Accuracy Of Continuous Glucose Monitoring Research Articles

Accuracy of continuous glucose monitoring systems in intensive care unit patients: a scoping review.

Glycemic control poses a challenge in intensive care unit (ICU) patients and dysglycemia is associated with poor outcomes. Continuous glucose monitoring (CGM) has been successfully implemented in the type 1 diabetes out-patient setting and renewed interest has been directed into the transition of CGM into the ICU. This scoping review aimed to provide an overview of CGM accuracy in ICU patients to inform future research and CGM implementation. We systematically searched PubMed and EMBASE between 5th of December 2023 and 21st of May 2024 and reported findings in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline for scoping reviews (PRISMA-ScR). We assessed studies reporting the accuracy of CGM in the ICU and report study characteristics and accuracy outcomes. We identified 2133 studies, of which 96 were included. Most studies were observational (91.7%), conducted in adult patients (74%), in mixed ICUs (47.9%), from 2014 and onward, and assessed subcutaneous CGM systems (80%) using arterial blood samples as reference test (40.6%). Half of the studies (56.3%) mention the use of a prespecified reference test protocol. The mean absolute relative difference (MARD) ranged from 6.6 to 30.5% for all subcutaneous CGM studies. For newer factory calibrated CGM, MARD ranged from 9.7 to 20.6%. MARD for intravenous CGM was 5-14.2% and 6.4-13% for intraarterial CGM. In this scoping review of CGM accuracy in the ICU, we found great diversity in accuracy reporting. Accuracy varied depending on CGM and comparator, and may be better for intravascular CGM and potentially lower during hypoglycemia.

9391 Clinical Accuracy Of Continuous Glucose Monitoring In Post-kidney Transplant Patients With Type 2 Diabetes

Abstract Disclosure: Q. Aziz: None. K. Batra: None. S. Fatima: None. J. Splinter: None. A.L. Champion: None. A.M. Kumar: None. K.E. Izuora: Research Investigator; Self; Novo Nordisk. Background: Continuous glucose monitoring (CGM) devices provide real time blood glucose data to guide therapy in patients with diabetes mellitus. Diabetic nephropathy is a major complication of diabetes which can eventually lead to End Stage Renal Disease (ESRD). Kidney transplant is a treatment option for ESRD and patients who undergo kidney transplant are exposed to anti-rejection therapy, including high-dose steroids, resulting in significant fluctuations in blood glucose. Having a reliable system for monitoring blood glucose continuously, such as a CGM, can provide valuable information to guide optimal diabetes management. Objective This study aims to compare the clinical accuracy of the CGM data with the Point of Care Testing (POCT) glucose values as a reference among post kidney transplant patients with Type 2 diabetes mellitus (T2DM). Methodology This study was conducted at an academic medical center from September 2023 to January 2024, enrolling subjects ≥ 18 years, diagnosed with T2DM , admitted for kidney transplant. Following informed consent, a blinded CGM (Freestyle Libre Pro®) was applied. We collected all POCT and serum glucose values and downloaded corresponding CGM glucose data. Using matched pairs between CGM and POCT glucose values, bias and absolute relative differences (ARD) were calculated. Based on the ARD, the Clarke error grid (CEG) analysis was conducted to quantify the clinical accuracy of CGM and POCT by assigning glucose data points into 5 zones A, B, C, D, and E. Summary statistics for numeric variables included mean and standard deviation, whereas categorical variables were described as counts and proportions. All analyses were performed using SAS, 9.4 version. Results: A total of 22 subjects were analyzed after excluding one patient due to CGM malfunction. Subjects were 58±9.69 years old, and 82% were males. The mean body mass index was 30±6.41 kg/m2 and mean HbA1c was 6.7 ± 1.07%, at baseline. The mean duration of diabetes and ESRD were 19±10.6 years and 3±2.27 years respectively. Average CGM wear time was 76±24.5 hours. The CEG comparing CGM values with POCT values showed 83.79% values in zone A, 15.29% in zone B (combined =99.08%) with the Mean Absolute Relative Difference (MARD) of 13.24%. The CEG comparing CGM values with serum glucose showed 83.1% values in zone A, 16.9% in zone B (combined =100%) with the MARD of 13.10%. Conclusion: Our results indicate that CGM values are comparable to the POCT and serum glucose values in post kidney transplant patients with T2DM receiving high dose steroids. Therefore, use of CGMs should be considered as a useful tool, providing timely information to guide prompt interventions and improve outcomes in this patient population. Presentation: 6/3/2024

