring for Prediabetes - Roles, Evidence, and Gaps.
  3. Comparator Value Pairing Impacts Reported Continuous Glucose Monitoring System Accuracy.
  4. Continuous glucose monitoring during intravenous insulin infusion treatment: Assessing accuracy to enable future clinical utility.
  5. Heterogeneity of continuous glucose monitoring features and their clinical associations in a type 2 diabetes population.
  6. Imputation Model for Glucose Values Above the Upper Detection Limit for Continuous Glucose Monitors.
  7. Glycemia risk index (GRI): a metric designed to facilitate the interpretation of continuous glucose monitoring data: a narrative review.
  8. A CGM-Based model for predicting hypoglycemia in type 2 diabetes patients with TIR in target.
  9. Impact of Pharmacist-Led Continuous Glucose Monitoring on Clinical Outcomes in People With Type 2 Diabetes in Primary Care: Protocol for a Prospective Cohort Study.
  10. Continuous glucose monitoring: Minimally and non-invasive technologies.
  11. Safety of a Novel Continuous Glucose Monitoring-Informed Insulin Bolus Calculator Mobile Application for People With Type 1 or Type 2 Diabetes.
  12. Glycemic Variability and Control by CGM in Healthy Older and Young Adults and Their Relationship With Diet.
  13. Performance of the DEXCOM G7 CGM system during and after major surgery.
  14. Predictors of impaired awareness of hypoglycaemia and severe hypoglycaemia in adults with type 1 diabetes.
  15. Serum zinc concentration and history of isCGM contact dermatitis in type 1 diabetes.
  16. Wide-linearity flexible OFET biosensors for wearable biomarkers detection.
  1. J Diabetes Sci Technol. 2025 May 17. 19322968251343645
    Minimum requirements for continuous glucose monitors: What does it mean?
    Jan S Krouwer.
      
    Keywords:  adverse events; continuous glucose monitor; diabetes; minimum requirement
    DOI:  https://doi.org/10.1177/19322968251343645
  2. Endocr Pract. 2025 May 21. pii: S1530-891X(25)00893-6. [Epub ahead of print]
    Continuous Glucose Monitoring for Prediabetes - Roles, Evidence, and Gaps.
    Salwa J Zahalka, Halis K Akturk, Rodolfo J Galindo, Viral N Shah, Cecilia C Low Wang.
      Continuous glucose monitoring (CGM) has transformed the care of patients with diabetes, and there is great potential to extend these benefits to prediabetes. The recent FDA approval of over the counter CGMs has increased interest for use in individuals with prediabetes. It is of particular interest to use CGM to guide early individualized lifestyle interventions to prevent the progression of prediabetes to diabetes and support reversion to normoglycemia. In this review, we discuss published evidence regarding CGM metrics in normoglycemia, briefly review the use of CGM to diagnose prediabetes, and review available evidence for CGM use during lifestyle interventions in individuals with prediabetes. Future studies are needed to validate CGM metrics for prediabetes and evaluate effects of early intervention with CGM in this population.
    Keywords:  continuous glucose monitoring; lifestyle intervention; metrics; normal glucose tolerance; prediabetes
    DOI:  https://doi.org/10.1016/j.eprac.2025.05.742
  3. J Diabetes Sci Technol. 2025 May 23. 19322968251344303
    Comparator Value Pairing Impacts Reported Continuous Glucose Monitoring System Accuracy.
    Stefan Pleus, Guido Freckmann, Robbert J Slingerland, Peter Diem, Elisabet Eriksson Boija, Marion Fokkert, Rolf Hinzmann, Johan Jendle, David C Klonoff, Jingyi Lu, Konstantinos Makris, Viswanathan Mohan, James H Nichols, John Pemberton, Elizabeth Selvin, Andreas Thomas, Nam K Tran, Lilian Witthauer, Manuel Eichenlaub.
      
    Keywords:  CGM performance; accuracy; continuous glucose monitoring; standardization
    DOI:  https://doi.org/10.1177/19322968251344303
  4. Diabet Med. 2025 May 21. e70076
    Continuous glucose monitoring during intravenous insulin infusion treatment: Assessing accuracy to enable future clinical utility.
