Design Principles for System-Level Integration of Static and Sequential Health Data

To evaluate continuous subcutaneous glucose monitoring in pediatric critical illness. Prospective evaluation. Mixed university pediatric intensive care unit. Children aged 1 mo to 16 yrs requiring mechanical ventilation with at least two organ system failures. None. Blood samples obtained from an arterial line, measurements using point-of-care glucometer, and laboratory analysis were compared with continuous subcutaneous glucose monitoring. Fourteen patients yielded 11,880 continuous subcutaneous glucose monitoring measurements; 436 glucometer levels and 34 laboratory levels had mean time-paired glucose values of 108 +/- 29 mg/dL and 110 +/- 25 mg/dL, respectively. Mean continuous subcutaneous glucose monitoring glucose was 101 +/- 31 mg/dL for samples paired with glucometer and 95 +/- 40 mg/dL for samples paired with laboratory tests. Continuous subcutaneous glucose monitoring measurements correlated with glucometer (r = 0.44) and laboratory testing (r = 0.48). Mean absolute differences between continuous subcutaneous glucose monitoring measurement and glucometer and laboratory values were 18 +/- 16 mg/dL and 25 +/- 20 mg/dL, respectively. Clarke error grid analysis found 69% of the measurements to be in zone A (clinically accurate), 29% in zone B (benign errors), and 2% in zone D (failure to detect errors). The mean absolute relative difference between the continuous subcutaneous glucose monitoring measurement and glucometer and laboratory measurements were 17% and 23%, respectively. Bland-Altman analysis showed good agreement between continuous subcutaneous glucose monitoring and the other methods of glucose measurement. However, in the lower range (< or =74 mg/dL) 39% of the continuous subcutaneous glucose monitoring readings had a difference >15 mg/dL. On multiple regressions, only glucometer glucose values, continuous subcutaneous glucose monitoring levels, and base deficit were associated with the mean absolute relative difference. The performance of continuous subcutaneous glucose monitoring against point-of-care glucometer and laboratory measurements may be considered "good" using statistical definitions (Bland-Altman and Clarke error grid analysis). However, there are important limitations in children with large base deficit, being actively cooled, and with glucose in the lower range, which may limit its application.

Continuous and wireless vital sign (VS) monitoring on hospital wards is superior to intermittent VS monitoring at detecting VS abnormalities; however, the impact on clinical outcomes remains to be confirmed. A recent propensity-matched study of primary surgical patients found decreased odds of intensive care unit (ICU) admission and mortality in patients receiving continuous monitoring. Primary surgical patients are inherently different from their medical counterparts who typically have high morbidity, including frailty. Continuous monitoring research has been limited in primary medical patients. This study aims to evaluate the clinical outcomes of primary medical patients who received either continuous or, as a contemporaneous control, intermittent vital monitoring as the standard of care using propensity matching. Propensity-matched analysis of a population-based sample of 7971 patients admitted to the medical wards between January 2018 and December 2019 at a single, tertiary United States medical center. The continuous monitoring device measures oxygen saturation, heart rate, respiratory rate, continuous noninvasive blood pressure, and either 3-lead or 5-lead electrocardiogram. Patients received either 12 hours or more of continuous and wireless VS monitoring (n=1450) or intermittent VS monitoring (n=6521). The primary outcome was the odds of a composite of in-hospital mortality or ICU transfer during hospitalization. Secondary outcomes were the odds of individual components of the primary outcome, as well as heart failure (HF), myocardial infarction (MI), acute kidney injury (AKI), and rapid response team (RRT) activations. Those who received intermittent VS monitoring had greater odds of a composite of in-hospital mortality or ICU admission (odds ratio [OR] 2.79, 95% CI 1.89-4.25; P<.001) compared with those who had continuous and wireless VS monitoring. The odds of HF (OR 1.03, 95% CI 0.83-1.28; P=.77), MI (OR 1.58, 95% CI 0.77-3.47; P=.23), AKI (OR 0.74, 95% CI 0.62-1.02; P=.06), and RRT activation (OR 0.94, 95% CI 0.75-1.19; P=.62) were similar in both groups. In this propensity-matched study, medical ward patients who received standard of care intermittent VS monitoring were at nearly 3 times greater odds of transfer to the ICU or death compared with those who received continuous VS monitoring.Our study was primarily limited by the inability to match patients on admission diagnosis due to limitations in electronic health record data. Other limitations included the number of and reasons for false alarms, which can be challenging with continuous monitoring strategies. Given the limitations of this work, these observations need to be confirmed with prospective interventional trials.