6521 Continuation of Continuous Glucose Monitors in Hospitalized Diabetic Patients Decreased the Incidence of Hypoglycemia

Abstract Disclosure: C.E. DeClue: None. S. Bao: None. Objective: Glycemic control improves patient outcomes in hospitalized patients, and this is generally achieved by monitoring point-of-care (POC) capillary glucose levels. In the outpatient setting, continuous glucose monitoring (CGM) devices have shown improved glycemic control in diabetic patients, but their evidence in hospitalized patients is lacking. Methods: To evaluate CGM accuracy and safety of use in the inpatient setting, 567 consults were analyzed in a single-center inpatient diabetes service between November 2022 and January 2023. Patients were included if managed with multiple daily injections or insulin pump therapy and separated into four groups based on CGM continuation and type of diabetes. POC glucose and incidence of hypoglycemia were recorded over 72 hours from the time of consultation. Results: Forty-six Type-1 (T1DM) and 72 Type-2 (T2DM) diabetic patients were included in this study, with average hemoglobin A1c of 8.6% and 9.0%, respectively. Both diabetic groups showed an average POC glucose that was not statistically different based on CGM continuation (185 mg/dL for T1DM and 187 mg/dL for T2DM continued on CGM versus 183 mg/dL for T1DM and 188 mg/dL for T2DM not using CGM). However, only 2 of the 18 T1DM patients continued on CGM experienced hypoglycemia, whereas 17 of the 28 T1DM patients not using CGM experienced at least 1 hypoglycemic event. Similarly, only 2 of the 20 T2DM patients continued on CGM experienced hypoglycemia, whereas 13 of the 52 patients not using CGM experienced at least 1 hypoglycemic event. Additionally, less glucose variability was observed in both T1DM and T2DM patients continued on CGM (average standard deviation of 64 mg/dL and 55 mg/dL, respectively) compared to those not using CGM (average standard deviation of 84 mg/dL and 62 mg/dL, respectively). Conclusion: CGM has great potential to improve patient care and nursing workload in the hospital, but the safety and accuracy are not yet well-established. In this study, there seemed to be a statistically insignificant trend to less glycemic variability for CGM users despite no glycemic difference on average POC testing. Importantly, significantly fewer hypoglycemic events were observed in patients continued on CGM devices regardless of type of diabetes or baseline glycemic control. This study adds further evidence to the growing body of work supporting improved safety of CGM utilization in hospitalized diabetic patients. Presentation: 6/1/2024

Accuracy of Continuous Glucose Monitoring in Hemodialysis Patients With Diabetes.

In the general population, continuous glucose monitoring (CGM) provides convenient and less-invasive glucose measurements than conventional self-monitored blood glucose and results in reduced hypoglycemia and hyperglycemia and increased time in target glucose range. However, accuracy of CGM versus blood glucose is not well established in hemodialysis patients. Among 31 maintenance hemodialysis patients with diabetes hospitalized from October 2020 to May 2021, we conducted protocolized glucose measurements using Dexcom G6 CGM versus blood glucose, with the latter measured before each meal and at night, plus every 30-min during hemodialysis. We examined CGM-blood glucose correlations and agreement between CGM versus blood glucose using Bland-Altman plots, percentage of agreement, mean and median absolute relative differences (ARDs), and consensus error grids. Pearson and Spearman correlations for averaged CGM versus blood glucose levels were 0.84 and 0.79, respectively; Bland-Altman showed the mean difference between CGM and blood glucose was ∼+15 mg/dL. Agreement rates using %20/20 criteria were 48.7%, 47.2%, and 50.2% during the overall, hemodialysis, and nonhemodialysis periods, respectively. Mean ARD (MARD) was ∼20% across all time periods; median ARD was 19.4% during the overall period and was slightly lower during nonhemodialysis (18.2%) versus hemodialysis periods (22.0%). Consensus error grids showed nearly all CGM values were in clinically acceptable zones A (no harm) and B (unlikely to cause significant harm). In hemodialysis patients with diabetes, although MARD values were higher than traditional optimal analytic performance thresholds, error grids showed nearly all CGM values were in clinically acceptable zones. Further studies are needed to determine whether CGM improves outcomes in hemodialysis patients.

Accuracy of continuous glucose monitoring in the hospital setting: an observational study.

