Continuous Glucose Monitoring Research Articles

Background: Cardiometabolic disorders are a major contributor to cognitive decline and Alzheimer’s disease and related dementias; yet, gaps remain in our understanding of glucose homeostasis and cognitive function. Continuous glucose monitoring (CGM) offers new opportunities to understand these relationships beyond what is possible from fasting glucose and HbA1c. Hypothesis: CGM abnormalities will be associated with worse cognitive function. Methods: CGM was measured in Multi-Ethnic Study of Atherosclerosis (MESA) participants concurrently with cognitive testing in 2022-2024. We report unadjusted and adjusted standardized estimates from linear regression of CGM metrics as quartiles (including mean, variability measures, and time in range variables) with global cognitive function (Composite = mean of z-scores for Cognitive Abilities Screening Instrument (CASI), Digit Symbol Coding (DSC, attention/processing speed), Digit Span (DS, forwards and backwards recall of working memory)) and cognitive domain scores (from the Uniform Data Set (UDS) neuropsychological battery version 3: memory immediate and delayed, attention/processing speed, executive function, visuospatial, language). Results: A total of 892 participants without diabetes (mean age of 76 years; 57% female; 47% white; 24% African American; 19% Hispanic; 10% Asian) were included. Fasting glucose, HbA1c, and CGM variables were significantly associated with unadjusted global cognitive function and processing speed ( Figure 1A ); yet, substantial attenuation was seen with adjustment. Results for memory delayed domain were similar to those for global cognitive composite score except for clinical measurements, with similar but weaker results for memory immediate recall domain (data not shown). In contrast, estimates for coefficient of variation, mean amplitude of glycemic excursions, Time Below Range, Time Above Range, and Time In Tight Range with attention/processing speed domain were significant in both unadjusted and adjusted models ( Figure 1B ). Results for other domains were weaker and not significant (data not shown). Conclusion: This first cross-sectional look from MESA suggests a high level of heterogeneity in the associations between different CGM metrics and indicators of cognitive function; however, the stronger estimates for attention/processing speed, often the earliest indicator of cognitive decline, suggest that CGM metrics may offer insight into the pathways from dysglycemia to cognitive risk.

Background: Prediabetes and diabetes are associated with increased risk for hypertension (HTN) and cardiovascular disease, especially in women. Relations of glycemic variability and other glycemic phenotypes with these diseases have not been well studied in individuals without diabetes. Methods: Framingham Heart Study (FHS) Third Generation, New Offspring Spouse, and Omni 2 participants attending Exam 4 Year 1 (n=1291) were invited to wear a Dexcom G6 Pro continuous glucose monitor (CGM) for 10 days. We included individuals who wore CGM for ≥3 full days (n=1038). Participants were excluded if they had diabetes, took glucose-lowering medication (n=133) or did not complete a mixed meal tolerance test (MMTT, n=53), resulting in a final analytic sample of 852 participants. We performed multivariable linear and logistic regression to examine associations of glucose measures (fasting and 2h-post MMTT) and CGM-metrics with blood pressure (BP) variables and prevalent HTN (defined as stage 2 HTN or taking BP medication). We standardized all predictors to 1SD, log-transformed CGM time above range >140mg/dL (TAR140), and adjusted all regression models for age, smoking status, and body mass index (BMI), stratifying by sex. Results: Among 852 FHS participants (56.9% women; average age 60.3 years), the average BMI was 27.9 kg/m 2 , and 30.5% had hypertension. In multivariable regression models, TAR140, mean CGM glucose, and higher blood glucose at fasting and 2h-MMTT were associated with higher odds of HTN (OR=1.20-1.38, all p<0.05). Among those without HTN (n=583), exploratory heatmaps (Figure) provide visualization of the unadjusted correlations of CGM and blood glucose related metrics with BP measures. In multivariable regression models in men and women without HTN (n=583), fasting and 2h-MMTT blood glucose were associated with systolic BP (β=1.65-2.56, p<0.001). In women only, TAR140, mean CGM glucose, coefficient of variation (CV), mean amplitude of glycemic excursion (MAGE), and mean of daily differences (MODD) were associated with pulse pressure (β=0.97-1.31, all p<0.05) and TAR140, mean CGM glucose, and MODD were also associated with systolic BP (β=1.54-1.94, all p<0.01). These associations were not significant in men (β=-0.56-0.28, all p>0.5). Conclusions: Among individuals without diabetes or HTN, associations of CGM metrics with BP measures were observed in women, not in men, which may reveal mechanistic differences in cardiometabolic disease progression by sex.