To examine the impact of continuous glucose monitoring on diabetes management and marital relationships of adults with Type1 diabetes and their spouses. Nine younger (30-49years) and 11 older (50-70years) patients with Type1 diabetes and 14 spouses participated in eight focus groups specific to age and role (patient or spouse). Audio-recorded data were transcribed, coded and analysed using thematic analysis and aided by NVivo software. Qualitative analysis revealed participants perceived continuous glucose monitoring as positively influencing hypoglycaemia management by decreasing spouses' anxiety, vigilance and negative experiences. Participants also described continuous glucose monitoring as promoting collaborative diabetes management and increasing spousal understanding of diabetes, especially when planning and managing pregnancy. Couples' conflicts occurred when (1) patients assumed sole responsibility for continuous glucose monitoring and/or did not respond to night-time glucose alarms and (2) spouses did not understand alarms and felt frustrated and helpless to assist patients. Our findings suggest that continuous glucose monitoring may positively impact collaborative diabetes management and marital relationships of patients with Type1 diabetes and their spouses. However, reluctance to collaborate and lack of understanding may contribute to couples' conflicts around continuous glucose monitoring. Our findings have important implications for clinical care and point to the need for interventions that include spouses in continuous glucose monitoring training to increase their understanding of continuous glucose monitoring, minimize risk for spousal conflict and enhance collaborative diabetes management. Further studies are needed to explore these issues in more detail and depth with larger and more diverse populations.

INTRODUCTION: The rising incidence of pediatric diabetes underscores the need for accurate glucose monitoring tools to facilitate early detection. Although both Blood Glucose Meters (BGM) and Continuous Glucose Monitoring (CGM) are widely used, their comparative effectiveness in predicting diabetes onset in children remains contested. This study evaluated and compared the predictive utility of BGM and CGM in high-risk pediatric populations. METHODS: A nine-month prospective observational study (January–September 2024) was conducted at the Health Polytechnic of the Ministry of Health, Sorong, involving 76 children aged 10–18 years diagnosed with Acanthosis Nigricans and positive FINDRISC scores. Participants were allocated to either BGM (every 3 days) or CGM (15-minute intervals). Key outcome measures included Time in Range (TIR), mean glucose levels, frequencies of hypo- and hyperglycaemic episodes, adherence rates, and Mean Absolute Relative Difference (MARD). RESULTS: CGM significantly outperformed BGM across all parameters: higher TIR (78.9% vs. 63.4%, p&lt;0.001), lower average glucose levels (145.3 vs. 162.7 mg/dL, p=0.003), fewer hypoglycaemic (1.1 vs. 2.8, p=0.015) and hyperglycaemic events (2.6 vs. 4.5, p=0.002), and superior adherence (88.7% vs. 71.3%, p&lt;0.001). CGM also showed a lower MARD (7.2% vs. 10.8%, p=0.004), indicating greater accuracy. CONCLUSIONS: CGM offers more reliable and comprehensive glucose monitoring than BGM for predicting diabetes onset in children at risk, supported by better glycaemic control, higher adherence, and improved accuracy. These findings endorse CGM as the preferred approach for early diabetes detection in pediatric populations.

Amylin, Eli Lilly, and Alkermes received a full response letter from the USFDA on the companies' New Drug Application (NDA) for their once-weekly exenatide, thereafter branded Bydureon.The USFDA's letter did not request any new clinical or preclinical data or data analysis, instead focusing on label fi nalization, Risk Evaluation and Mitigation Strategy (REMS), and clarifi cation

Blood glucose monitoring is an important part and means in the process of diabetes treatment and management. There is a high correlation between glucose concentration in interstitial fluid and glucose concentration in blood. Real-time monitoring of glucose concentration in interstitial fluid has important clinical significance. Continuous glucose monitoring (CGM) is an emerging glucose monitoring technology, which indirectly reflects the blood glucose level of the body through the glucose level in the interstitial fluid, providing continuous and comprehensive information and rules of blood glucose variation over a period of time. There are three main categories of CGM: minimally invasive implantation, non-invasive microtransparency and non-invasive technology. Noninvasive blood glucose monitoring technology is the future development direction, but accuracy and delay of blood glucose will be the biggest challenge to be overcome in clinical application. Key words: Blood glucose monitoring; Continuous glucose monitoring; Noninvasive glucose monitoring