Continuous glucose monitoring (CGM) improves glycaemic outcomes in the outpatient setting; however, there are limited data regarding CGM accuracy in hospital. We conducted a prospective, observational study comparing CGM data from blinded Dexcom G6 Pro sensors with reference point of care and laboratory glucose measurements during participants' hospitalisations. Key accuracy metrics included the proportion of CGM values within ±20% of reference glucose values >5.6 mmol/l or within ±1.1 mmol/l of reference glucose values ≤5.6 mmol/l (%20/20), the mean and median absolute relative difference between CGM and reference value (MARD and median ARD, respectively) and Clarke error grid analysis (CEGA). A retrospective calibration scheme was used to determine whether calibration improved sensor accuracy. Multivariable regression models and subgroup analyses were used to determine the impact of clinical characteristics on accuracy assessments. A total of 326 adults hospitalised on 19 medical or surgical non-intensive care hospital floors were enrolled, providing 6648 matched glucose pairs. The %20/20 was 59.5%, the MARD was 19.2% and the median ARD was 16.8%. CEGA showed that 98.2% of values were in zone A (clinically accurate) and zone B (benign). Subgroups with lower accuracy metrics included those with severe anaemia, renal dysfunction and oedema. Application of a once-daily morning calibration schedule improved accuracy (MARD 11.4%). The CGM accuracy when used in hospital may be lower than that reported in the outpatient setting, but this may be improved with appropriate patient selection and daily calibration. Further research is needed to understand the role of CGM in inpatient settings.

Performance of Subcutaneous Continuous Glucose Monitoring in Adult Critically Ill Patients Receiving Vasopressor Therapy.

Background: Subcutaneous continuous glucose monitoring (CGM) may facilitate glucose control in the ICU. We aimed to assess the accuracy of CGM (Dexcom G6) against arterial blood glucose (ABG) in adult critically ill patients receiving intravenous insulin infusion and vasopressor therapy. We also aimed to assess feasibility and tolerability of CGM in this setting. Methods: We included ICU patients receiving mechanical ventilation, insulin, and vasopressor therapy. Numerical accuracy was assessed by the mean absolute relative difference (MARD), overall, across arterial glucose strata, over different noradrenaline equivalent infusion rates, and over time since CGM start. MARD <14% was considered acceptable. Clinical accuracy was assessed using Clarke Error Grid (CEG) analysis. Feasibility outcome included number and duration of interrupted sensor readings due to signal loss. Tolerability outcome included skin reactions related to sensor insertion or sensor adhesives. Results: We obtained 2946 paired samples from 40 patients (18 with type 2 diabetes) receiving a median (IQR) maximum noradrenaline equivalent infusion rate of 0.18 (0.08-0.33) µg/kg/min during CGM. Overall, MARD was 12.7% (95% CI 10.7-15.3), and 99.8% of CGM readings were within CEG zones A and B. MARD values ≥14% were observed when ABG was outside target range (6-10 mmol/L [108-180 mg/dL]) and with noradrenaline equivalent infusion rates above 0.10 µg/kg/min. Accuracy improved with time after CGM start, reaching MARD values <14% after 36 h. We observed four episodes of interrupted sensor readings due to signal loss, ranging from 5 to 20 min. We observed no skin reaction related to sensor insertion or sensor adhesives. Conclusions: In our ICU cohort of patients receiving vasopressor infusion, subcutaneous CGM demonstrated acceptable overall numerical and clinical accuracy. However, suboptimal accuracy may occur outside glucose ranges of 6-10 mmol/L (108-180 mg/dL), during higher dose vasopressor infusion, and during the first 36 h after CGM start.

Importance of FDA-Integrated Continuous Glucose Monitors to Ensure Accuracy of Continuous Glucose Monitoring.

Continuous glucose monitoring (CGM) has been shown to improve glycemic control and self-monitoring, as well as to reduce the risk of hypoglycemia. Integrated CGM (iCGM) FDA-cleared systems with published performance data are established nonadjunctive and accurate CGM tools that can directly inform decision-making in the treatment of diabetes (i.e., insulin dosing). Studies have assessed accuracy and safety data of CGMs that were eventually cleared for iCGM by the FDA and that informed the recommendation for their nonadjunctive use. Subsequent robust clinical trials and real-world studies demonstrated clinical effectiveness with improvements in a range of patient outcomes. In recent years, a number of non-iCGM-approved CGM devices have entered the market outside the United States worldwide. Some of these non-iCGM-approved CGM devices require additional user verification of blood glucose levels to be performed for making treatment decisions, termed adjunctive. Moreover, in many non-iCGM-approved CGM devices, accuracy studies published in peer-reviewed journals are scarce or have many limitations. Consequently, non-iCGM-approved CGM devices cannot be automatically perceived as having the same performance or quality standards than those approved for iCGM by the FDA. As a result, although these devices tend to cost less than iCGMs that carry FDA clearance and could therefore be attractive from the point of view of a health care payer, it must be emphasized that evaluation of costs should not be limited to the device (such as the usability preference that patients have for nonadjunctive sensors compared to adjunctive sensors) but to the wider value of the total benefit that the product provides to the patient.