Prior studies have not identified if continuous glucose monitoring (CGM) metrics at a critical gestational age window can discriminate risk of adverse pregnancy outcomes. We evaluated late second- and third-trimester CGM metrics by gestational age associated with pregnancy outcomes in gravidas with type 1 diabetes (T1DM). Dexcom G6 CGM data from a retrospective cohort of singleton gestations with T1DM (2018-2022) at an academic medical center were analyzed. Time in, above, and below range 63 to 140 mg/dL (TIR, TAR, TBR), glycemic variability, and mean glucose concentration were computed in two-week CGM intervals from 240 to 396 weeksdays. Adverse pregnancy outcomes were hypertensive disorders of pregnancy (HDP), large-for-gestational age (LGA), and neonatal hypoglycemia. Linear mixed-effects models were fitted on CGM metrics computed from two-week CGM intervals, with gestational age, adverse pregnancy outcomes (i.e. presence/absence of HDP, LGA, and/or neonatal hypoglycemia), and their interaction as fixed effects. In 87 gravidas with preconception median hemoglobin A1c 6.5% (IQR 6.0, 7.1) and maternal body mass index 24.8 kg/m2 (IQR 21.9, 27.1), 71% had at least one adverse pregnancy outcome. Between weeks 240 and 376, gravidas with HDP had higher TAR and mean glucose and lower TIR (P < .05). Gravidas with LGA had lower TBR between weeks 240 and 356. TIR, TAR, and mean glucose evolution differed by HDP status, with greatest divergence between groups at 280 to 296 weeks' gestation (P ≤ .001). CGM metrics in the late second to early third trimester, a period of peak insulin resistance, may help to distinguish risk of HDP and LGA in gravidas with T1DM.

Background: Cardiac arrhythmias, particularly atrial fibrillation (AF), are highly prevalent in diabetes due, in part, to cardiac autonomic neuropathy. More frequent AF may contribute to negative cardiovascular outcomes such as stroke and heart failure. It is unknown if episodes of higher glucose are associated with paroxysmal AF occurrences. Hypothesis: Episodes of higher glucose levels are associated with higher risks of paroxysmal AF onset. Methods: We invited Atherosclerosis Risk in Communities participants with diabetes at visits 9 and 10 (2021-2023) to undergo 14 days of concurrent continuous glucose monitoring (CGM) and “patch” electrocardiographic (ECG) monitoring regardless of arrhythmia history. Among them, we modelled the odds of episodic AF onset, defined as the transition from sinus rhythm to an AF episode (&gt;30 seconds of irregularly irregular rhythm without P-waves), based on same-hour glucose using multilevel logistic regression, and 4-hour CGM data preceding AF onset using generalized scalar-on-function regression. Results: Of 211 CGM-ECG study participants, AF was detected in 18. Ten individuals with at least one episodic AF onset (mean age 81 years, 5 females, 3 Black adults) formed the analytic sample where a total of 129 days of ECG data and 11,453 glucose measurements were analyzed. Among individual monitoring periods, the number of AF episodes ranged from 1 to 159, and the median CGM time below (&lt;70 mg/dl), in (70-180 mg/dl), and above (&gt;180 mg/dl) range was 2%, 65%, and 32%, respectively. Using multilevel logistic regression dividing data into distinct one-hour intervals and accounting for diurnal patterns and participant random effects, we found a 4% higher odds of AF onset per 10 mg/dl higher same-hour mean glucose (odds ratio [OR] 1.04, 95% confidence interval [CI] 1.00-1.09, p =0.04; Figure 1A ). Generalized scalar-on-function regression with participant random effects and adjustment for time of day found a potentiating association between AF onset and glucose elevations accumulated over 4 preceding hours (per 10 mg/dl consistent elevation over 4 hours, integrated OR 1.17, 95% CI 1.11-1.24, p &lt;0.001; Figure 1B ). Conclusion: Among older, US community-dwelling adults with diabetes, the risk of a paroxysmal AF episode was preceded by higher glucose levels for up to 4 hours as measured by CGM. This finding highlights the importance of continuous monitoring with wearable devices and timely detection of hyperglycemia as a marker of AF risk.