    Ray Wang, Mervyn Kyi, Brintha Krishnamoorthi, Ailie Connell, Cherie Chiang, Debra Renouf, Rahul Barmanray, Spiros Fourlanos.
       AIMS: Continuous glucose monitoring (CGM) during intravenous insulin infusions (IVII) could reduce blood glucose (BG) testing burden in hospital, however CGM accuracy concerns exist. We aimed to assess CGM accuracy during IVII.
    METHODS: This multi-centre observational study included adults with type 1 diabetes (T1D) who required IVII treatment during hospital admission whilst wearing their own CGM devices (Abbott FreeStyle Libre 2, Medtronic Guardian 3, Dexcom G6). IVII dose adjustments were performed based upon standard of care BG measures. Accuracy was assessed according to mean absolute relative difference (MARD) and Consensus error grid (CEG) analysis, using time-matched (±5 minutes) pairs of CGM glucose and reference BG (point-of-care [POC], blood gas [GAS]) obtained during IVII.
    RESULTS: In total, 736 time-matched glucose pairs were obtained from 56 hospital admissions (52% with diabetic ketoacidosis; 32% requiring intensive care). Median IVII duration was 16 hours (IQR 7.2-28). Overall MARD was 12.5% (11.9% for CGM-POC pairs; 14.1% for CGM-GAS pairs). In CEG analysis, 99.0% of glucose pairs were within zones A/B. Based on local hospital IVII dose titration protocols for non-intensive care wards, if CGM measures had been used instead of POC, dose adjustments would have been the same in 77% of instances.
    CONCLUSIONS: This real-world study of adults with T1D demonstrated high concordance of CGM measures with BG during IVII. The accuracy of CGM during IVII might enable its greater clinical utility when treating inpatients receiving IVII. More inpatient studies are required to validate the use of CGM during IVII.
    Keywords:  CGM; CGMS; hospitalization; inpatient; insulin infusion; sensor accuracy
    DOI:  https://doi.org/10.1111/dme.70076
  5. Diabetes Obes Metab. 2025 May 19.
    Heterogeneity of continuous glucose monitoring features and their clinical associations in a type 2 diabetes population.
    Elizabeth Healey, Carlos Morato, Jaime Murillo, Isaac Kohane.
       OBJECTIVE: Data from continuous glucose monitors (CGM) enable the extraction of features descriptive of glycemic dynamics that may provide insight into underlying health status. In this work, we analyse CGM data from a large population of individuals with type 2 diabetes (T2D) and study the association of features with clinical covariates.
    METHODS: We retrospectively analysed CGM and electronic health record data from a large population of individuals with T2D. We extracted 25 daily CGM features for each individual over a 30-day period and performed statistical association tests on the features and clinical findings from medical claims data and laboratory records.
    RESULTS: Our final analysis was performed on 6533 individuals. When clustering the CGM features across the population of individuals with T2D, four distinct clusters of features emerged. Further, the CGM features had heterogeneous discriminatory power with clinical covariates, including laboratory values and the presence of claims for diabetic complications. Features related to glycemic variability, such as coefficient of variation, showed markedly lower p-values in many association tests for the presence of diabetic complications than mean glucose.
    CONCLUSIONS: In examining the characteristics of different features extracted from CGM data in a large population of individuals with T2D, we found that the features were heterogeneously associated with different clinical comorbidities related to diabetes. This work motivates further research to investigate the relationship between CGM features and health outcomes in T2D to enable precision medicine.
    Keywords:  cohort study; continuous glucose monitoring; database research; diabetes complications; type 2 diabetes
    DOI:  https://doi.org/10.1111/dom.16432
  6. Diabetes Technol Ther. 2025 May 21.
    Imputation Model for Glucose Values Above the Upper Detection Limit for Continuous Glucose Monitors.
    Mikkel T Olsen, Maria Panagiotou, Knut J Strømmen, Carina K Klarskov, Peter L Kristensen, Stavroula Mougiakakou.