Practical considerations for continuous glucose monitoring in elite athletes with type 1 diabetes mellitus: A narrative review.

Type 1 diabetes mellitus (T1DM) refers to a metabolic condition where a lack of insulin impairs the usual homeostatic mechanisms to control blood glucose levels. Historically, participation in competitive sport has posed a challenge for those with T1DM, where the dynamic changes in blood glucose during exercise can result in dangerously high (hyperglycaemia) or low blood glucoses (hypoglycaemia) levels. Over the last decade, research and technological development has enhanced the methods of monitoring and managing blood glucose levels, thus reducing the chances of experiencing hyper- or hypoglycaemia during exercise. The introduction of continuous glucose monitoring (CGM) systems means that glucose can be monitored conveniently, without the need for frequent fingerpick glucose checks. CGM devices include a fine sensor inserted under the skin, measuring levels of glucose in the interstitial fluid. Readings can be synchronized to a reader or mobile phone app as often as every 1-5min. Use of CGM devices is associated with lower HbA1c and a reduction in hypoglycaemic events, promoting overall health and athletic performance. However, there are limitations to CGM, which must be considered when being used by an athlete with T1DM. These limitations can be addressed by individualized education plans, using protective equipment to prevent sensor dislodgement, as well as further research aiming to: (i) account for disparities between CGM and true blood glucose levels during vigorous exercise; (ii) investigate the effects of temperature and altitude on CGM accuracy, and (iii) explore of the sociological impact of CGM use amongst sportspeople without diabetes on those with T1DM.

Accuracy of continuous glucose monitoring during exercise-related hypoglycemia in individuals with type 1 diabetes.

Hypoglycemia is common in individuals with type 1 diabetes, especially during exercise. We investigated the accuracy of two different continuous glucose monitoring systems during exercise-related hypoglycemia in an experimental setting. Fifteen individuals with type 1 diabetes participated in two separate euglycemic-hypoglycemic clamp days (Clamp-exercise and Clamp-rest) including five phases: 1) baseline euglycemia, 2) plasma glucose (PG) decline ± exercise, 3) 15-minute hypoglycemia ± exercise, 4) 45-minute hypoglycemia, and 5) recovery euglycemia. Interstitial PG levels were measured every five minutes, using Dexcom G6 (DG6) and FreeStyle Libre 1 (FSL1). Yellow Springs Instruments 2900 was used as PG reference method, enabling mean absolute relative difference (MARD) assessment for each phase and Clarke error grid analysis for each day. Exercise had a negative effect on FSL1 accuracy in phase 2 and 3 compared to rest (ΔMARD = +5.3 percentage points [(95% CI): 1.6, 9.1] and +13.5 percentage points [6.4, 20.5], respectively). In contrast, exercise had a positive effect on DG6 accuracy during phase 2 and 4 compared to rest (ΔMARD = -6.2 percentage points [-11.2, -1.2] and -8.4 percentage points [-12.4, -4.3], respectively). Clarke error grid analysis showed a decrease in clinically acceptable treatment decisions during Clamp-exercise for FSL1 while a contrary increase was observed for DG6. Physical exercise had clinically relevant impact on the accuracy of the investigated continuous glucose monitoring systems and their ability to accurately detect hypoglycemia.

Feasibility and Performance of Continuous Glucose Monitoring to Guide Computerized Insulin Infusion Therapy in Cardiovascular Intensive Care Unit.

