Search Results (514)

Background: The global aging population faces an increasing prevalence of type 2 diabetes mellitus (T2DM), often complicated by frailty, cognitive decline, and impaired manual dexterity. These factors make glucose self-monitoring particularly challenging. Minimally invasive glucose monitoring methods, particularly continuous glucose monitoring (CGM) as well as emerging non-invasive glucose monitoring technologies offer potential solutions, but remain insufficiently evaluated in older adults. Objective: To systematically review and synthesize available evidence on the advantages of continuous glucose monitoring (CGM) and non-invasive glucose monitoring methods in older adults aged ≥65 years, focusing on clinical efficacy, usability, adherence, and existing knowledge gaps. Methods: A systematic literature search was conducted across PubMed, Scopus, and Web of Science, including studies from 2020 to 2025. Eligible studies included participants aged ≥65 years and evaluated the clinical performance of CGM or other minimally invasive or non-invasive glucose monitoring technologies. The PRISMA framework guided screening and selection. Risk of bias was assessed using RoB 2 and ROBINS-I tools. Due to substantial heterogeneity among study designs and reported outcomes, a narrative synthesis approach was adopted. Results: A total of 426 records were identified, of which 13 met the predefined eligibility criteria after full-text screening. After risk of bias assessment, one study was excluded, resulting in 12 studies included in the final synthesis. No eligible studies evaluating completely non-invasive glucose monitoring technologies were identified, highlighting a significant research gap in this area specifically for older adults. CGM was associated with improved glycemic control, reduced hypoglycemia, and increased time in range among older adults. Usability was generally high, particularly with newer, user-friendly devices. Conclusions: CGM is associated with improved glycemic outcomes and favorable usability in adults aged ≥65 years. However, a significant gap exists in research on non-invasive glucose monitoring technologies in this population. Future studies should address the accuracy, feasibility, and usability of non-invasive glucose monitoring devices, while accounting for the physiological and behavioral complexities associated with aging. Full article

Ramadan fasting substantially alters meal timing, sleep patterns, and daily activity, thereby increasing the risk of hypoglycaemia in adults with type 1 diabetes (T1D). Although continuous glucose monitoring (CGM) systems provide real-time alerts, these are largely reactive or limited to short prediction horizons, offering insufficient warning under fasting-related behavioural and circadian disruption. This study aims to evaluate whether behaviour-aware, temporally enriched recurrent deep learning models, leveraging multimodal CGM and wearable-derived signals, can forecast hypoglycaemia one hour ahead during Ramadan and the post-fasting period. In an observational, free-living cohort study conducted in Qatar, 33 adults with T1D were monitored using CGM and a wrist-worn wearable during Ramadan 2023 and the subsequent month. Multimodal data were aggregated into hourly features and organised into rolling 36 h sequences. In addition to physiological signals, explicit temporal and circadian proxy features were engineered, including cyclic time encodings, day–night indicators, and Ramadan-specific behavioural windows (e.g., pre-iftar, iftar, post-iftar, and fasting phases). Recurrent models, including LSTM and BiLSTM architectures, were trained using patient-wise, leak-free splits, with focal loss applied to address class imbalance. Model performance was evaluated on a held-out, naturally imbalanced test set using ROC AUC, precision–recall AUC, recall, and probability calibration, alongside cross-phase evaluation between Ramadan and post-fasting periods. Following quality control, 1164 participant-days were retained, with hypoglycaemia accounting for approximately 4% of hourly observations. Temporal feature enrichment and the use of a 36 h lookback window improved both discrimination and calibration, with performance stabilizing beyond this horizon. On the imbalanced test set, the best-performing multimodal model achieved an ROC AUC of 0.867 and a precision–recall AUC of 0.341, identifying 77% of next-hour hypoglycaemic events at a sensitivity-focused operating point (precision = 0.14). The selected BiLSTM model demonstrated good probability calibration (Brier score ≈ 0.03). Models trained using wearable-derived inputs alone achieved comparable discrimination and, in some configurations, higher precision–recall AUC than CGM-only baselines. Notably, models trained on the original imbalanced data outperformed resampled variants, suggesting that temporal and behavioural features provided sufficient discriminatory signal without requiring aggressive class balancing. Cross-phase evaluation indicated robust generalisation, particularly for the BiLSTM model. Overall, behaviour-aware, temporally enriched multimodal models can provide calibrated, hour-ahead hypoglycaemia risk estimates during Ramadan fasting in adults with T1D, enabling proactive intervention beyond reactive CGM alerts. Explicit modelling of circadian and behavioural dynamics enhances predictive performance under real-world class imbalance. Furthermore, integrating wearable-derived behavioural and physiological signals adds predictive value beyond CGM alone, supporting robustness across varying levels of contextual data availability. External validation and prospective clinical evaluation are required prior to deployment. Full article