Continuous glucose monitoring (CGM) is widely used to monitor glucose levels in patients with diabetes and guide insulin dosing in outpatients. In inpatient care, special regulatory requirements necessitate CGM accuracy as a prerequisite for its integration into clinical decision support. To meet the specific demands of in-hospital care, CGM accuracy was retrospectively evaluated in 226 patients using paired CGM and point-of-care glucose measurements, assessed via mean absolute relative difference (MARD), Clarke Error Grid (CEG) analysis, and a modified version of the U.S. Food and Drug Administration agreement rule. A dynamic, patient-specific algorithm incorporating time lag correction and linear modeling was developed to minimize MARD and applied in a second cohort of 24 patients within the clinical workflow. Data analysis showed an initial MARD of 10.30%, with 99.02% of data points located in zones A and B of the CEG. The application of the patient-specific optimization algorithm improved the MARD by 4.33%. Evaluation of the patient-specific algorithm on the second inpatient cohort demonstrated a 5.58% reduction in intrapersonal MARD, indicating its potential applicability within clinical workflows. Patient-specific algorithmic refinements of CGM data demonstrate the potential to adequately address the unique demands of inpatient diabetes care by reducing intrapersonal MARD, paving the way for the adoption of CGM systems into hospital environments.

Early detection and management of gestational diabetes mellitus (GDM) benefits both mother and infants. We aimed to compare continuous glucose monitoring (CGM) to routine self-monitoring of blood glucose (SMBG) in a randomised controlled trial on glycaemic management and pregnancy outcomes in women with GDM diagnosed in gestational Weeks 8-26. From October 2021 to December 2023, 128 women with GDM were enrolled and 120 completed the trial after 2:1 randomisation to either the intervention (Dexcom G6 CGM, n = 80) or the control group (SMBG 4×/day and monthly blinded CGM [Dexcom G6 Pro], n = 40). Both groups received lifestyle and medication advice based on the CGM interpretation, clinical follow-up and glucose monitoring until delivery. CGM metrics were evaluated with the automated glucose data analysis (AGATA) toolbox (https://github.com/gcappon/agata) and maternal and neonatal outcomes were collected from medical records. Participants completed the CGM Satisfaction survey prior to delivery. While no significant differences between groups in time spent in the glucose target range (TIR) 63-140 mg/dL (primary outcome) were found (p = 0.37), the intervention group experienced significantly lower unscheduled caesarean section rates (20.0% vs. 44.4%, p = 0.046, V = 0.19) and preterm deliveries (6.8% vs. 18.4%, p = 0.041, V = 0.19). Neonates experienced lower large-for-gestational-age rates (5.0% vs. 18.4%, p = 0.019, V = 0.22) and neonatal intensive care unit admissions (22.5% vs. 44.7%, p = 0.013, V = 0.23) compared to the control group. Participants in the intervention group reported high CGM satisfaction and endorsed the behavioural and psychosocial benefits. For women with early GDM, despite no improvement in TIR, CGM improved maternal and neonatal outcomes versus SMBG. The effect may be mediated by improved awareness of glycaemic excursions and by facilitation of treatment regimen adjustments.

Abstract This study presents a high-sensitivity optical glucose sensor based on a tapered fiber Mach-Zehnder interferometer (MZI). The sensor utilizes a tapered optical fiber integrated into the sensing arm of the MZI system, enhancing sensitivity through strong evanescent field interaction. Two configurations were investigated: single-mode taper fiber (SMTF) and single-multi-single mode taper fiber (SMSTF). Experimental results demonstrated that the SMSTF configuration achieved superior performance, with a sensitivity of 0.3042 nm/mg/mL and linearity of 98%. Further enhancement was achieved by integrating the external MZI system, improving sensitivity to 0.6509 nm/mg/mL with a linearity of 99%. The sensor exhibited excellent stability, with a limit of detection (LOD) of 0.3539 mg/mL. Comparative analysis with prior optical glucose sensors highlights the sensor’s advancements in sensitivity, range, and practical usability. These findings establish the proposed sensor as a promising candidate for continuous glucose monitoring (CGM) applications, with potential for integration into healthcare systems for diabetes management.