We evaluated the feasibility of real-time continuous glucose monitoring (CGM) for titrating continuous intravenous insulin infusion (CII) to manage hyperglycemia in postoperative individuals in the cardiovascular intensive care unit and assessed their accuracy, nursing acceptance, and postoperative individual satisfaction. Dexcom G6 CGM devices were applied to 59 postsurgical patients with hyperglycemia receiving CII. A hybrid approach combining CGM with periodic point-of-care blood glucose (POC-BG) tests with two phases (initial-ongoing) of validation was used to determine CGM accuracy. Mean and median absolute relative differences and Clarke Error Grid were plotted to evaluate the CGM accuracy. Surveys of nurses and patients on the use of CGMs experience were conducted and results were analyzed. In this cohort (mean age 64, 32% female, 32% with diabetes) with 864 paired POC-BG and CGM values analyzed, mean and median absolute relative difference between POC-BG and CGM values were 13.2% and 9.8%, respectively. 99.7% of paired CGM and POC-BG were in Zones A and B of the Clarke Error Grid. Responses from nurses reported CGMs being very or quite convenient (n = 28; 93%) and it was favored over POC-BG testing (n = 28; 93%). Majority of patients (n = 42; 93%) reported their care process using CGM as being good or very good. This pilot study demonstrates the feasibility, accuracy, and nursing convenience of adopting CGM via a hybrid approach for insulin titration in postoperative settings. These findings provide robust rationale for larger confirmatory studies to evaluate the benefit of CGM in postoperative care to improve workflow, enhance health outcomes, and cost-effectiveness.

Accuracy of a Real-Time Continuous Glucose Monitor in Pediatric Diabetic Ketoacidosis Admissions.

Objective: Continuous glucose monitoring (CGM) devices are integral in the outpatient care of people with type 1 diabetes, although they lack inpatient labeling. Food and Drug Administration began allowing inpatient use during the coronavirus disease 2019 (COVID-19) pandemic, with some accuracy data now available, primarily from adult hospitals. Pediatric inpatient data remain limited, particularly during diabetic ketoacidosis (DKA) admissions and for patients receiving intravenous (IV) insulin. Design and Methods: This retrospective chart review compared point-of-care glucose values to personal Dexcom G6 sensor data during pediatric hospitalizations. Accuracy was assessed using mean absolute relative difference (MARD), Clarke Error Grids, and the percentage of values within 15/20/30% if glucose value >100 mg/dL and 15/20/30 mg/dL if glucose value ≤100 mg/dL. Results: Matched paired glucose values (N = 612) from 36 patients (median age 14 years, 58.3% non-Hispanic White, 47.2% male) and 42 inpatient encounters were included in this subanalysis of DKA admissions. The MARDs for DKA and non-DKA admissions (N = 503) were 11.8% and 11.7%, with 97.6% and 98.6% of pairs falling within A and B zones of the Clarke Error Grid, respectively. Severe DKA admissions (pH <7.15 and/or bicarbonate <5 mmol/L) had a MARD of 8.9% compared to 14.3% for nonsevere DKA admissions. The MARD during administration of IV insulin (N = 266) was 13.4%. Conclusions: CGM accuracy is similar between DKA and non-DKA admissions and is maintained in severe DKA and during IV insulin administration, suggesting potential usability in pediatric hospitalizations. Further study on the feasibility of implementation of CGM in the hospital is needed.

Accuracy and Feasibility of Real-time Continuous Glucose Monitoring in Critically Ill Patients After Abdominal Surgery and Solid Organ Transplantation.

Glycemia management in critical care is posing a challenge in frequent measuring and adequate insulin dose adjustment. In recent years, continuous glucose measurement has gained accuracy and reliability in outpatient and inpatient settings. The aim of this study was to assess the feasibility and accuracy of real-time continuous glucose monitoring (CGM) in ICU patients after major abdominal surgery. We included patients undergoing pancreatic surgery and solid organ transplantation (liver, pancreas, islets of Langerhans, kidney) requiring an ICU stay after surgery. We used a Dexcom G6 sensor, placed in the infraclavicular region, for real-time CGM. Arterial blood glucose measured by the amperometric principle (ABL 800; Radiometer, Copenhagen, Denmark) served as a reference value and for calibration. Blood glucose was also routinely monitored by a StatStrip bedside glucose meter. Sensor accuracy was assessed by mean absolute relative difference (MARD), bias, modified Bland-Altman plot, and surveillance error grid for paired samples of glucose values from CGM and acid-base analyzer (ABL). We analyzed data from 61 patients and obtained 1,546 paired glucose values from CGM and ABL. Active sensor use was 95.1%. MARD was 9.4%, relative bias was 1.4%, and 92.8% of values fell in zone A, 6.1% fell in zone B, and 1.2% fell in zone C of the surveillance error grid. Median time in range was 78%, with minimum (<1%) time spent in hypoglycemia. StatStrip glucose meter MARD compared with ABL was 5.8%. Our study shows clinically applicable accuracy and reliability of Dexcom G6 CGM in postoperative ICU patients and a feasible alternative sensor placement site.

Effect of Arterialization on Venous Blood Glucose Concentrations and Implications for Observed Continuous Glucose Monitoring Accuracy.

