Continuous Glucose Monitoring Decreases Hypoglycemia Avoidance Behaviors,but Not Worry in Parents of Youth With New Onset Type 1 Diabetes

Background:Existing research shows that hypoglycemia fear (HF) is common in parents of children with established type 1 diabetes (T1D). We examined parental HF in the T1D recent-onset period and evaluated whether continuous glucose monitoring (CGM) adoption relates to improved outcomes of parental HF.Methods:In TACKLE-T1D, a prospective study of five- to nine-year olds with recent-onset T1D, parents completed the Hypoglycemia Fear Survey-Parents (HFS-P) at baseline (T1) and 6 (T2) and 12 (T3) months post-baseline. The HFS-P measures worry about hypoglycemia (HFS-Worry score) as well as hypoglycemia avoidance behaviors (HFS-Behavior score). We recorded CGM start dates for youth during the same time period through medical record review.Results:Between T1 and T2, 31 youth (32.3%) initiated CGM therapy, and between T2 and T3, an additional 17 youth (17.7%) began using CGM, leaving 48 youth who never initiated CGM therapy (50%) in the recent-onset period. Parents reported moderate HFS-Worry scores at T1 (32.9 ± 11.9), which increased between T1 and T2 (37.6 ± 11.4, P < .001) and plateaued between T2 and T3 (37.7 ± 12.4, P = .89). In contrast, parental HFS-Behavior scores decreased between T1 (33.1 ± 5.8) and T2 (32.2 ± 6.0, P = .005) and plateaued between T2 and T3 (32.2 ± 6.0, P = .95). Baseline HFS-Behavior and Worry scores were associated with increased adoption of CGM between T1-T2 and T2-T3, respectively. Parents of children initiating CGM therapy between T1 and T2 showed the largest decrease in HFS-Behavior (P = .03).Conclusions:Initiating CGM therapy within the first 12 months of T1D may help reduce parents’ use of hypoglycemia avoidance behaviors, but has little effect on parents’ hypoglycemia worry.     

Use of Personal Continuous Glucose Monitoring Device Is Associated With Reduced Risk of Hypoglycemia in a 16-Week Clinical Trial of People With Type 1 Diabetes Using Continuous Subcutaneous Insulin Infusion

Aims:Continuous glucose monitoring (CGM) has the potential to promote diabetes self-management at home with a better glycemic control as outcome. Investigation of the effect of CGM has typically been carried out based on randomized controlled trials with prespecified CGM devices on CGM-naïve participants. The aim of this study was to investigate the effect on glycemic control in people using their personal CGM before and during the trial.Materials and Methods:Data from the Onset 5 trial of 472 people with type 1 diabetes using either their personal CGM (n = 117) or no CGM (n = 355) and continuous subcutaneous insulin infusion in a 16-week treatment period were extracted. Change from baseline in glycated hemoglobin A1c (HbA_1c), number of hypoglycemic episodes, and CGM metrics at the end of treatment were analyzed with analysis of variance repeated-measures models.Results:Use of personal CGM compared with no CGM was associated with a reduction in risk of documented symptomatic hypoglycemia (event rate ratio: 0.82; 95% CI: 0.69-0.97) and asymptomatic hypoglycemia (event rate ratio: 0.72; 95% CI: 0.53-0.97), reduced time spent in hypoglycemia (P = .0070), and less glycemic variability (P = .0043) without a statistically significant increase in HbA_1c (P = .2028).Conclusions:Results indicate that use of personal CGM compared with no CGM in a population of type 1 diabetes is associated with a safer glycemic control without a statistically significantly deteriorated effect on HbA_1c, which adds to the evidence about the real-world use of CGM, where device type is not prespecified, and users are not CGM naïve.     