Background: Μetabolic syndrome (MetS)—comprises central adiposity, elevated blood pressure, dyslipidaemia, and dysglycaemia, increasing the risk of type 2 diabetes and cardiovascular disease. Exercise training improves cardiorespiratory fitness and several MetS components, but real-world effectiveness is limited by poor adherence, restricted supervision, and insufficient personalisation. Objective: This scoping review mapped the clinical intervention evidence on technology-enhanced exercise and structured physical activity relevant to MetS, while distinguishing direct MetS evidence from translational evidence. Methods: In accordance with PRISMA-ScR, we searched PubMed and extended the search to Scopus and Web of Science; a supplementary IEEE Xplore search and a post hoc Embase check were also conducted. Eligible studies were interventions using web-based delivery, wearables, telemonitoring/mobile health (mHealth), artificial intelligence (AI) coaching, virtual reality (VR)/exergaming, or continuous glucose monitoring (CGM) alongside exercise training or structured physical activity. Results: Nineteen studies met the eligibility criteria. The evidence base was weighted toward wearable/app-based feedback and telemonitoring/mHealth/web-based approaches, with fewer studies on VR/exergaming, CGM-enabled exercise, and AI coaching. Most studies were randomised or cluster-randomised, but interventions were usually short term. Across categories, technology most consistently supported adherence, self-monitoring, accountability, remote supervision, and, in selected cases, physiology-informed personalisation. Direct MetS evidence was strongest for wearables with structured feedback, telemonitoring, mHealth, and web-based delivery, whereas AI coaching and CGM were supported by adjacent translational evidence. Conclusions: Technology-enhanced exercise and structured physical activity show promising but heterogeneous and still preliminary potential for MetS management. Key limitations include short follow-up, uneven representation across categories, inconsistent reporting of exercise dose/intensity fidelity and adverse events, and limited equity and implementation outcomes. Full article

Background/Objectives: Continuous glucose monitoring (CGM) has transformed diabetes management by enabling high-resolution assessment of glucose dynamics, with well-established use in type 1 diabetes (T1D) and insulin-treated type 2 diabetes (T2D), and expanding applications across broader populations, including non-insulin-treated T2D and gestational diabetes. However, real-world implementation remains constrained by economic barriers, fragmented reimbursement, workflow challenges, and limited capacity for continuous data interpretation. This review examines key barriers to CGM implementation and synthesizes current evidence on pharmacist-integrated CGM care as an emerging model to support CGM adoption across clinical and community-based settings. Methods: A narrative literature review was conducted to synthesize evidence on pharmacist-integrated CGM services in diabetes care. Literature was identified through structured searches of PubMed, Embase, and the Cochrane Library, supplemented by Google Scholar and citation tracking, covering publications from January 2010 to December 2025. Studies were selected based on predefined criteria, including those reporting clinical outcomes, pharmacist involvement, or health system and implementation factors related to CGM use. Relevant survey-based and real-world studies were also considered to capture healthcare professionals’ perspectives and implementation experiences. Evidence was synthesized thematically across clinical, behavioral, and health system domains. Results: Available evidence suggests that pharmacist-integrated CGM care is associated with improvements in glycemic management, including increased time in range, reduced glycemic variability, and more timely pharmacotherapy optimization. Pharmacist involvement may also support patient education, self-management, and engagement with digital health technologies, and facilitate ongoing data interpretation and treatment adjustment between clinical encounters. However, evidence remains heterogeneous and geographically limited, with predominantly retrospective and pilot studies and few randomized trials, constraining the robustness and external validity of the findings. Further studies are needed to confirm its clinical effectiveness, comparative effectiveness, and economic value. Conclusions: Pharmacist-integrated CGM represents a promising and operationally feasible approach to supporting CGM use in routine diabetes care. While current evidence indicates potential benefits in glycemic management and care delivery processes, further research and implementation efforts are required to support its effective and sustainable adoption across diverse healthcare settings. Full article