Background: Heating of the arm and/or hand ("arterialization") is sometimes used in continuous glucose monitoring (CGM) performance studies with the reported aim of reducing differences between venous and capillary glucose concentrations. In this study, the effect of heating on venous glucose concentrations and CGM accuracy was investigated. Methods: A heating pad set to 50°C (122°F) was used with 20 participants to heat either the dominant or nondominant arm and hand. Venous and capillary samples were obtained every 15 min on both arms throughout each of three 6-h glucose challenges. CGM sensors were worn on each upper arm for each of the three visits. Results: Heating of the arm led to a median increase in venous glucose concentrations of +1.4%. No similar effect on capillary concentrations was observed. As a result, the median capillary to venous difference decreased from +5.9% in the nonheated arm to +4.2% in the heated arm. CGM accuracy observed in this study was affected by the selection of heated venous, nonheated venous, or capillary glucose concentrations as comparator data. The heating effect was more pronounced with rapidly decreasing glucose concentrations. Temperatures on the skin did not exceed 40°C (104°F). No adverse events or protocol deviations were associated with the use of the heating pad. Conclusions: Heating of the arm led to a small increase in venous glucose concentrations, but venous concentrations did not reach the level of capillary glucose concentrations. CGM accuracy observed in this study varied depending on the selected comparator data. This study was registered at the German Clinical Trials Register (DRKS00031197).

Testing the Real-World Accuracy of the Dexcom G6 Pro CGM During the Insulin-Only Bionic Pancreas Pivotal Trial.

Continuous glucose monitors (CGMs) have transformed the way people with type 1 diabetes can self-monitor glucose levels. Past studies have evaluated the accuracy of CGMs in clinic-based studies, but few have analyzed their accuracy in real-world settings. The Insulin-Only Bionic Pancreas Trial provided the opportunity to assess real-world accuracy of the blinded Dexcom G6 Pro sensor over the first 48-60 h of wear using a blood glucose meter (BGM) as a comparator for 1073 CGM-BGM pairs across 53 participants. The mean absolute relative difference (MARD) was 11.0% over a median period of 50 h (range 47-79 h). The MARD was 13.6% in the first 12 h, 10.5% in hours 12-24, and 10.1% after the first 24 h. These results are comparable with accuracy shown previously with laboratory-based measurements and provide real-world evidence of Dexcom G6 Pro accuracy, which improved after the first 12 h and then remained stable thereafter. Clinical Trial Registry: clinicaltrials.gov; NCT04200313.

Accuracy and impact on quality of life of real-time continuous glucose monitoring in children with hyperinsulinaemic hypoglycaemia.

Continuous glucose monitoring (CGM) is the standard of care for glucose monitoring in children with diabetes, however there are limited data reporting their use in hyperinsulinaemic hypoglycaemia (HH). Here, we evaluate CGM accuracy and its impact on quality of life in children with HH. Real-time CGM (Dexcom G5 and G6) was used in children with HH aged 0-16years. Data from self-monitoring capillary blood glucose (CBG) and CGM were collected over a period of up to 28days and analysed. Quality of life was assessed by the PedsQL4.0 general module and PedsQL2.0 family impact module, completed by children and their parents/carers before and after CGM insertion. Analysis of accuracy metrics included mean absolute relative difference (MARD) and proportion of CGM values within 15, 20, and 30% or 15, 20, and 30 mg/dL of reference glucose values >100 mg/dL or ≤100 mg/dL, respectively (% 15/15, % 20/20, % 30/30). Clinical reliability was assessed with Clarke error grid (CEG) analyses. Prospective longitudinal study with data analysed from 40 children. The overall MARD between reference glucose and paired CGM values (n=4,928) was 13.0% (Dexcom G5 12.8%, Dexcom G6 13.1%). The proportion of readings meeting %15/15 and %20/20 were 77.3% and 86.4%, respectively, with CEG analysis demonstrating 97.4% of all values in zones A and B. Within the hypoglycaemia range (<70 mg/dL), the median ARD was 11.4% with a sensitivity and specificity of 64.2% and 91.3%, respectively. Overall PedsQL child report at baseline and endpoint were 57.6 (50.5 - 75.8) and 87.0 (82.9 - 91.2), and for parents were 60.3 (44.8 - 66.0) and 85.3 (83.7 - 91.3), respectively (both p<0.001). Use of CGM for children with HH is feasible, with clinically acceptable accuracy, particularly in the hypoglycaemic range. Quality of life measures demonstrate significant improvement after CGM use. These data are important to explore use of CGM in disease indications, including neonatal and paediatric diabetes, cystic fibrosis and glycogen storage disorders.

