Accuracy of continuous glucose monitoring in critically ill patients

Studies have shown that hyper/hypoglycemia and glycemic variation are associated with adverse outcomes in critically ill patients. Currently, frequent blood point-of-care (POC) glucose measurements from an arterial or capillary sample is the only technology available to minimize glycemic excursions in the ICU. Continuous glucose monitoring (CGM) is becoming the standard of care for outpatient diabetes care and has shown improved glycemic control in the non-ICU inpatient setting. The Dexcom G6 sensor (G6) is the first CGM device approved by Health Canada for outpatient diabetes management without the need for calibration, but it has not yet been approved for inpatient use. We collected data from 23 adults who were on an insulin infusion in a medical-surgical ICU in Vancouver, British Columbia to evaluate the accuracy of uncalibrated CGM in the ICU. A blinded G6 was attached to the patient's arm and collected glucose measurements every five minutes without calibration. Nursing staff continued POC arterial glucose measurements using the AccuChek Inform II machine per standard of care. Excluding four outliers (with mean absolute relative difference (MARD) ≥ 25%), the overall MARD was 13.24% (SE 0.43) over 649 matched CGM and arterial glucose values. A Clarke Error Grid demonstrated 99.1% of CGM measurements within zones A and B. The MARD using three-point rolling averages of CGM measurements in five-minute intervals was 13.49% (SE 0.68). There were 573 matched pairs between glucose ranges of 3.9-13.9 mmol/L with two pairs <3.9 and 74 pairs >13.9 mmol/L. Eleven patients had renal replacement therapy and twelve had vasopressor use. There was no significant difference in MARD with renal replacement or across glycemic ranges ≥3.9. The MARD for patients with vasopressors was lower than for patients without (13% vs 13.55%, p<0. 01), a finding of doubtful clinical relevance. There is no expert agreement yet about the acceptable accuracy for CGM use in hospital. Our overall MARD meets the 2013 Critical Care expert consensus recommendations for MARD <14%. The FDA guidance on standard of accuracy for conventional POC glucometers require 98% of values within 15% for BG ≥ 75mg/dL. Our data showed 65.18% of values were within 15%. Previous studies using CGM in the ICU, even those using G6, all used calibration. The majority were non-blinded, and none met FDA criteria for inpatient use. Our study is the first uncalibrated and blinded study that was able to demonstrate acceptable accuracy in a large sample size. Since CGM accuracy may be affected by various factors, our comprehensive data can potentially identify specific interferences and quantify a calibration or correction criteria to improve CGM accuracy in critically ill patients. Overall, our results show that CGM shows strong potential to be an accurate, resource-efficient, and intuitive alternative to POC glucose monitoring to meet glycemic targets in the ICU.Presentation: Sunday, June 12, 2022 12:30 p.m. - 2:30 p.m.

Introduction: Continuous glucose monitoring (CGM) use in people with type 1 diabetes (T1D) is revolutionizing management. Use of CGM in hospital is poised to transform care, however routine use is not currently recommended due to lack of accuracy validation in acute care, including in people with T1D. We aimed to determine real-world CGM accuracy in hospitalized adults with T1D. Materials and Methods: In this multicenter retrospective observational study, we compared CGM interstitial fluid glucose with reference blood glucose (capillary/whole-blood point-of-care [POC], blood gas [GAS]) in adults with T1D requiring multiday admissions during 2020-2023 across three health services in Australia. Patients requiring dialysis or admitted under pediatric/obstetric/palliative care/psychiatry units were excluded. CGM accuracy was assessed by comparison with time-matched (±5 min) reference glucose measures, utilizing median absolute relative difference (ARD), mean ARD (MARD), and consensus error grid (CEG) analysis. Results: In total, 2,199 CGM-reference glucose pairs from 214 admissions (146 patients) were assessed. Overall, mean (SD) ARD was 12.8% (13.1) and median (IQR) ARD was 9.4% (3.7-17.7). MARD for CGM-POC pairs was 12.3%; MARD for CGM-GAS pairs was 14.3%. In CEG analysis, 99.3% of glucose pairs were within zones A/B. Accuracy was lower in critical care compared with noncritical care wards (MARD 16.1% vs. 12.0%, P < 0.001). Conclusions: In this real-world multicenter study, CGM glucose agreed well with reference blood glucose, suggesting modern CGM devices could be safely and effectively used in hospitalized adults with T1D. Further prospective studies of CGM accuracy with newer generation devices across different scenarios will further elucidate inpatient CGM accuracy and safety.