Perceived Burdens and Benefits Associated With Continuous Glucose Monitor Use in Type 1 Diabetes Across the Lifespan

Background:Continuous glucose monitors (CGMs) help people with type 1 diabetes (T1D) improve their glycemic profiles but are underutilized. To better understand why, perceived CGM burdens and benefits in nonusers versus users with type 1 diabetes across the lifespan were assessed.Methods:Burdens (BurCGM) and benefits of CGM (BenCGM) questionnaires were completed during T1D outpatient visits (n = 1334) from February 2019 to February 2020. Mean scores were calculated (scale one to five; higher scores reflect greater perceived burdens/benefits). Data were collected from medical records including glycated hemoglobin (HbA1c) within 3 months of the visit.Results:Individuals of all ages using CGM described more benefits and less burdens (mean scores 4.48 and 1.69, respectively) when compared with those who were not using CGM (mean score 4.19 and 2.35, respectively) (P < .001). There were no differences in burdens or benefits by sex. Non-CGM users aged ≥50 years had higher mean BurCGM scores than those aged <50 years (P = .004); the cost was the greatest barrier in those aged 27+ years. Other burdens were readings not trusted, painful to wear, and takes too much time to use. For those aged 65+, nonusers versus users, 18.5% versus 3.1% agreed with “it was too hard to understand CGM information,” and 21.4% versus 7.7% agreed that CGM causes too much worry. Mean HbA1C was lower in CGM users (8.1%) versus non-CGM users (mean A1c 9.1%; P < .001).Conclusions:CGM was perceived as having more burdens and less benefits in nonusers, with differences in concerns varying across the lifespan. Lower costs and age-appropriate education are needed to address these barriers.     

Professional Continuous Glucose Monitoring in Subjects with Type 1 Diabetes: Retrospective Hypoglycemia Detection

Background

An important task in diabetes management is detection of hypoglycemia. Professional continuous glucose monitoring (CGM), which produces a glucose reading every 5 min, is a powerful tool for retrospective identification of unrecognized hypoglycemia. Unfortunately, CGM devices tend to be inaccurate, especially in the hypoglycemic range, which limits their applicability for hypoglycemia detection. The objective of this study was to develop an automated pattern recognition algorithm to detect hypoglycemic events in retrospective, professional CGM.

Methods

Continuous glucose monitoring and plasma glucose (PG) readings were obtained from 17 data sets of 10 type 1 diabetes patients undergoing insulin-induced hypoglycemia. The CGM readings were automatically classified into a hypoglycemic group and a nonhypoglycemic group on the basis of different features from CGM readings and insulin injection. The classification was evaluated by comparing the automated classification with PG using sample-based and event-based sensitivity and specificity measures.

Results

With an event-based sensitivity of 100%, the algorithm produced only one false hypoglycemia detection. The sample-based sensitivity and specificity levels were 78% and 96%, respectively.

Conclusions

The automated pattern recognition algorithm provides a new approach for detecting unrecognized hypoglycemic events in professional CGM data. The tool may assist physicians and diabetologists in conducting a more thorough evaluation of the diabetes patient’s glycemic control and in initiating necessary measures for improving glycemic control.     

Glycemic Metrics Derived From Intermittently Scanned Continuous Glucose Monitoring

Background:Glucose data from intermittently scanned continuous glucose monitoring (isCGM) is a combination of scanned and imported glucose values. The present knowledge of glycemic metrics originate mostly from glucose data from real-time CGM sampled every five minutes with a lack of information derived from isCGM.Methods:Glucose data obtained with isCGM and hemoglobin A1c (HbA1c) were obtained from 169 patients with type 1 diabetes. Sixty-one patients had two observations with an interval of more than three months.Results:The best regression line of HbA1c against mean glucose was observed from 60 days prior to HbA_1c measurement as compared to 14, 30, and 90 days. The difference between HbA1c and estimated HbA1c (=glucose management indicator [GMI]) first observed correlated with the second observation (R2 0.61, P < .001). Time in range (TIR, glucose between 3.9 and 10 mmol/L) was significantly related to GMI (R2 0.87, P < .001). A TIR of 70% corresponded to a GMI of 6.8% (95% confidence interval, 6.3-7.4). The fraction of patients with the optimal combination of TIR >70% and time below range (TBR) <4% was 3.6%. The fraction of patients with TBR>4% was four times higher for those with high glycemic variability (coefficient of variation [CV] >36%) than for those with lower CV.Conclusion:The individual difference between HbA1c and GMI was reproducible. High glycemic variability was related to increased TBR. A combination of TIR and TBR is suggested as a new composite quality indicator.     