Continuous glucose monitors are crucial for diabetes management, but invasive sampling, signal drift and frequent calibrations restrict their widespread usage. Microneedle sensors are emerging as a minimally-invasive platform for real-time monitoring of clinical parameters in interstitial fluid. Herein, a painless and flexible microneedle sensing patch is constructed by a mechanically-strong microneedle base and a thin layer of fluorescent hydrogel sensor for on-site, accurate, and continuous glucose monitoring. The Förster resonance energy transfer (FRET)-based hydrogel sensors are fabricated by facile photopolymerizations of acryloylated FRET pairs and glucose-specific phenylboronic acid. The optimized hydrogel sensor enables quantification of glucose with reversibility, high selectivity, and signal stability against photobleaching. Poly (ethylene glycol diacrylate)-co-polyacrylamide hydrogel is utilized as the microneedle base, facilitating effective skin piercing and biofluid extraction. The integrated microneedle sensor patch displays a sensitivity of 0.029 mM−1 in the (patho)physiological range, a low detection limit of 0.193 mM, and a response time of 7.7 min in human serum. Hypoglycemia, euglycemia and hyperglycemia are continuously monitored over 6 h simulated meal and rest activities in a porcine skin model. This microneedle sensor with high transdermal analytical performance offers a powerful tool for continuous diabetes monitoring at point-of-care settings.

Diabetes technology has the potential to provide useful data for theory-based behavioral counseling. The aims of this study are to evaluate the feasibility, acceptability, and preliminary efficacy of a continuous glucose monitoring and problem-solving counseling intervention to change physical activity (PA) behavior in women with type 2 diabetes. Women (n=29) with type 2 diabetes were randomly assigned to one of two treatment conditions: continuous glucose counseling and problem-solving skills or continuous glucose monitoring counseling and general diabetes education. Feasibility data were obtained on intervention dose, implementation, and satisfaction. Preliminary efficacy data were collected at baseline and 12 weeks on the following measures: PA amount and intensity, diet, problem-solving skills, self-efficacy for PA, depression, hemogoloin A1c, weight, and blood pressure. Demographic and implementation variables were described using frequency distributions and summary statistics. Satisfaction data were analyzed using Wilcoxon rank. Differences between groups were analyzed using linear mixed-modeling. Women were mostly white/non-Latina with a mean age of 53 years, a 6.5-year history of diabetes, and suboptimal glycemic control. Continuous glucose monitoring plus problem-solving group participants had significantly greater problem-solving skills and had greater, although not statistically significant, dietary adherence, moderate activity minutes, weight loss, and higher intervention satisfaction pre- to post-intervention than did participants in the continuous glucose monitoring plus education group. A continuous glucose monitoring plus problem-solving intervention was feasible and acceptable, and participants had greater problem-solving skills than continuous glucose monitoring plus education group participants.

BackgroundNew technologies for the management of children with type 1 diabete (T1D) are constantly and rapidly evolving. However, few real-life studies have been conducted, and rarely in the youngest patients (<6 years). AimTo study parental satisfaction with continuous and flash glucose monitoring devices in young children with T1D. MethodsA questionnaire was completed by the parents of 114 children under the age of 6 years with T1D treated with an insulin pump followed-up in one of the hospitals of the French ADIM network between January and July 2020. ResultsOne hundred and nine patients (96 %) were equipped with a glucose monitor and 95 % (104/109) of parents stated that they were satisfied or very satisfied with their child's monitoring device, with no significant difference in satisfaction rates between flash and continuous glucose monitoring. The parameter most strongly associated with satisfaction was confidence in the reliability of the device (p = 0.008). Parents who struggled to apply the device were significantly less satisfied (p = 0.024). In real-life use, 83 % of parents (90/109) used additional adhesives, 28 % reported mild skin reactions (30/108) and 39 % severe skin reactions (42/108), 50 % stated that applying the device was not painful, and 95 % found the device easy to apply. The most commonly reported unexpected difficulties were device malfunction (by 16 respondents), the device being too large and causing scarring (6 respondents), and lengthy calibration (6 respondents). ConclusionThe vast majority of parents in this group of young children with T1D were satisfied with continuous or flash glucose monitoring. Satisfaction was strongly associated with confidence in the reliability of the device. Reported adverse effects such as skin reaction and difficulties attaching the device highlight the importance of data on real-life use.