Objective: To assess the accuracy of the subcutaneous continuous glucose monitoring (CGM) sensor by comparing to the capillary blood glucose (CBG) and venous plasma glucose (VPG) measurements in the medical intensive care unit (MICU) patients. Subjects and Methods: In a prospective study in patients in the MICUs, Medtronic Enlite sensor was inserted in the abdominal area. Paired sensor glucose readings with reference glucose values (CBG and VPG) were collected from MICU patients receiving intravenous insulin infusion therapy. The accuracy was assessed using the mean absolute relative difference (MARD), surveillance error grid (SEG) analysis and modified Bland-Altman plot. Results: Twelve patients completed the study (age 69.3 ± 11.6 years; BMI 21.6 ± 2.9 kg/m2; APACHE II score 21.8 ± 6.3 and duration of CGM use 108.7 ± 41.1 hours). A total of 353 paired CGM and CBG glucose readings and 125 paired CGM and VPG readings were included in the analysis. Using CBG as the reference, MARD was 7.2%. The modified Bland-Altman plot showed 95% of the limit of agreement (LoA) was -18.4% to 19.2%. The SEG analysis showed that 100% of paired glucose values were within zones A or B. No clinically significant difference in the accuracy was seen between subgroups of vasopressor use (MARD 6.1% in the vasopressor group vs. 6.8% in the non-vasopressor group, p = NS). Using VPG as the reference, the MARD was 8.8%. The modified Bland-Altman plot showed 95% LoA of - 22.6% to 28.2%. The SEG analysis showed 95.2% of glucose readings were within zones A or B. Conclusion: The accuracy of the subcutaneous CGM sensor in MICU patients was comparable to that observed in non-critical care settings, with no device-related adverse events. The sensor accuracy remained within the similar range when using VPG as the references compared to using CBG as the references. No differences in terms of accuracy between the vasopressor and non-vasopressor groups were found in this study. Disclosure N. Laichuthai: None. P. Buranasupkajorn: None. W. Khovidhunkit: Speaker’s Bureau; Self; Amgen, AstraZeneca. Funding Quality Improvement Fund; King Chulalongkorn Memorial Hospital; Thai Red Cross Society (1-62-30101-A-11)

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)

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)