Effect of Professional CGM (pCGM) on Glucose Management in Type 2 Diabetes Patients in Primary Care

Background:Little data exists regarding the impact of continuous glucose monitoring (CGM) in the primary care management of type 2 diabetes (T2D). We initiated a quality improvement (QI) project in a large healthcare system to determine the effect of professional CGM (pCGM) on glucose management. We evaluated both an MD and RN/Certified Diabetes Care and Education Specialist (CDCES) Care Model.Methods:Participants with T2D for >1 yr., A1C ≥7.0% to <11.0%, managed with any T2D regimen and willing to use pCGM were included. Baseline A1C was collected and participants wore a pCGM (Libre Pro) for up to 2 weeks, followed by a visit with an MD or RN/CDCES to review CGM data including Ambulatory Glucose Profile (AGP) Report. Shared-decision making was used to modify lifestyle and medications. Clinic follow-up in 3 to 6 months included an A1C and, in a subset, a repeat pCGM.Results:Sixty-eight participants average age 61.6 years, average duration of T2D 15 years, mean A1C 8.8%, were identified. Pre to post pCGM lowered A1C from 8.8% ± 1.2% to 8.2% ± 1.3% (n=68, P=0.006). The time in range (TIR) and time in hyperglycemia improved along with more hypoglycemia in the subset of 37 participants who wore a second pCGM. Glycemic improvement was due to lifestyle counseling (68% of participants) and intensification of therapy (65% of participants), rather than addition of medications.Conclusions:Using pCGM in primary care, with an MD or RN/CDCES Care Model, is effective at lowering A1C, increasing TIR and reducing time in hyperglycemia without necessarily requiring additional medications.     

Pediatric Medicaid Patients With Type 1 Diabetes Benefit From Continuous Glucose Monitor Technology

Background:We determined the uptake rate of continuous glucose monitors (CGMs) and examined associations of clinical and demographic characteristics with CGM use among patients with type 1 diabetes covered by Colorado Medicaid during the first two years of CGM coverage with no out-of-pocket cost.Method:We retrospectively reviewed data from 892 patients with type 1 diabetes insured by Colorado Medicaid (Colorado Health Program [CHP] and CHP+, Colorado Medicaid expansion). Demographics, insulin pump usage, CGM usage, and hemoglobin A1c (A1c) were extracted from the medical record. Data downloaded into CGM software at clinic appointments were reviewed to determine 30-day use prior to appointments. Subjects with some exposure to CGM were compared to subjects never exposed to CGM, and we examined the effect of CGM use on glycemic control.Results:Twenty percent of subjects had some exposure to CGM with a median of 22 [interquartile range 8, 29] days wear. Sixty one percent of CGM users had >85% sensor wear. Subjects using CGM were more likely to be younger (P < .001), have shorter diabetes duration (P < .001), and be non-Hispanic White (P < .001) than nonusers. After adjusting for age and diabetes duration, combined pump and CGM users had a lower A1c than those using neither technology (P = .006). Lower A1c was associated with greater CGM use (P = .002) and increased percent time in range (P < .001).Conclusion:Pediatric Medicaid patients successfully utilized CGM. Expansion of Medicaid coverage for CGM may help improve glycemic control and lessen disparities in clinical outcomes within this population.     

Use of Continuous Glucose Monitoring to Estimate Insulin Requirements in Patients with Type 1 Diabetes Mellitus During a Short Course of Prednisone

Background

Insulin requirements to maintain normoglycemia during glucocorticoid therapy and stress are often difficult to estimate. To simulate insulin resistance during stress, adults with type 1 diabetes mellitus (T1DM) were given a three-day course of prednisone.

Methods

Ten patients (7 women, 3 men) using continuous subcutaneous insulin infusion pumps wore the Medtronic Minimed CGMS^® (Northridge, CA) device. Mean (standard deviation) age was 43.1 (14.9) years, body mass index 23.9 (4.7) kg/m², hemoglobin A1c 6.8% (1.2%), and duration of diabetes 18.7 (10.8) years. Each patient wore the CGMS for one baseline day (day 1), followed by three days of self-administered prednisone (60 mg/dl; days 2–4), and one post-prednisone day (day 5).