Closed-loop insulin delivery systems, which integrate continuous glucose monitoring (CGM) and algorithms that continuously guide insulin dosing, have been shown to improve glycaemic control. The ability to predict future glucose values can further optimize such devices. In this study, we used machine learning to train models in predicting future glucose levels based on prior CGM and accelerometry data. We used data from The Maastricht Study, an observational population-based cohort that comprises individuals with normal glucose metabolism, prediabetes, or type 2 diabetes. We included individuals who underwent >48h of CGM (n = 851), most of whom (n = 540) simultaneously wore an accelerometer to assess physical activity. A random subset of individuals was used to train models in predicting glucose levels at 15- and 60-minute intervals based on either CGM data or both CGM and accelerometer data. In the remaining individuals, model performance was evaluated with root-mean-square error (RMSE), Spearman's correlation coefficient (rho) and surveillance error grid. For a proof-of-concept translation, CGM-based prediction models were optimized and validated with the use of data from individuals with type 1 diabetes (OhioT1DM Dataset, n = 6). Models trained with CGM data were able to accurately predict glucose values at 15 (RMSE: 0.19mmol/L; rho: 0.96) and 60 minutes (RMSE: 0.59mmol/L, rho: 0.72). Model performance was comparable in individuals with type 2 diabetes. Incorporation of accelerometer data only slightly improved prediction. The error grid results indicated that model predictions were clinically safe (15 min: >99%, 60 min >98%). Our prediction models translated well to individuals with type 1 diabetes, which is reflected by high accuracy (RMSEs for 15 and 60 minutes of 0.43 and 1.73 mmol/L, respectively) and clinical safety (15 min: >99%, 60 min: >91%). Machine learning-based models are able to accurately and safely predict glucose values at 15- and 60-minute intervals based on CGM data only. Future research should further optimize the models for implementation in closed-loop insulin delivery systems.

Objective: To describe the state of type 1 diabetes (T1D) in minority adults in the South Bronx, and their experience with continuous glucose monitoring (CGM). Introduction: In a recent analysis of data from the Type 1 Diabetes Exchange Registry, one notable finding was the difference in metabolic control and use of diabetes technology in patients of different socioeconomic status and racial/ethnic backgrounds. With limited data available on Hispanic and Black patients, we sought to examine the use of and experience with continuous glucose monitoring (CGM) in our hospital system, which primarily serves a low-income, minority population in the South Bronx. Methods: 68 adults with T1D who attended the Endocrinology clinic at our hospital from 2017 to 2019 were identified. Patients were contacted by telephone to complete a questionnaire regarding CGM use and satisfaction. A retrospective chart review was conducted to obtain additional demographic and clinical information. Results: Out of 68 patients with T1D in the hospital database who were contacted, 47 patients completed the questionnaire. The age range was 23 to 63 years. 42.6% were male. 59.6% were Hispanic, 19.1% Black/African American (AA), 4.3% Caucasian, and 17% not specified. 87.2% had public insurance. Overall, 48.9% of patients were actively using CGM, 19.1% had discontinued use of CGM, and 31.9% had never used CGM. In Hispanic patients using CGM, mean HbA1C was 8.2% compared to 10.1% in Hispanic non-users. In Black/AA patients using CGM, mean HbA1C was 9.2% compared to 9.9% in Black/AA non-users. Hospitalizations for acute diabetes complications were lower in CGM users (4.3%) compared to non-CGM users (16.7%). Among active CGM users, 74% rated their satisfaction as “extremely satisfied” or “very satisfied.” Perceived benefits included the prevention of hypoglycemia and awareness of inappropriate food intake. Discussion: Our study population, mainly comprised of Hispanic and Black T1D adults, showed a higher CGM utilization rate than previously reported. After stratification by socioeconomic status, CGM utilization was reported to be as low as 16% in Hispanic and 10% in Black patients with household income <$50,000/year in the T1D Exchange Registry. By comparison, 49% of our studied population possessing similar demographics was actively using CGM. This study demonstrated that CGM acceptance was high in this largely minority, low-income population in the South Bronx, and was associated with lower A1C levels, high degree of patient satisfaction and reduction in diabetes-related hospitalizations. However, glycemic control remained suboptimal overall despite CGM access. Additional strategies to optimize the utility of CGM are needed to improve clinical outcomes such as HbA1C levels in minority T1D patients.