Analytical Performance of the Factory-Calibrated Flash Glucose Monitoring System FreeStyle Libre2TM in Healthy Women.

Continuous glucose monitoring (CGM) is used clinically and for research purposes to capture glycaemic profiles. The accuracy of CGM among healthy populations has not been widely assessed. This study assessed agreement between glucose concentrations obtained from venous plasma and from CGM (FreeStyle Libre2TM, Abbott Diabetes Care, Witney, UK) in healthy women. Glucose concentrations were assessed after fasting and every 15 min after a standardized breakfast over a 4-h lab period. Accuracy of CGM was determined by Bland-Altman plot, 15/15% sensor agreement analysis, Clarke error grid analysis (EGA) and mean absolute relative difference (MARD). In all, 429 valid CGM readings with paired venous plasma glucose (VPG) values were obtained from 29 healthy women. Mean CGM readings were 1.14 mmol/L (95% CI: 0.97 to 1.30 mmol/L, p < 0.001) higher than VPG concentrations. Ratio 95% limits of agreement were from 0.68 to 2.20, and a proportional bias (slope: 0.22) was reported. Additionally, 45% of the CGM readings were within ±0.83 mmol/L (±15 mg/dL) or ±15% of VPG, while 85.3% were within EGA Zones A + B (clinically acceptable). MARD was 27.5% (95% CI: 20.8, 34.2%), with higher MARD values in the hypoglycaemia range and when VPG concentrations were falling. The FreeStyle Libre2TM CGM system tends to overestimate glucose concentrations compared to venous plasma samples in healthy women, especially during hypoglycaemia and during glycaemic swings.

A Consensus Statement for Continuous Glucose Monitoring Metrics for Inpatient Clinical Trials.

Diabetes Technology Society organized an expert consensus panel to develop metrics for research in the use of continuous glucose monitors (CGMs) in a hospital setting. The experts met virtually in small groups both before and after an April 13, 2023 virtual meeting of the entire panel. The goal of the panel was to develop consensus definitions in anticipation of greater use of CGMs in hospital settings in the future. Establishment of consensus definitions of inpatient analytical metrics will be easier to compare outcomes between studies. Panelists defined terms related to 10 dimensions of measurements related to the use of CGMs including (1) hospital hypoglycemia, (2) hospital hyperglycemia, (3) hospital time in range, (4) hospital glycemic variability, (5) hospital glycemia risk index, (6) accuracy of CGM devices and reference methods for CGMs in the hospital, (7) meaningful time blocks for hospital glycemic goals, (8) hospital CGM data sufficiency, (9) using CGM data for insulin dosing, and (10) miscellaneous factors. The panelists voted on 51 proposed recommendations. Based on the panel vote, 51 recommendations were classified as either strong (43) or mild (8). Additional research is needed on CGM performance in the hospital. This consensus report is intended to support that type of research intended to improve outcomes for hospitalized people with diabetes.

Real-world Accuracy of CGM in Inpatient Critical and Noncritical Care Settings at a Safety-Net Hospital.

We sought to determine real-world accuracy of inpatient continuous glucose monitoring (CGM) at multiple levels of acuity in a large safety-net hospital. We analyzed records from hospitalized patients on Dexcom G6 CGM, including clinical, point of care (POC), and laboratory (Lab) glucose, and CGM data. POC/Lab values were matched to the closest timed CGM value. Encounters were divided into not critically ill (NCI) versus critically ill (CI). CGM accuracy was evaluated. Paired readings (2,744 POC-CGM; 3,705 Lab-CGM) were analyzed for 233 patients with 239 encounters (83 NCI, 156 CI). POC-CGM aggregated and average mean absolute relative differences (MARD) were 15.1% and 17.1%. Lab-CGM aggregated and average MARDs were 11.4% and 12.2%. Accuracy for POC-CGM and Lab-CGM was 96.5% and 99.1% in Clarke Error Grid zones A/B. Real-world accuracy of inpatient CGM is acceptable for NCI and CI patients. Further exploration of conditions associated with lower CGM accuracy in real-world settings is warranted.