Background/Objectives: Blood glucose prediction (BGP) for individuals with type 1 diabetes (T1D) is a clinically essential yet highly challenging task in time series forecasting (TSF) and an important problem in personalised medicine. Accurate bespoke BGP is crucial for individualised T1D management, reducing complications, and supporting patient-specific glycaemic risk mitigation. However, the pronounced volatility of glycaemic fluctuations in T1D, combined with the need for mathematical rigor and clinical relevance, hampers reliable prediction. This complexity underscores the demand to explore and enhance more advanced techniques. While adversarial learning is adept at modelling intricate data variability, its potential for BGP remains largely untapped. Methods: This work presents a novel approach for BGP by addressing a key limitation in conventional adversarial learning when applied to this task. Typically, these methods optimise prediction accuracy within a set horizon by minimising adversarial loss. This focus overlooks how predictions align with longer-term patterns, which are critical for clinical relevance in BGP, thereby yielding suboptimal results. To overcome this limitation, we introduce collaborative augmented adversarial learning, designed to improve the model’s temporal awareness. Incorporating collaborative interaction optimisation, this approach enables the model to reflect extended time dependencies beyond the immediate horizon, thereby improving both the clinical reliability of predictions and overall predictive performance. We develop and evaluate four learning systems for BGP: independent learning, adversarial learning, collaborative learning, and adversarial collaborative learning. The proposed systems were evaluated for two clinically relevant prediction horizons, namely 30 min and 60 min ahead. Results: The interdependent collaboratively augmented learning frameworks, validated using the well-established Ohio T1D datasets, demonstrate statistically significant superior performance in both clinical and mathematical evaluations. Conclusions: Beyond advancing BGP accuracy and clinical reliability, the proposed approach supports personalised medicine by improving subject-specific glucose forecasting from CGM data, with potential relevance for more individualised diabetes monitoring and decision support. The proposed approach also opens new avenues for advancements in other complex TSF domains, as outlined in our future work. Full article

Background: Continuous glucose monitoring (CGM) systems have significantly improved glycemic management in patients with type 1 diabetes mellitus and are generally considered safe. However, transcutaneous sensor insertion disrupts the skin barrier and, in susceptible individuals, may contribute to infectious complications. Severe soft tissue infections occurring in temporal association with CGM use are exceedingly rare. Case Presentation: We report a fatal case of necrotizing soft tissue infection in a 54-year-old male with long-standing type 1 diabetes mellitus occurring in temporal association with CGM use. The patient initially developed localized inflammation at a prior sensor insertion site that failed to fully resolve. Over subsequent weeks, he experienced progressive systemic symptoms and worsening local findings, culminating in advanced necrotizing infection. Despite emergency surgical debridement, broad-spectrum antimicrobial therapy, and intensive care support, the clinical course was complicated by septic shock and multiorgan failure, resulting in death. Discussion: This case highlights the role of patient-specific vulnerability, persistent insertion-site inflammation, and delayed clinical recognition in the progression from localized skin changes to life-threatening infection. Importantly, this report does not establish a direct causal relationship between CGM use and necrotizing soft tissue infection but underscores the need for heightened vigilance in high-risk individuals. Conclusions: Although CGM systems have a favorable safety profile, careful inspection of insertion sites, avoidance of sensor reapplication over incompletely healed tissue, and early evaluation of persistent or progressive symptoms are essential to minimize the risk of severe outcomes in susceptible patients. Full article