Background: Continuous glucose monitoring (CGM) improves glycemic control. Less than half of youth with type 1 diabetes (T1D) use CGM, with disparities among minority and low-income youth. The aim of this study was to determine if trial CGM use increases uptake of personal CGM. Methods: T1D youth were provided sample CGM placement at the point of care, with CGM education and app setup. Follow-up calls at 5 and 10 days assessed CGM data, and desire to continue using CGM. Follow-up at 3-6 months recorded CGM use, CGM data, and A1c. Participants completed surveys at enrollment, 10 days, and 3 months. Differences were assessed between baseline and follow-up. Results: Of the 26 enrolled participants with T1D, 15 were CGM naive, and 11 were prior CGM users. The mean age was 14.1 ± 2.9 years, 65% male, 42% were Black, 12% were Hispanic, 65% were on public insurance, and 43% had household income of <$50,000. The median duration of diabetes was 4.6 years (interquartile range 2.4-7.7), mean baseline A1c was 10.7% ± 2.4%. After trial CGM use, 85% of participants reported wanting personal CGM, and at 3-6 months follow-up 76% had obtained one and 43% were using a personal CGM. There were no improvements in A1C or time in range, but participants reported an increase in the perceived benefits of CGM usage (4.0 vs. 4.3, p = 0.03). Conclusions: Placing a sample CGM at the point of care can improve uptake of personal CGM and may help mitigate disparities in CGM use in minority and underserved youth. Long-term studies are needed to determine how similar interventions impact glycemic control and patient outcomes. ClinicalTrials.gov: NCT04721145.

Continuous glucose monitoring (CGM) metrics and self-reported disease characteristics (severe hypoglycemic events [SHEs], HbA1c) warrant further description in people with T1D using CGM and pumps, including hybrid closed-loop systems (HCLS) . We conducted a one-time online survey of adults with T1D in the T1D Exchange Registry or online communities, where ∼50% of participants contributed up to 1 year of CGM data. Patients were asked about their medical history (SHEs, HbA1c) , while glucose management indicator (GMI) , prolonged hypoglycemic events (&amp;lt;54 mg/dL) , time in and below range (TIR/TBR) , and coefficient of variation (CV) were derived from CGM data. Patients who completed the survey and contributed CGM data (N=926) had a mean age of 42 y and T1D duration of 25 y; 73% were female; 96% were white; 94% had ≥1 year of CGM use. Mean HbA1c was 6.6% (69.0% had HbA1c &amp;lt;7%) . While most patients met consensus glycemic targets (HbA1c, GMI, TIR, TBR, and CV) , with higher proportions observed in those using HCLS pumps than in those using pump + CGM (not HCLS) and MDI + CGM (Table) , patients continued to have significant hypoglycemia based on CGM data and an average of 1.1 SHEs in the prior year. Despite improvements in glycemic control (TIR, TBR, and self-reported HbA1c) with advanced technologies, many patients still cannot achieve clinical targets and experience significant hypoglycemia, highlighting the unmet need for novel T1D treatments. Disclosure L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc. K.S.M.Chapman: None. D.Finan: None. R.M.Bergenstal: Advisory Panel; Hygieia, Medtronic, Roche Diabetes Care, Zealand Pharma A/S, Consultant; Abbott Diabetes, Ascensia Diabetes Care, Bigfoot Biomedical, Inc., CeQur SA, Dexcom, Inc., Eli Lilly and Company, Novo Nordisk, Onduo LLC, Sanofi, United HealthCare Services, Inc., Research Support; Abbott Diabetes, Dexcom, Inc., Eli Lilly and Company, Insulet Corporation, Medtronic, Novo Nordisk, Sanofi. J.Liu: None. L.Titievsky: Employee; Intercept Pharmaceuticals, Inc., Pfizer Inc., Vertex Pharmaceuticals Incorporated, Stock/Shareholder; Intercept Pharmaceuticals, Inc., Pfizer Inc., Vertex Pharmaceuticals Incorporated. K.Hagan: Employee; Vertex Pharmaceuticals Incorporated. T.Liu: Employee; Takeda Pharmaceutical Company Limited, Vertex Pharmaceuticals Incorporated, Stock/Shareholder; Seattle Genetics, Inc. K.Chandarana: Employee; Vertex Pharmaceuticals Incorporated. J.L.Gaglia: Advisory Panel; Dompé, Regeneron Pharmaceuticals Inc., Consultant; Vertex Pharmaceuticals Incorporated, Research Support; Avotres Inc., Dompé, Janssen Research &amp; Development, LLC, Provention Bio, Inc., Stock/Shareholder; Vertex Pharmaceuticals Incorporated. W.Wolf: None. J.Bispham: Employee; PPD Inc., T1D Exchange.