Results

Analysis using Wilcoxon signed rank test (values are median [25th percentile, 75th percentile]) indicated a significant difference between day 1 and the mean of days on prednisone (days 2–4) for average glucose level (110.0 [81.0, 158.0] mg/dl vs 149.2 [137.7, 168.0] mg/dl; p = .022), area under the glucose curve and above the upper limit of 180 mg/dl per day (0.5 [0, 8.0] mg/dl·d vs 14.0 [7.7, 24.7] mg/dl·d; p = .002), and total daily insulin dose (TDI) , (0.5 [0.4, 0.6] U/kg·d vs 0.9 [0.8, 1.0] U/kg·d; p = .002). In addition, the TDI was significantly different for day 1 vs day 5 (0.5 [0.4, 0.6] U/kg·d vs 0.6 [0.5, 0.8] U/kg·d; p = .002). Basal rates and insulin boluses were increased by an average of 69% (range: 30–100%) six hours after the first prednisone dose and returned to baseline amounts on the evening of day 4.

Conclusions

For adults with T1DM, insulin requirements during prednisone induced insulin resistance may need to be increased by 70% or more to normalize blood glucose levels.     

Improved Real-World Glycemic Control With Continuous Glucose Monitoring System Predictive Alerts

Background:Most standalone real-time continuous glucose monitoring (RT-CGM) systems provide predictive low and high sensor glucose (SG) threshold alerts. The durations and risk of low and high SG excursions following Guardian™ Connect CGM system predictive threshold alerts were evaluated.Methods:Continuous glucose monitoring system data uploaded between January 2, 2017 and May 22, 2018 by 3133 individuals using multiple daily injections (MDIs) or continuous subcutaneous insulin infusion (CSII) therapy were deidentified and retrospectively analyzed. Glucose excursions were defined as SG values that went beyond a preset low or high SG threshold for ≥15 minutes. For a control group, thresholds were based on the median of the low SG threshold limit (70 mg/dL) and the high SG threshold limit (210 mg/dL) preset by all system users. During periods when alerts were not enabled, timestamps were identified when a predictive alert would have been triggered. The time before low horizon was 17.5 minutes and the time before high horizon was 15 minutes, of all users who enabled alerts. Excursions occurring after a low SG or high SG predictive alert were segmented into prevented, ≤20, 20-60, and >60 minutes.Results:Excursions were prevented after 59% and 39% of low and high SG predictive alerts, respectively. The risk of a low or high excursion occurring was 1.9 (P < 0.001, 95% CI, 1.88-1.93) and 3.3 (P < 0.001, 95% CI, 3.20-3.30) times greater, respectively, when alerts were not enabled.Conclusions:The predictive alerts of the RT-CGM system under study can help individuals living with diabetes prevent some real-world low and high SG excursions. This can be especially important for those unable to reach or maintain glycemic control with basic RT-CGM or CSII therapy.     

Lessons Learned From a Pilot RCT of Simultaneous Versus Delayed Initiation of Continuous Glucose Monitoring in Children and Adolescents With Type 1 Diabetes Starting Insulin Pump Therapy

Uncertainty remains about effectiveness of continuous glucose monitoring (CGM) in pediatric type 1 diabetes (T1D). Success with CGM is related to CGM adherence, which may relate to readiness to make the behavior changes required for effective use. We hypothesize that readiness for change will be greater at initiation of insulin pump therapy than in established pump users, and that this will predict CGM adherence. Our objective was to evaluate the feasibility of a randomized controlled trial (RCT) in children with established T1D comparing simultaneous pump and CGM initiation to standard pump therapy with delayed CGM initiation. We randomized participants to simultaneous pump and CGM initiation or to standard pump therapy with the option of adding CGM 4 months later. CGM adherence was tracked via web-based download and readiness for change assessed with the SOCRATES questionnaire. Of 41 eligible children, 20 agreed to participate; 15 subjects completed the study (7 males; baseline age 11.8 ± 4.0 years; T1D duration 2.7 ± 2.7 years; mean A1C 8.2 ± 0.8%). Six of 8 simultaneous group subjects used CGM > 60% of the time for 4 months compared to 1 of 7 delayed group subjects (P = .02). Using SOCRATES, we could assign 87-100% of subjects to a single motivation stage at baseline and 4 months. This pilot study demonstrates the feasibility of randomizing pump naïve children and adolescents with established T1D to simultaneous pump and CGM initiation versus standard pump therapy with delayed CGM initiation. Lessons from this pilot study were used to inform development of a full-scale multicenter RCT.     