Background/Objectives: Patients with hepatic glycogen storage disease (GSD) require frequent nighttime intake of uncooked corn starch (UCCS) to prevent fasting hypoglycemia, which imposes a substantial burden. Glycosade, an extended-release cornstarch, was developed to prolong overnight glucose availability. However, data regarding South Korean patients are limited. Therefore, we aimed to evaluate the efficacy and safety of Glycosade in South Korean patients with hepatic GSD. Methods: In this single-center prospective observational study, patients with hepatic GSD underwent laboratory evaluations before and 1 month after Glycosade administration. Continuous glucose monitoring (CGM) was performed during UCCS and Glycosade administration periods. The nocturnal mean glucose, coefficient of variation, time in range (70–180 mg/dL), and time below the range (<70 and <54 mg/dL) were compared between the periods using paired analyses. Results: No significant differences were observed in the nocturnal CGM metrics between the treatment periods. However, time-aligned CGM profiles revealed distinct temporal patterns, with a decline in glucose levels approximately 3–4 h after UCCS intake, whereas Glycosade showed a more sustained glucose profile over an extended period. Liver enzyme and lipid levels improved significantly after 1 month of Glycosade supplementation. Conclusions: In a cohort of South Korean patients with hepatic GSD, Glycosade maintained nocturnal glycemic stability comparable to that of conventional cornstarch without increasing the risk of hypoglycemia. Glycosade was also associated with improved biochemical parameters, supporting its role in nighttime dietary management. Full article

The ADA 2026 Standards of Care in Diabetes introduces pivotal updates that refine diagnostic and therapeutic workflows. Expanding upon the 2025 guidelines, the 2026 edition broadens continuous-glucose-monitoring (CGM) eligibility to include all individuals on insulin or non-insulin therapies where CGM aids management. Significant new guidance addresses hyperglycemia management in oncology, identifying metformin as the preferred first-line intervention for drug-induced glycemic excursions. Additionally, type 1-diabetes (T1D) risk stratification is refined; a confirmed single IA-2 autoantibody now warrants monitoring levels similar to the Stage 2 disease. Furthermore, prerequisites for automated-insulin-delivery (AID) initiation have been removed to streamline technology access. For laboratory professionals, these revisions emphasize the critical role of advanced glycemic metrics and precise autoantibody profiling in complex clinical contexts. Full article

The newly identified greisen-hosted Nb-Ta mineralization in the Qidashan iron deposit, Liaoning Province, China, offers a unique opportunity to explore how hydrothermal processes contribute to the enrichment of critical metals. In this study, an integrated analytical approach of petrographic observation and scanning electron microscopy–energy-dispersive spectrometer (SEM-EDS), electron probe microanalyzer (EPMA), and laser ablation inductively coupled plasma mass spectrometer (LA-ICP-MS) U-Pb dating of columbite-group minerals (CGMs) were employed to systematically decipher the paragenetic sequence, micro-structure, elemental composition and mineralization age of CGMs, aiming at the genesis of greisen-hosted Nb-Ta mineralization. The mineralization is characterized by the abundant occurrence of CGMs. Three generations of CGMs and two mineralization stages are distinguished: stage I contains CGM Is and CGM IIs, with Nb₂O₅ ranging from 25.7 to 69.56 wt.% and Ta₂O₅ from 5.8 to 52.5 wt.%; stage II contains CGM IIIs, with Nb₂O₅ between 59.5 and 71.5 wt.% and Ta₂O₅ between 3.5 and 16.2 wt.%. CGM Is consist of euhedral, homogeneous crystals of more than 100 μm, exhibit low Ta/(Nb + Ta) ratios (0.05–0.06) and high Mn/(Fe + Mn) ratios (0.19–0.26), and belong to columbite-Fe. CGM IIs generally overgrow on CGM Is with hydrothermal overprinting textures, and show significant compositional gaps compared to CGM Is, exhibiting higher Ta/(Nb + Ta) ratios (0.13–0.55) and restricted Mn/(Fe + Mn) ratios (0.15–0.18), with some belonging to columbite-Fe and others to tantalite-Fe, which reveals a transition from magma to “hydrosilicate fluid”. CGM IIIs are mainly anhedral and homogeneous, with a grain size of less than 50 μm. However, some CGM IIIs overgrow on CGM IIs and/or CGM Is with patchy textures indicative of subsequent hydrothermal overprinting of hydrosilicate fluid, forming a coarse-grain size over 100 μm. CGM IIIs are characterized by lower Ta/(Nb + Ta) ratios (0.03–0.14) and variable Mn/(Fe + Mn) ratios (0.08–0.26), and they belong to columbite-Fe. LA-ICP-MS U-Pb dating yields weighted mean ²⁰⁶Pb/²³⁸U ages of 2646 ± 15 Ma for stage I and 2500 ± 28 Ma for stage II, indicating two-stage Nb-Ta mineralization. The early mineralization may correlate with the partial melting of volcanic–sedimentary rocks due to the geothermal anomalies associated with ~2.7 Ga submarine volcanism, and the late mineralization formed by the magmatic hydrothermal activities related to emplacement of the Qidashan granite in 2.5 Ga. We therefore propose that the two-stage greisen-hosted Nb-Ta mineralization probably widely occurred in these sedimentary–metamorphic iron deposits in the Anshan–Benxi area and even in the northern edge of the North China Craton, and it may provide new insights for evaluating the Nb-Ta resource potential in similar Algoma-type iron deposits globally. Full article