      Objective: All continuous glucose monitors (CGMs) have an upper detection limit, typically of 22.2 mmol/L. This might bias CGM metrics. We aimed to develop and validate a statistical model for imputing values above this limit. Methods: We analyzed CGM data from 85 inpatients with type 2 diabetes, 705 outpatients with type 1 diabetes, and 27 outpatients with type 2 diabetes. A Bayesian nonparametric latent Gaussian process regression model was applied to the CGM data intentionally right censored for the top 5%, 10%, 20%, and 30% and compared with the uncensored CGM data by the bias, mean squared error (MSE), and coefficient of determination (R2) of mean glucose, standard deviation (SD), and coefficient of variation (CV). Results: In hospitalized patients with diabetes, outpatients with type 1 diabetes, and outpatients with type 2 diabetes for 5% to 30% right censoring, respectively, the bias on mean glucose after imputation ranged from -0.012 to 0.362, -0.018 to 0.485, and -0.008 to 0.130, respectively. Bias on SD ranged from -0.024 to 0.226, -0.033 to 0.381, and -0.016 to 0.138, respectively. Bias on CV ranged from -0.207 to 1.543, -0.316 to 2.609, and -0.222 to 1.721, respectively. Similar results indicating good performance of the imputation model were observed for MSE and R2. Conclusions: An imputation model for glucose values above the upper detection limit of CGMs was developed and validated in various populations. This enables a more unbiased quantification of CGM metrics for patients with severe hyperglycemia.
    Keywords:  censoring; continuous glucose monitoring; hyperglycemia; imputation; statistics
    DOI:  https://doi.org/10.1089/dia.2025.0092
  7. J Endocrinol Invest. 2025 May 17.
    Glycemia risk index (GRI): a metric designed to facilitate the interpretation of continuous glucose monitoring data: a narrative review.
    Philippe Oriot, Gaëtan Prévost, Jean-Christophe Philips, Noemie Klipper Dit Kurz, Michel P Hermans.
      The Glycemia Risk Index (GRI) is a novel composite metric that integrates both hypoglycemia and hyperglycemia episodes to provide a comprehensive view of glycemic control in individuals with type 1 or type 2 diabetes. Unlike traditional metrics such as HbA1c or time-in-range (TIR), the GRI highlights extreme glycemic excursions and aligns more closely with clinical perceptions of glycemic risk. It correlates well with other CGM-derived indicators and has demonstrated relevance in various settings, including the management of individuals using hybrid closed-loop systems. In individuals with HbA1c ≤ 7%, the GRI can reveal hidden risks not captured by HbA1c alone, highlighting its added value in routine clinical assessment. Despite these strengths, the GRI has limitations. It was developed using CGM data from healthy adults on intensive insulin therapy, limiting generalization to other populations. Unlike HbA1c or TIR, it is not yet validated against hard clinical outcomes. As CGM technology evolves, the GRI holds promise as a valuable tool, provided its current limitations are addressed through further research and clinical integration.
    Keywords:  Advanced hybrid closed-loop systems; Ambulatory glucose profile; Continuous glucose monitoring; GRI; Glycemia risk index; Hyperglycemia; Hypoglycemia
    DOI:  https://doi.org/10.1007/s40618-025-02609-1
  8. Diabetol Metab Syndr. 2025 May 24. 17(1): 169
    A CGM-Based model for predicting hypoglycemia in type 2 diabetes patients with TIR in target.
    Jianwen Lu, Danrui Chen, Beisi Lin, Zhigu Liu, Yanling Yang, Ling He, Jinhua Yan, Daizhi Yang, Wen Xu.
       AIM: This study aims to predict risk factors for hypoglycemia in patients with type 2 diabetes mellitus (T2DM) using continuous glucose monitoring (CGM) and with time in range (TIR) > 70%.