Background: Continuous glucose monitoring (CGM) improves glycemic control for youth with type 1 diabetes (T1D) . Despite these benefits, less than half of youth with T1D use CGM. Objective: To determine if trial CGM use (10-days) increases CGM uptake and is associated with improved glycemic control among minority youth and youth with poorly controlled T1D. We also examined barriers to CGM use. Methods: This prospective study was conducted at an academic Pediatric Diabetes Center. Youth with T1D for more than 3 months, with no previous CGM usage, or no CGM usage in the last year were enrolled. Diabetes staff placed CGM at the point of care (POC) and provided CGM education. Barriers to prior CGM use, hemoglobin A1c (HbA1c) , and demographic information were recorded. Participants received 5 and 10-day follow up calls from the diabetes team to review glycemic trends. At 3 months, participants' use of CGM and HbA1c were recorded. Results: Youth with T1D (n=22) were enrolled (13 first time CGM users, 9 past users) , mean age 14.1years (SD 3.1) , 41% non-Hispanic black, 68% female, mean diabetes duration 6.3 ± 4.4years, and baseline mean HbA1c of 10.8%. Patient-cited barriers to prior CGM use included technical difficulties (n=5) , unawareness of CGM (n=4) , difficulty obtaining CGM (n=4) , general apprehension (n=3) , not wanting devices (n=3) , and pain, fear of needles, and new diabetes diagnosis (n=1 each) . Of participants, 20 completed some follow-up, and 18/20 (90%) cited wanting to use CGM long-term. Of 13 participants who completed 3 and/or 6-month follow-up visits, only 9 were actively using CGM. Further barriers to use included insurance issues (n=2) and CGM falling off (n=1) . There was no change in mean HbA1c from baseline to follow-up (10.8 ±2.4% vs. 10.3 ±2.3%, p=0.46) . Conclusion: There are many barriers to CGM uptake in youth. Providing a trial use of CGM at the POC may increase uptake of CGM use in at-risk diabetes populations, but further investigation of additional barriers that impact long-term adherence to CGM is needed. Disclosure T.L.Lin: None. J.A.Manfredo: None. N.Illesca: None. K.Abiola: None. N.Hwang: None. M.Seel: None. E.A.Brown: None. R.M.Wolf: Consultant; NEMA Research, Research Support; Dexcom, Inc. Funding Johns Hopkins Children's Center Innovation Award, and Dexcom

The key part to strengthen blood glucose management is comprehensive and careful blood glucose monitoring. Continuous glucose monitoring (CGM) is able to continuously monitor glucose levels of patients through the implantation of a glucose sensor in subcutaneous tissue fluid on which a chemical reaction is triggered, leading to subsequent transformation into electrical signals. Correct and standardized CGM operation can significantly reduce the burden of clinical nursing. At present, CGM has been widely used in clinical practice. However, the success of CGM usage is influenced by many factors (such as the effectiveness of sensor, aseptic operation or not, sensor error, etc.) in actual practice. Therefore, medical personnel should apply CGM in accordance with standard operating procedures and eliminate various alarms in a timely manner, ensuring accurate and valid CGM results. Because Medtronic’s CGM system is widely used in China, this chapter focuses on the operation standards of Medtronic CGM systems.