In the 21st century, there have been radical changes in healthcare related to the transition from a universal approach to personalized medicine based on the unique characteristics of each patient. In large part, this has become possible due to the development and distribution of wearable medical devices that are capable of providing continuous monitoring of a variety of physiological parameters outside medical institutions. The most important of these devices are modern biosensors that allow real-time tracking of various biomarkers in the body, thereby opening up new opportunities for disease prevention, early diagnosis, and personalized treatment strategies. The most obvious example of the transformation is the implementation of wearable devices for continuous glucose monitoring (CGM), which has significantly facilitated the daily lives of millions of people with diabetes. Nevertheless, despite the examples of successful implementation of these devices, their large-scale distribution is associated with many challenges, such as the need for standardization, data transmission security, and the risks of immune responses to implantable devices or infections. This review examines all the current problems of wearable biosensors and possible ways to overcome them. Special emphasis will be placed on devices for continuous glucose monitoring as the most commercially successful representatives of this device class. Full article

Metabolic control is poor in East Africa for youth with type1 diabetes (T1D). Self-monitoring of blood glucose (SMBG) by fingerstick 2–3 times daily is routine care. This randomized controlled trial (RCT) will test the hypothesis that providing continuous glucose monitoring (CGM) to Ugandan youth with T1D will improve glucose time-in-range (TIR glucose 3.9–10.0 mmol/L) and be cost effective in this setting. Ugandan youth with T1D (n = 180, age 4–26 years) will be divided into four 12-month cohorts (August 2022–August 2027). Half will receive unblinded Freestyle Libre 2 Flash CGM for 12 months. For six months, control subjects received sufficient test strips for SMBG three times daily while wearing blinded Freestyle Libre Pro CGM (for endpoint assessment), and then they switch to unblinded CGM for six months. Everyone receives monthly diabetes education. The primary endpoints are as follows: (1) the six-month change from baseline in glucose TIR, unblinded CGM versus SMBG; (2) a cost analysis of CGM versus SMBG. The TIR hypothesis will be tested by linear mixed effects models. Cost analysis assumptions include direct material and indirect costs like hospitalizations, missed school/work, and diabetes complications. The study will inform T1D management guidelines in a low resource setting using evidence-based recommendations. Full article