Blood glucose monitoring is essential for the treatment of diabetes, a chronic disease that affects millions of people worldwide. Non-electrochemical blood glucose sensors often lack sensitivity and selectivity, especially in complex biological fluids, and are not suitable for wearable point-of-care devices. Electrochemical blood glucose sensors, on the other hand, are easy to handle, inexpensive, and offer high sensitivity and selectivity even in the presence of interfering molecules. They can also be seamlessly integrated into wearable devices. This review explores the key blood glucose technologies, emphasizing the operating principle and classification of electrochemical glucose sensors. It also highlights the role of functional solid–liquid interfaces in optimizing sensor performance. Recent developments in solid–liquid interfacial materials, including metal-based, metal oxide-based, carbon-based, nanoparticle-based, conductive polymer, and graphene-based interfaces, are systematically analyzed for their sensing potential. Furthermore, this review highlights existing patents, the evolving market landscape, and data from clinical studies that bridge the gap between laboratory research and commercial application. Finally, we present future perspectives and highlight the need for next-generation wearable and enzyme-free glucose sensors for continuous and non-invasive glucose monitoring.

Advancing self-powered continuous glucose monitoring: a comprehensive simulation of sensor-on-chip development and analog interface circuit design

Diabetes mellitus represents one of the most significant global health challenges of the 21st century, affecting over 537 million adults worldwide. The management of both type 1 diabetes (T1D) and type 2 diabetes (T2D) has evolved dramatically over the past decades, transitioning from rudimentary insulin therapy and dietary restrictions to sophisticated, personalized treatment regimens incorporating cutting-edge pharmacological agents and technological innovations. This comprehensive review critically examines the spectrum of therapeutic approaches for diabetes management, encompassing lifestyle modifications, conventional pharmacotherapy, and emerging novel therapeutic targets. We explore the pathophysiological distinctions between T1D and T2D that necessitate different management strategies, evaluate the efficacy and limitations of current treatment modalities, and discuss promising investigational therapies including immunomodulatory agents, beta-cell regeneration strategies, incretin-based therapies, SGLT inhibitors, and gene therapy approaches. Additionally, we address the integration of continuous glucose monitoring systems, insulin pump technology, and artificial pancreas systems in contemporary diabetes care. Understanding the evolving landscape of diabetes therapeutics is essential for optimizing patient outcomes and reducing the substantial morbidity and mortality associated with this chronic metabolic disorder

Effects of continuous glucose monitoring on dietary behavior and physical activity: A systematic review and meta-analysis.

New methods of continuous glucose monitoring (CGM) data analysis are emerging that are valuable for interpreting CGM patterns and underlying metabolic physiology. These new methods use functional data analysis and artificial intelligence (AI), including machine learning (ML). Compared to traditional metrics for evaluating CGM tracing results (CGM Data Analysis 1.0), these new methods, which we refer to as CGM Data Analysis 2.0, can provide a more detailed understanding of glucose fluctuations and trends and enable more personalized and effective diabetes management strategies once translated into practical clinical solutions.

This study aimed to examine glucose metrics and insulin delivery patterns in children, adolescents, and adults with type1 (T1D) or 2 (T2D) diabetes in France using the tubeless Omnipod DASH® pump with and a continuous glucose monitoring (CGM) sensor connected to myDiabby Healthcare® Data Management Platform (DMP). Time-stamped CGM and insulin data were extracted from the DMP on December 6, 2023 for 17,344 users whose first data point from the tubeless pump occurred after January 1, 2020. The study population included users with sufficient pump and CGM data (≥ 90days of use) and ≥ 15.5% of CGM use days reaching > 70% coverage. Analyses were performed by type of diabetes and age group. Among 14,757 users included in this analysis, most reported having T1D (93.7%), the median age was 33years (Q1-Q3, 16-51), and the median duration of pump use was 545days for people with T1D and 505days for people with T2D (1.49 and 1.38years, respectively). People with T1D spent a median of 52.5% (Q1-Q3, 43.4-62.5) of time in range (70-180mg/dL, TIR) and a TIR ≥ 70% was attained by 12.6% of users. The median time below range (TBR, < 70mg/dL) was 3.7% (Q1-Q3, 2.1-6.1). For users with T2D, median TIR was 66.9% (Q1-Q3, 54.0-77.8), with 42.8% of users achieving a TIR ≥ 70%. Over 90% of all users consumed less than 60UI/day. This robust and scalable analysis of a database of substantial quantity, density, and quality found that tubeless pump users achieved moderate glycemic outcomes overall with favorablesafety outcomes in particular, and used the pump consistently. Such databases could be useful for research and patient care, and further work will show how best to use them.