Healthcare Utilization,Costs, and Adverse Events of Real-Time Continuous Glucose Monitoring versus Traditional Blood Glucose Monitoring Among US Adults with Type 1 Diabetes

Objective:To compare healthcare utilization, costs, and incidence of diabetes-specific adverse events (ie, hyperglycemia, diabetic ketoacidosis, and hypoglycemia) in type 1 diabetes adult patients using real-time continuous glucose monitoring (rtCGM) versus traditional blood glucose monitoring (BG).Methods:Adult patients (≥18 years old) with type 1 diabetes in a large national administrative claims database between 2013 and 2015 were identified. rtCGM patients with 6-month continuous health plan enrollment and ≥1 pharmacy claim for insulin during pre-index and post-index periods were propensity-score matched with BG patients. Healthcare utilization associated with diabetic adverse events were examined. A difference-in-difference (DID) method was used to compare the change in costs between rtCGM and BG cohorts.Results:Six-month medical costs for rtCGM patients (N = 153) increased from pre- to post-index period, while they decreased for matched BG patients (N = 153). DID analysis indicated a $2,807 (P = .062) higher post-index difference in total medical costs for rtCGM patients. Pharmacy costs for both cohorts increased. DID analysis indicated a $1,775 (P < .001) higher post-index difference in pharmacy costs for rtCGM patients. The incidence of hyperglycemia for both cohorts increased minimally from pre- to post-index period. The incidence of hypoglycemia for rtCGM patients decreased, while it increased marginally for BG patients. Inpatient hospitalizations for rtCGM and BG patients increased and decreased marginally, respectively.Conclusions:rtCGM users had non-significantly higher pre-post differences in medical costs but significantly higher pre-post differences in pharmacy costs (mostly due to the rtCGM costs themselves) compared to BG users. Changes in adverse events were minimal.     

The Benefits of Continuous Glucose Monitoring and a Glucose Monitoring Schedule in Individuals with Type 1 Diabetes during Recreational Diving

Background

Our objective is to evaluate the Medtronic CGMS^® continuous glucose monitoring system and plasma glucose (PG) measurement performed in a monitoring schedule as tools to identify individuals with type 1 diabetes at risk when diving.

Methods

We studied 24 adults, 12 type 1 diabetes subjects and 12 controls, during 5 recreational scuba dives performed on 3 consecutive days. The CGMS was used by all participants on all the days and all the dives. Comparisons were made between PG performed in a monitoring schedule during the days of diving, self-monitored blood glucose (SMBG) performed 2 weeks prior to diving, and the CGMS during the study.

Results

One hundred seventeen dives were performed. Hypoglycemia (<70 mg/dl) was found in six individuals and on nine occasions. However, no symptoms of hypoglycemia were present during or immediately postdiving. In one case, repetitive hypoglycemia prediving gave rise to a decision not to dive. None of the dives were aborted. The number of hypoglycemic episodes, 10 min prediving or immediately postdiving, were related to the duration of diabetes, r = 0.83 and p =0.01, and the percentage of SMBG values below target (<72 mg/dl), r = 0.65 and p =0.02. Moreover, the number of hypoglycemic episodes was also related to the total duration below low limit (<70 mg/dl), measured by the CGMS, r =0.74 and p =0.006.

Conclusion

Safe dives are possible to achieve by well-informed, well-controlled individuals with type 1 diabetes. Using downloaded SMBG, CGMS, and repetitive PG in a monitoring schedule, it is possible to identify those subjects who are suitable for diving.     

Exploring Parental Experiences of Using a Do-It-Yourself Solution for Continuous Glucose Monitoring Among Children and Adolescents With Type 1 Diabetes: A Qualitative Study