    METHODS: Data from 111 patients with T2DM who underwent CGM with TIR > 70% were analyzed. A hypoglycemia episode was defined as CGM-detected glucose < 3.9mmol/L sustained for at least 5 min. Logistic regression analysis was performed to examine the relationship between hypoglycemia and mean blood glucose (MBG), glycemic variability (GV) metrics [including mean amplitude of glucose excursion (MAGE), largest amplitude of glycemic excursion (LAGE), mean of daily difference (MODD), coefficient of variation (CV), standard deviation (SD)], and low blood glucose index (LBGI). A nomogram model was constructed, and its diagnostic performance was assessed. Data were bootstrapped 1000 times for internal validation, and a calibration curve was drawn to evaluate the model's predictive ability. Decision curve analysis was performed to assess its clinical usefulness.
    RESULTS: Among the 111 included patients, 53 experienced hypoglycemic event during wearing CGM (47.75%). GV metrics were higher in hypoglycemia group, while MBG was lower. The multivariable logistic regression analysis showed that the MBG, GV metrics, LBGI were independently associated with hypoglycemia. The receiver operating characteristics (ROC) analysis indicated that the area under the curve (AUC) for the MBG-SD-LBGI model was 0.93 (95% CI = 0.88-0.97). The calibration curve showed good consistency between the predicted and observed probabilities. Decision curve analysis demonstrated strong clinical applicability.
    CONCLUSION: This study demonstrates a significant correlation between CGM metrics and hypoglycemia in patients with T2DM who achieved TIR > 70%. These findings suggest that CGM metrics can predict the risk of hypoglycemia in T2DM patients with a TIR > 70%, and the nomogram developed from these metrics holds strong potential for clinical application.
    Keywords:  Continuous glucose monitoring; Hypoglycemia; Nomogram; Time in range; Type 2 diabetes
    DOI:  https://doi.org/10.1186/s13098-025-01713-9
  9. JMIR Res Protoc. 2025 May 23. 14 e67014
    Impact of Pharmacist-Led Continuous Glucose Monitoring on Clinical Outcomes in People With Type 2 Diabetes in Primary Care: Protocol for a Prospective Cohort Study.
    Kevin Cowart, Raechel T White, Kevin Olson, Nicholas W Carris, Karim Hanna, Janice Zgibor.
       BACKGROUND: Continuous glucose monitoring (CGM) is increasingly being recognized as the new standard of care for glycemic monitoring in people with type 2 diabetes (T2D). However, despite advances in therapeutics and technology, glycemic control remains suboptimal. Team-based approaches involving pharmacists, particularly in primary care, have shown to be effective in addressing these shortcomings yet have not been rigorously evaluated in the literature.
    OBJECTIVE: Herein we present the protocol for a study that seeks to evaluate the change in hemoglobin A1c (HbA1c) in people with T2D using CGM under a pharmacist-led approach as compared with a pharmacist-led approach using no CGM (only self-monitoring blood glucose with a glucometer). We will also assess changes in CGM-derived glycemic outcomes, health behavior, and safety outcomes among the pharmacist-led CGM cohort.
    METHODS: This is a 12-week prospective cohort study in an academic family medicine department. We will enroll adults with T2D and a HbA1c level of ≥8%. Participants in the intervention cohort will wear a CGM sensor (FreeStyle Libre 2) for 12 weeks and receive structured diabetes self-management education and support from a pharmacist. Each participant in the intervention group will have 5 visits with a pharmacist. The primary objective is the between-group difference in change in HbA1c levels from baseline to 12 weeks between the intervention and historical cohort. Secondary objectives include a change in CGM-derived metrics among the intervention group from baseline to 12 weeks, and a change in health behavior via the Summary of Diabetes Self-Care Activities measure from baseline to 12 weeks in the intervention cohort. A CGM survey will also be administered to participants in the intervention cohort to evaluate changes in diet, physical activity, general lifestyle, and medication adherence. Safety endpoints will also be evaluated. The primary and secondary outcomes will be analyzed within and between groups using descriptive statistics, with a multivariable regression analysis conducted as appropriate to adjust for potential known confounding effects.