Achievement of time in range goals among patients with diabetes using continuous glucose monitoring

The aim of this study was to investigate the cost-utility of real-time continuous glucose monitoring (rt-CGM) versus self-monitoring of blood glucose (SMBG) in people with insulin-treated type 2 diabetes (T2D) in Sweden. The CORE Diabetes Model (CDM v10) was used for the analysis. Clinical effectiveness data were obtained from the Steno2Tech trial, an investigator-initiated, 12-month, single center randomized controlled trial based in Denmark. Adverse event rates were sourced from a large-scale observational study based in the USA. Costs were obtained from Swedish and European studies and inflated to 2023 Swedish Krona (SEK). The analysis adopted the perspective of the Swedish payer, and a remaining lifetime horizon was used in the base case. A discount rate of 3% was applied to future costs and outcomes on an annual basis. A commonly cited willingness-to-pay (WTP) threshold of SEK 500,000 was used. rt-CGM led to a gain in mean incremental survival by 0.082years (11.529 life years for rt-CGM versus 11.447 life years for SMBG). Total mean incremental costs were SEK 138,448 higherwith rt-CGM compared with SMBG (SEK 1,151,049 for rt-CGM versus SEK 1,012,601 for SMBG). However, rt-CGM incurred fewer overall diabetes-related complication costs than SMBG over the remaining lifetime horizon. Rt-CGM also yielded a gain in mean incremental quality-adjusted life years (QALYs) of 0.632 (8.608 QALYs for rt-CGM versus 7.976 QALYs for SMBG). The mean incremental cost-utility ratio (ICUR) for rt-CGM was SEK 219,063 per QALY gained, which showed rt-CGM to be cost-effective when compared with the WTP threshold of SEK 500,000. When various indirect cost estimates were incorporated, rt-CGM was consistently more cost-effective than in the base case analysis. For individuals living in Sweden with T2D requiring insulin treatment, rt-CGM is a cost-effective management option relative to SMBG.

Phase separation-based porous microneedle array for non-invasive point-of-care dermal interstitial fluid testing.

Effective inpatient glycemic control is essential to prevent complications such as diabetic ketoacidosis, a serious but avoidable condition linked to longer hospital stays, higher costs, and increased mortality. This review analyzes six preventable cases of diabetic ketoacidosis at a community hospital from April 2022 to October 2023. Such cases often result from inadequate insulin dosing, delayed recognition of hyperglycemia, and inconsistent monitoring. It underscores the role of quality improvement strategies — such as standardized insulin protocols, staff education, and regular feedback — that have been shown to reduce rates of diabetic ketoacidosis by up to 57%. The review advocates for implementing electronic glucose management systems and promoting multidisciplinary collaboration to optimize inpatient diabetes care. Although challenges such as staff compliance and the costs of continuous glucose monitoring exist, these can be addressed through leadership support and targeted interventions. Enhancing protocols and education can significantly lower the incidence of diabetic ketoacidosis and improve outcomes for hospitalized patients with diabetes.

The association of continuous glucose monitoring (CGM) frequency with glycemic control among people with type 2 diabetes has not been well-studied. To evaluate the association of CGM frequency with glycemic status over 12 months vs no CGM use. This retrospective, propensity score-matched, cross-sectional study used Optum deidentified Market Clarity Data (claims and electronic medical record data) obtained between January 1, 2019, and December 31, 2023, including data from 6 months prior to each participant's index date with 12 months follow-up. Participants with type 2 diabetes, aged 18 years or older, and with hemoglobin A1C (HbA1C) levels between 7.0% to 15.0% at baseline were included. Number of days using CGM during the 12-month postindex period (frequency 1, ≥1 to ≤90 days; frequency 2, >90 to ≤180 days; frequency 3, 180 to ≤270 days; frequency 4, >270 days; control, no CGM use). The primary outcome was change in HbA1C relative to frequency of CGM use vs no CGM. A mixed-model analysis was used to determine HbA1C changes across groups. The analysis included 9258 patients (4207 female [45.4%]; mean [SD] age, 55.9 [10.6] years), with 4629 patients in the control group, 1081 in frequency 1, 523 in frequency 2, 540 in frequency 3, and 2485 in frequency 4. High CGM use (frequency 4) was associated with greater reductions in HbA1C at 12 months (-1.52 percentage points; 95% CI, -1.73 to -1.32 percentage points) vs no CGM use (-0.63 percentage points; 95% CI, -0.80 to -0.45 percentage points). CGM users experienced the greatest reductions at approximately 3 months (frequency 1: -0.59 percentage points; 95% CI, -0.96 to -0.21 percentage points; frequency 2: -0.57 percentage points; 95% CI, -1.10 to -0.05 percentage points; frequency 3: -0.79 percentage points; 95% CI, -1.25 to -0.34 percentage points; frequency 4: -0.91 percentage points; 95% CI, -1.12 to -0.70 percentage points) compared with control patients (-0.28 percentage points; 95% CI, -0.47 to -0.09 percentage points). No further glycemic improvement was observed in frequency 2 and frequency 3 groups after 6 months. Improvements in patients in frequency 1 and frequency 4 groups were sustained for the duration of the postindex period. The addition of a glucagon-like peptide-1 receptor agonist in the frequency 4 group was associated with an HbA1C treatment difference of -1.13 percentage points (95% CI, -1.46 to -0.80 percentage points) vs controls at approximately 12 months. This cross-sectional study found that frequent use of CGM (>75% sensor wear) was associated with improved glycemic control compared with infrequent or no use of CGM. These findings suggest that clinicians should monitor CGM use at 6 months, identify potential therapeutic obstacles, and encourage continuous use of CGM.