Glucose data regarding extreme elite performances in athletes without diabetes remains limited. The purpose is to characterize continuous glucose monitoring (CGM) responses in elite athletes across distinct high-performance contexts. This descriptive case series includes three separate elite athletes who used a CGM during their respective sporting events. The first is an ultra-endurance relay cycling world-record performance (Race Across the West, RAW), the second is a continuous high-intensity Everesting Challenge cycling record attempt, and the third is a maximal constant-weight no-fins breath-hold depth dive performed in international competition. Glycemic outcomes, as measured by CGM, included mean, maximum, and minimum glucose, glucose standard deviation (SD), and the percentage of time in tight glucose range (TITR: 70–140 mg/dL; 3.9–7.8 mmol/L), time below range (TBR: <70 mg/dL; <3.9 mmol/L), and time above range (TAR140: >140 mg/dL; >7.8 mmol/L). Other performance data, including peak power, heart rate, and lactate, are also provided where available. During the RAW challenge lasting 44 h and 20 min, mean glucose was 91 ± 23.2 mg/dL (mean ± SD) with 9.15% TBR and 35.58% TITR during cycling and 115 ± 24.7 mg/dL with 9.11% TBR and 43.16% TITR during resting periods. In contrast, the Everesting Challenge cycling record attempt demonstrated a persistently elevated glucose profile (160 ± 5.7 mg/dL), minimal variability (CV 3.5%), and 100% TAR140. Following the maximal breath-hold depth dive, interstitial glucose was 100% TAR140 during recovery (187 ± 18.5 mg/dL), alongside marked elevations in blood lactate concentrations (peak 13.4 mmol/L). The series of case studies demonstrate that substantial deviations from traditional euglycemic ranges are common during elite performance in athletes without diabetes. Interpretation of CGM data in athletic settings should therefore be performance- and context-specific rather than based on clinical glycemic thresholds. Full article

Background/Objectives: Type 2 diabetes (T2D) affects more than 38 million Americans and remains a leading public health challenge. Behavioral self-management is central to glycemic control but is often undermined by dysregulated and addictive-like eating behaviors. Continuous glucose monitoring (CGM) offers immediate feedback that may strengthen self-regulation, yet the psychological processes linking CGM use, food addiction (FA), and behavior change are poorly understood. This secondary mixed-methods study examined how CGM-supported group medical visits (GMVs) influence glycemic outcomes and FA symptoms in adults with diabetes. Methods: Adults with T2D participated in a 14-week GMV program integrating CGM review with education on nutrition, physical activity, sleep, stress, and intermittent fasting. Thirteen participants had paired CGM summaries and psychosocial data. Quantitative outcomes included mean glucose, glycemic variability, time-in-range (TIR), and symptoms of food addiction using the modified Yale Food Addiction Scale 2.0 (mYFAS 2.0). Qualitative data came from open-ended surveys analyzed using reflexive thematic analysis. Integration followed a convergent design, merging individual change trajectories with thematic interpretations and case vignettes. Results: Mean glucose decreased by 21 mg/dL and TIR improved by 9 percentage points. Among six participants with baseline FA symptoms, all showed reductions in self-reported mYFAS 2.0 symptom counts. Four moved from mild to no symptoms, one from moderate to no symptoms, and one from severe to no symptoms. Across the full sample, the mean change was a reduction of 1.2 in the mYFAS 2.0 symptom counts per participant. Thematic analysis identified four interrelated psychological mechanisms: enhanced awareness of food–glucose relationships, increased accountability through shared tracking, motivation via gamified self-monitoring, and relief from cognitive burden associated with dietary uncertainty. Conclusions: Integrating CGM feedback into GMVs was associated with improvements in glycemic metrics and reductions in addictive-like eating symptoms in this pilot sample. These findings position CGM as a behavioral intervention tool that complements its traditional monitoring role and highlight the value of combining real-time biofeedback with group-based support in diabetes care. Full article

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%. Full article

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 (MARD_{REN 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 MARD_{REN ON/OFF} across all participants was 1.61% (IQR 0.84–2.44%), significantly below the 5% threshold (p < 0.001). All participants achieved MARD_{REN ON/OFF} < 5%. Subgroup analyses were consistent: the median MARD_{REN 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. Full article