    RESULTS: This study was funded in July 2023. We began enrolling participants in December 2024. At the time of writing, 3 participants have been enrolled. It is anticipated that we will conclude this study in December 2025 and expect to disseminate results in March 2026.
    CONCLUSIONS: Results of this study will further elucidate the role of pharmacist-led CGM in primary care.
    TRIAL REGISTRATION: ClinicalTrials.gov NCT06572306; https://clinicaltrials.gov/study/NCT06572306.
    INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/67014.
    Keywords:  continuous glucose monitoring; family medicine; pharmacist; primary care; prospective study; type 2 diabetes
    DOI:  https://doi.org/10.2196/67014
  10. Clin Chim Acta. 2025 May 14. pii: S0009-8981(25)00237-2. [Epub ahead of print]575 120358
    Continuous glucose monitoring: Minimally and non-invasive technologies.
    Jeong Eun Lee, Badrinathan Sridharan, Daehun Kim, Yeongho Sung, Jin Hyeong Park, Hae Gyun Lim.
      This paper highlights technological advancements in non-invasive blood glucose monitoring against the backdrop of increasing global prevalence of diabetes. Traditional monitoring methods, primarily invasive methods face limitations in providing continuous glucose level data, which is essential for effective and timely diagnosis of disease stage and for determining the optimal therapeutic strategy. Recent non-invasive technologies encompass optical, acoustic, electromagnetic, and chemical approaches. These technologies exploit the intrinsic properties of glucose, such as its optical absorption coefficients, to offer promising avenues for less intrusive blood glucose monitoring. Despite these advancements, challenges in achieving high accuracy persist due to interference from substances like water and other blood components. This underlines the need for sophisticated algorithms and sensor designs for accurate glucose estimation. Further research is required to integrate various sensing techniques and advanced data processing to enhance accuracy and user-friendliness. In conclusion, while significant progress has been made, developing a reliable, convenient, and accessible method for non-invasive glucose monitoring is crucial for transforming diabetes management and improving patients' quality of life.
    Keywords:  Biomedical Sensing technology; Biosensors; Diabetes management; Non-invasive glucose monitoring; Wearable technology
    DOI:  https://doi.org/10.1016/j.cca.2025.120358
  11. Diabetes Spectr. 2025 ;38(2): 153-160
    Safety of a Novel Continuous Glucose Monitoring-Informed Insulin Bolus Calculator Mobile Application for People With Type 1 or Type 2 Diabetes.
    Mansur Shomali, Colleen Kelly, Abhimanyu Kumbara, Anand Iyer, Jean Park, Grazia Aleppo.
       BACKGROUND: Managing bolus insulin dosing can be a significant burden for people with diabetes, many of whom have limited numeracy skills. Insulin bolus calculators (IBCs) may improve glycemia as well as treatment satisfaction.
    OBJECTIVE: The purpose of this study was to demonstrate the safety of a novel, continuous glucose monitoring (CGM)-informed IBC mobile device app that applies trend arrow adjustments to bolus insulin dose recommendations.
    RESEARCH DESIGN AND METHODS: This clinical trial was an open-label, industry-sponsored single-arm study conducted at two sites. Fifty-four participants with type 1 or type 2 diabetes were enrolled and used the IBC app on their mobile device for 30 days. Study participants were adults who were already using CGM and dosing bolus insulin. The analysis examined both noninferiority and superiority of time in range (TIR) during the study period compared with baseline. Other important end points included hypoglycemia, glucose variability, nocturnal and diurnal TIR, and diabetes distress. The per-protocol (PP) group was defined as participants who used the IBC >30 times during the study.
    RESULTS: Mean TIR improved by 3.8% (95% CI 0.7-6.9%) from 69.2 to 73.0% (P = 0.017) in the PP group. This TIR corresponds to a mean of 0.9 more hours per day spent in range, and the improvement was driven by those with type 2 diabetes. There was no increase in measures of hypoglycemia or diabetes distress. Exploratory analysis revealed a reduction in measures of glucose variability. In addition, individuals with type 1 diabetes had greater improvements in diurnal TIR than in nocturnal TIR.