BackgroundType 2 diabetes (T2D) is highly prevalent in Singapore, yet glycemic control remains suboptimal in primary care. Continuous glucose monitoring (CGM) offers real-time feedback that may improve self-management, but adoption in Asian primary care settings is limited by cost and system integration challenges. This study evaluated the feasibility, acceptability, and perceived impact of CGM implementation in Singapore’s public primary care clinics using a convergent mixed-methods design.MethodsA CGM pilot program was conducted across five public polyclinics. We studied a purposive sample of 12 adults with T2D and 10 primary care providers. Patients used CGM sensors for two cycles over a three- to six-month period. Quantitative surveys assessed usability, satisfaction, and perceived outcomes. Semi-structured interviews with patients and providers explored user experiences and implementation barriers. Data were analysed independently and then integrated for a comprehensive assessment.ResultsAmong the study participants, over 80% of patients found the CGM device easy to use, comfortable, and useful in understanding daily glucose fluctuations. Real-time feedback prompted immediate behaviour changes, 83% reported healthier diets and more frequent glucose monitoring, and 67% felt more confident managing diabetes. Providers unanimously reported that CGM improved clinical decision-making and enhanced patient engagement, enabling more timely and tailored treatment adjustments. Key barriers identified included cost (only 58% of patients were willing to pay out-of-pocket; 89% of providers cited funding concerns), added workload for data interpretation and patient education, and difficulties integrating CGM data into existing workflows. Nonetheless, 67% of patients expressed willingness to reuse CGM if affordable, and providers endorsed its clinical value.ConclusionCGM use in Singapore’s public primary care was feasible and acceptable, supporting individualized diabetes care. Broader adoption will require addressing cost, IT integration, and provider support to realize CGM’s full potential in routine T2D management.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12875-025-03001-x.

Purpose: Continuous glucose monitoring (CGM) technology offers real-time glucose feedback and has shown potential to improve glycemic control. This retrospective study evaluated the effect of CGM on glycemic outcomes in Korean children and adolescents with type 1 diabetes mellitus (T1DM) in a real-world setting.Methods: We included 66 participants divided into a CGM group (n=22) and a self-monitoring blood glucose (SMBG) group (n=44). We compared changes in hemoglobin A1c (HbA1c) of the 2 groups over 1 year and observed changes in CGM activation time, mean glucose, glucose management indicator (GMI), coefficient of variation (CV), time in range (TIR), and hypoglycemia.Results: The CGM group had a mean age of 16.63 years and time from diagnosis to the initiation of study of 4.19 years, while those of the SMBG group were 17.85 years and 5.19 years, respectively. In the CGM group, mean HbA1c decreased from 8.68% at baseline to 7.92% at 12 months (P=0.011), whereas HbA1c increased from 8.46% to 8.93% in the SMBG group (P&lt;0.001). The changes in HbA1c at 1 year between the CGM and SMBG groups were significantly different (-0.76%±1.39% vs. 0.47%±1.38%, P=0.001). CGM activation time decreased slightly (89.09% to 79.24%, P=0.093), and there were no significant changes in TIR, mean glucose, GMI, CV, or hypoglycemia over time.Conclusion: CGM use in Korean children and adolescents with T1DM significantly improves HbA1c levels over 12 months compared to SMBG. The implementation of CGM may provide valuable benefits in glycemic control and potentially reduce the risk of diabetes-related complications.