Background:MiaoMiao (MM) is a Bluetooth transmitter, which when paired with a smart phone/device, converts the Abbott FreeStyle Libre flash glucose monitoring system into a Do-It-Yourself (DIY) continuous glucose monitor (CGM). Families are increasingly adopting DIY CGM solutions, but little is known about parent and child experiences with these add-on technologies. We aimed to explore experiences of families using MM-CGM including challenges faced and their advice to others who may choose to use the technology.Methods:Between May and July 2019, we conducted 12 semistructured interviews (in person or via video conference) with parents of children (aged ≤16 years) with type 1 diabetes using MM-CGM. Interviews were audio recorded; professionally transcribed and key themes were identified through thematic analysis.Results:Overall, parents used MM-CGM to proactively manage their child’s blood glucose. In all participants, this led to a perceived decrease in frequency of hypoglycemia. Participants reported that the visibility and easy access to blood glucose readings, glucose trends, and customized alarms on parent’s phones decreased their disease burden and improved their sleep quality. Common barriers to using MM-CGM included difficulty of the setting up process, connectivity issues, and lack of support from medical teams.Conclusion:This study highlights the potential feasibility of using a DIY CGM system like MM-CGM, which could be an empowering and cost-effective tool for enabling remote monitoring of blood glucose in real time.     

Recommendations for Standardizing Glucose Reporting and Analysis to Optimize Clinical Decision Making in Diabetes: The Ambulatory Glucose Profile

Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes mellitus. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardizing the analysis and presentation of glucose monitoring data, with the initial focus on data derived from continuous glucose monitoring systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile, and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This article provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.     

A Novel Algorithm for Prediction and Detection of Hypoglycemia Based on Continuous Glucose Monitoring and Heart Rate Variability in Patients With Type 1 Diabetes

Background:Hypoglycemia is a common and serious side effect of insulin therapy in patients with diabetes. Early detection and prediction of hypoglycemia may improve treatment and avoidance of serious complications. Continuous glucose monitoring (CGM) has previously been used for detection of hypoglycemia, but with a modest accuracy. Therefore, our aim was to investigate whether a novel algorithm that adds information of the complex dynamic/pattern of heart rate variability (HRV) could improve the accuracy of hypoglycemia as detected by a CGM device.Methods:Data from 10 patients with type 1 diabetes studied during insulin-induced hypoglycemia were obtained. Blood glucose samples were used as reference. HRV patterns and CGM data were combined in a mathematical prediction algorithm. Detection of hypoglycemic periods, performed by the algorithm, was treated as a pattern recognition problem and features/patterns derived from HRV and CGM prior to each blood glucose sample were used to decide if that particular point in time was below the hypoglycemic threshold of 3.9 mmol/L.Results:A total of 903 samples were analyzed by the novel algorithm, which yielded a sensitivity of 79% and a specificity of 99%. The algorithm was able to detect 16/16 hypoglycemic events with no false positives and had a lead time of 22 minutes as compared to the CGM device.Conclusions:Detection accuracy and lead time were significantly improved by the novel algorithm compared to that of CGM alone.     

The Impact of Continuous Glucose Monitoring on Low Interstitial Glucose Values and Low Blood Glucose Values Assessed by Point-of-care Blood Glucose Meters: Results of a Crossover Trial

In a randomized crossover trial the impact of continuous glucose monitoring (CGM) was tested on the occurrence of low blood glucose values measured by point of care (POC) measurement and on low glucose values measured by CGM in the interstitial fluid. A total of 41 type 1 diabetic patients (age 42.0 ± 11.4 years, diabetes duration 15.3 ± 10.1 years, A1c 8.2 ± 1.4%) used a CGM system (Dexcom SEVEN PLUS system) twice. In first study phase (CGM blind), patients were blind regarding the CGM current glucose levels and were not alerted when critical glucose values were reached. In the second phase (CGM real time), patients had access to current glucose levels and were alerted if critical glucose values were reached. During CGM real time the proportion of hypoglycemic POC blood glucose values were significantly reduced (7.5 ± 5.6% vs 10.1 ± 7.5%; P = .04), whereas the proportion of euglycemic blood glucose values were significantly enhanced (73.7 ± 18.3% vs 68.3 ± 12.1%; P = .01). The duration of low glucose periods in the interstitial fluid was significantly lower in the CGM real time phase (125 ± 89 vs 181 ± 125 minutes per day; P = .005). The time until a low blood glucose was detected by POC measurement was shortened by 33.2 ± 76.1 minutes (P = .03). The study demonstrated that CGM is able to not only reduce duration of hypoglycemia measured by CGM in interstitial fluid, but also reduce the proportion of low POC blood glucose measurements. In addition, hypoglycemia can be detected earlier.