    CONCLUSION: A CGM-informed IBC app that applies trend arrow adjustments to bolus insulin dose recommendations improved TIR without increasing hypoglycemia or diabetes distress in individuals with type 1 or type 2 diabetes.
    DOI:  https://doi.org/10.2337/ds24-0032
  12. J Endocr Soc. 2025 Jul;9(7): bvaf081
    Glycemic Variability and Control by CGM in Healthy Older and Young Adults and Their Relationship With Diet.
    Anika Köhlmoos, Manuela Dittmar.
      Continuous glucose monitoring (CGM) might be beneficial for investigating healthy aging since high glycemic variability may increase protein glycation, oxidative stress, and inflammation, resulting in vascular damage. Additionally, CGM data on the risks for hypoglycemia and hyperglycemia are scarce, have not been analyzed by individual day and night blocks, and have not been related to diet. Therefore, this study aimed to compare glucose parameters of healthy older and young adults and the relationship with diet. Participants were 34 young (age 20-35 years) and 27 older volunteers (age 60-75 years) with a normal glycated hemoglobin A1c less than 39 mmol/mol hemoglobin, free of disorders and medication. Twenty-four CGM-derived glucose parameters measured over 5 consecutive days were analyzed for whole days and for individual daytime and nighttime blocks. Dietary intake was determined by 3-day dietary record. Neither intraday nor interday glycemic variability differed between the healthy age groups. Glycemic control was good in both age groups, but somewhat poorer in older adults. The risk of hyperglycemia was higher and of hypoglycemia lower in older adults. During the daytime, mean and minimum glucose were higher in older adults. During the nighttime, age group differences were small. The carbohydrate intake correlated positively with glycemic variability in both age groups. The protein intake correlated positively with the hypoglycemic risk in young adults, but negatively in older adults. Results suggest that healthy aging does not increase glycemic variability and the risk of hypoglycemia. The effect of diet on hypoglycemic and hyperglycemic risk might change with aging.
    Keywords:  continuous glucose monitoring (CGM); glycemic control; glycemic variability; healthy aging; nutrition
    DOI:  https://doi.org/10.1210/jendso/bvaf081
  13. Diabetes Obes Metab. 2025 May 21.
    Performance of the DEXCOM G7 CGM system during and after major surgery.
    Gabija Krutkyte, Eva-Dorothea Rolfes, David Herzig, Dominik P Guensch, Thilo Schweizer, Patrick Y Wuethrich, Guido Beldi, Andreas P Vogt, Lia Bally.
      
    Keywords:  continuous glucose monitoring; glucose monitoring technologies; inpatient; sensor accuracy; surgery
    DOI:  https://doi.org/10.1111/dom.16462
  14. Diabet Med. 2025 May 19. e70074
    Predictors of impaired awareness of hypoglycaemia and severe hypoglycaemia in adults with type 1 diabetes.
    Nicola N Zammitt, Shareen Forbes, Berit Inkster, Mark W J Strachan, Rohana J Wright, Anna R Dover, Roland H Stimson, Fraser W Gibb.
       AIMS: This study aimed to assess the prevalence of impaired awareness of hypoglycaemia (IAH) and severe hypoglycaemia (SH) in adults with type 1 diabetes and identify risk factors for both conditions in a contemporary cohort.
    METHODS: A cross-sectional survey was conducted on 782 adults with type 1 diabetes. Participants completed a questionnaire including validated hypoglycaemia awareness and mental health tools. Continuous glucose monitoring (CGM) data were collected in 402 participants. SH was identified based on self-reported episodes.
    RESULTS: 89% were CGM users and 27% were using continuous subcutaneous insulin infusion (CSII). 5.3% of participants reported a recent episode of SH and 21% had IAH based on the Gold score. Elevated Gold Score was independently associated with socioeconomic deprivation (OR 1.9, p = 0.002), female sex (OR 1.8, p = 0.002) and positive depression screen (OR 2.1, p = 0.007). Hypoglycaemia detection threshold <3.0 mM was independently associated with older age (OR 1.03 per year, p < 0.001) and positive depression screen (OR 2.7, p < 0.001). Greater glucose variability (OR 1.14 per % CV glucose, p < 0.001), positive anxiety screen (OR 3.0, p = 0.031) and detection threshold <3.0 mM (OR 6.7, p < 0.001) were all independently associated with SH risk.