952-P: The Accuracy and Feasibility of Continuous Glucose Monitoring in COVID-19 Non-Critically Ill Hospitalized Patients—A Pilot Study

Background: Optimal glycemic control is associated with favorable outcomes in COVID-19 hospitalized patients. Frequent capillary blood glucose (CBG) monitoring is difficult to perform. Using continuous glucose monitoring (CGM) system to assist glycemic care can reduce the exposure of healthcare personnel and PPE usage. However, data on the accuracy of CGM in this setting are limited. Objective: To evaluate the accuracy and feasibility of real-time CGM (rt-CGM) in non-ICU hospitalized adult COVID-19 patients. Methods: This is a single-center prospective study of non-ICU hospitalized adult patients with COVID-19 infection who had hyperglycemia requiring insulin therapy during admission. Medtronic Guardian Connect rt-CGM sensor and transmitter were placed on the patient’s abdomen. Paired CBG and sensor glucose values were analyzed for accuracy of CGM using mean absolute relative difference (MARD) and Clarke Error Grid Analysis (CEGA). Results: Fifteen patients were enrolled. Mean age was 48.6 ± 17.9 years. Thirteen patients (86.7%) had pre-existing diabetes. Mean HbA1c was 10.6± 3.6%. Mean duration of CGM use was 6 ± 1.2 days and mean calibration was 2.6 ± 0.7 times/day. There were 253 paired CBG and CGM measurements. The overall MARD was 9.9 ± 9.3%. The lowest MARD was observed in the CBG range of 70-180 mg/dl (9.6 ± 9.0%). The percentages of glucose readings within ±15%/15 mg/dL, ±20%/20 mg/dL, and ±30%/30 mg/dL were 80.2%, 89.7%, and 95.3%, respectively. A total of 99.2% of the data points were in zone A and B of CEGA, and none were in zone E. Percent time in range on day 1 was 57.9 ± 22.9 and improved to 64.9 ± 18.1 in the last 72 hours of sensor wear. No adverse events from the CGM were observed. CGM reduced POC testing by 30%. Conclusions: Rt-CGM use in hospitalized patients with COVID-19 infection demonstrates high accuracy and potentially improves glucose control, reduces the frequency of CBG testing, and preserves medical resources. Disclosure C.Sakjirapapong: None. S.Sirinvaravong: None. L.Preechasuk: None. N.Thongtang: None. Funding Specific League Funds (R016421005)

1118-P: Accuracy of Dexcom G6 Continuous Glucose Monitor in Pediatric Diabetic Ketoacidosis Admissions

Continuous glucose monitors (CGMs) are an integral part of care for youth with type 1 diabetes (T1D) though lack FDA labeling for inpatient use. While some adult data on CGM use in inpatient settings is available, pediatric data are minimal. This retrospective chart review evaluated the accuracy of Dexcom G6 CGM versus point of care (POC, Nova Biomedical StatStrip [MARD 6%])) blood glucose values from pediatric inpatient encounters. Blood glucose data, diagnosis codes, and initial labs were collected from the medical record. CGM values were obtained from Dexcom Clarity CSV files. Paired glucose values (N=1191) from 83 patients with T1D (median age 12 yrs, 54% male, 69% non-Hispanic White) were used to calculate mean absolute relative difference (MARD) and Clarke Error Grid. Data from DKA admissions (N=665) had a MARD of 11.1% with 97.8% of values within A&amp;B zones, compared to 11.4% and 98.5% for non-DKA admissions (N=526). Values from severe DKA admissions (N= 307) (pH &amp;lt;7.15 and/or bicarbonate &amp;lt;5 mmol/L) had a lower MARD compared to non-severe admissions (N=358) (8.4% vs 13.4%, p=0.01). In summary, CGM accuracy is comparable between DKA and non-DKA admissions. The accuracy of CGMs, even in severe DKA, suggests potential usability during pediatric hospital encounters. Further analysis will differentiate POC versus lab glucose and the effect of medications, including IV insulin infusions. Disclosure L.A.Waterman: None. L.Pyle: None. L.Towers: None. E.Jost: Other Relationship; Tandem Diabetes Care, Inc. A.J.Karami: None. C.Berget: Consultant; Insulet Corporation, Dexcom, Inc., Other Relationship; Tandem Diabetes Care, Inc. G.P.Forlenza: Advisory Panel; Medtronic, Consultant; Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc., Lilly Diabetes, Research Support; Medtronic, Abbott, Dexcom, Inc., Insulet Corporation, Tandem Diabetes Care, Inc. R.Wadwa: Consultant; Eli Lilly and Company, Other Relationship; Dexcom, Inc., Eli Lilly and Company, Research Support; Dexcom, Inc., Eli Lilly and Company, Beta Bionics, Inc., Tandem Diabetes Care, Inc. E.C.Cobry: None. Funding National Institutes of Health (5T32DK063687)