    CONCLUSIONS: The prevalence of SH is lower in the modern era of type 1 diabetes management and may reflect greater use of CGM and CSII. Mental health symptoms and socioeconomic deprivation are key associations with IAH and SH. Risk models incorporating clinical, psychological and CGM data may more effectively predict SH.
    Keywords:  hypoglycaemia; severe hypoglycaemia; type 1 diabetes
    DOI:  https://doi.org/10.1111/dme.70074
  15. J Health Popul Nutr. 2025 May 17. 44(1): 161
    Serum zinc concentration and history of isCGM contact dermatitis in type 1 diabetes.
    Mitsunobu Kubota, Shizuka Matsuda, Mimu Matsuda, Shinji Maeda, Sayo Yoshiyama.
       BACKGROUND: In insulin treatment for type 1 diabetes, intermittent scanning continuous glucose monitoring (isCGM: FreeStyle® Libre), in which a sensor is adhered to the skin, is often used to monitor blood glucose fluctuations and manage glucose levels. Zinc-deficient skin is reportedly more susceptible to primary irritant rashes. This study investigated whether zinc deficiency is associated with a history of contact dermatitis caused by isCGM in patients with type 1 diabetes.
    METHODS: The subjects comprised 55 patients (23 men, 32 women, age 57.9 ± 17.6 years) with type 1 diabetes who were outpatients at our department and had a history of isCGM use. We examined the history of contact dermatitis due to isCGM in relation to serum zinc concentration.
    RESULTS: Serum zinc was significantly lower in those with history of contact dermatitis (23 subjects) compared to those without (32 subjects) (P = 0.033). History of contact dermatitis due to isCGM was negatively associated with both age (β =  - 0.266, P = 0.040) and zinc deficiency category (β =  - 0.315, P = 0.017).
    CONCLUSIONS: For people undergoing treatment for type 1 diabetes for whom skin problems caused by isCGM are a barrier to glucose management, screening of serum zinc concentration may be important.
    Keywords:  Contact dermatitis; Intermittent scanning continuous glucose monitor; Serum zinc concentration; Type 1 diabetes
    DOI:  https://doi.org/10.1186/s41043-025-00927-x
  16. Talanta. 2025 May 08. pii: S0039-9140(25)00784-2. [Epub ahead of print]295 128294
    Wide-linearity flexible OFET biosensors for wearable biomarkers detection.
    Xingguo Zhang, Zhihua Pu, Wangwang Zhu, Wenjun Li, Hao Zheng, Chengcheng Li, Dachao Li.
      Flexible organic field-effect transistor (OFET) sensors, which leverage conjugated π-bonds in organic semiconductor layers to facilitate rapid charge transfer and enhance sensing sensitivity, offer significant advantages for detecting low concentrations of biomarkers in wearable biomedical electronics, such as glucose monitoring for diabetes. However, conventional OFET sensors suffer from a narrow linear range due to limitations in threshold voltage and saturation current. Therefore, a common problem in the field of the OFET-based biomarker sensing is that the narrow linear range of these sensors fails to meet detection requirements. This study addresses this challenge by expanding the linear detection range of OFET glucose sensors to 16.78 μM-1 M through the synergistic integration of four p-type and n-type OFET sensor array. Additionally, to ensure consistency in the fabrication of the sensor array, a fully printed processing technology using a bank structure was developed. Finally, a flexible epidermal continuous blood glucose monitoring system based on the wide-linearity OFET glucose sensor array was constructed to verify its practical feasibility.
    Keywords:  Biomarker detection; Glucose sensor; OFET; Wide-linearity detection
    DOI:  https://doi.org/10.1016/j.talanta.2025.128294
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