BackgroundThe COVID-19 pandemic led to crisis-level shortage of hospital beds and staff, predominantly in the ICUs. Minimization of patient contact moved the FDA to issue a statement that allowed CGMs in hospitals, which were quickly adopted by ICUs. We conducted a study to better understand the use of CGM in ICUs and test for accuracy, reliability feasibility, and acceptance by care providers.MethodsPatients were eligible for CGM if they had diabetes mellitus and concomitant COVID-19 infection that required ICU level of care. CGM signals were received by smart phones that were placed in a transparent biohazard bag outside patients’ rooms. Nurses were educated on the interpretation of glucose trends, alerts, and calibration. CGM alerts were set for glucose readings below 100mg/dL and above or equal to 250mg/dL. Nursing staff could obtain point-of-care (POC) glucose as scheduled and for CGM alarms. Mean Absolute Relative Difference (MARD) values were calculated for accuracy. Nurses were invited to respond to a questionnaire with 5-point Likert scales to assess their perception of CGM use, and the potential decrease in the amount of personal protective equipment (PPE) needed in the care of patients on CGM. A question on the estimated time it takes to donn and doff PPE was also included.Results26 patients were included in the study; average age 60.8 + 13.5 years, 7 were female and 12 belonged to underrepresented minorities (Hispanic, non-Hispanic Black, or Asian); mean HbA1c was 9.2 + 2.6%. 7 patients were on intravenous insulin infusion, 6 were intubated and 5 received vasopressors. Average duration on CGM was 6 + 3.75 days.168 paired serum glucose-CGM measurements and 259 paired POC-CGM measurements were used. MARD between serum glucose and CGM measurements was 11.2%; MARD between POC glucose and CGM measurement was 11.6%. Questionnaires from 33 nursing staff were analyzed; the most frequent answer (mode) for time to donn and doff PPE was 10 minutes. The vast majority of answers were "agree" (21.2%) or "strongly agree" (78.8%) to the statements that CGM was easy to use and interpret and during the pandemic staff felt protected with use of CGM. Likewise, the answers were "agree" (18.8%) or "strongly agree" (81.8%) that CGMs could replace POC glucose in COVID-19 patients and that there was a lower need for PPE.ConclusionThere is not an established acceptable MARD for patients with COVID-19 in an ICU setting. Wollersheim et al. suggested that CGM with a MARD of <14% is acceptable for ICU patients. The MARD we found in our study was well within this range. We concluded that use of CGM in the ICU setting has acceptable accuracy and is reliable, feasible and well accepted by the nursing staff.Presentation: No date and time listed

There are no published studies directly comparing the accuracy of continuous glucose monitoring (CGM) devices in the outpatient setting. We tested the performance of the Dexcom G5, Abbot Freestyle Libre Pro, and Senseonics Eversense (an implantable CGM approved in Europe) during a 6-week, free-living, outpatient bionic pancreas study involving 23 subjects with type 1 diabetes who wore all 3 devices concomitantly. The primary outcome was the mean absolute relative difference (MARD) vs. plasma glucose (PG) values measured with the Nova Biomedical StatStrip Xpress meter that was also used for calibrations according to the manufacturer's instruction (except for Libre Pro that is not calibrated). We compared PG values with CGM readings when they were available from all 3 CGMS in the 5 minutes preceding the PG values (n=829 sets). Since the Libre Pro records readings every 15 minutes, we also did a two-way comparison between the G5 and the Eversense that allowed a higher number of comparisons (n=2277 sets). Statistical significance was determined using a repeated measurements model fitted with the generalized estimating equation method. All 3 CGM systems produced higher average MARDs than during in-clinic studies. However, since all three CGM systems were worn by the same individuals and used the same meter for calibration and as comparator, we were able to directly compare their performance under real-world conditions. In the 3-way comparison Eversense achieved the lowest nominal MARD (14.8%) followed by Dexcom G5 (16.3%) and Libre Pro (18.0%) (Eversense vs. Libre Pro p=0.004, other comparisons p=NS). In the 2-way comparison the MARD difference between Eversense (15.1%) and G5 (16.9%) was statistically significant (p=0.008). We found that the point accuracy of the Eversense was significantly better than two other CGM systems. The Eversense CGM system may be useful to provide glucose values to artificial pancreas devices. Disclosure R.Z. Jafri: None. C.A. Balliro: None. F. El-Khatib: Stock/Shareholder; Self; Beta Bionics. Employee; Self; Beta Bionics. M. Maheno: None. M.A. Hillard: None. A.J. O'Donovan: None. R. Selagamsetty: None. H. Zheng: None. E. Damiano: Other Relationship; Self; Beta Bionics. S.J. Russell: Other Relationship; Self; Beta Bionics, Novo Nordisk Inc.. Advisory Panel; Self; Companion Medical, Tandem Diabetes Care, Inc., Unomedical a/s. Research Support; Self; Beta Bionics, Zealand Pharma A/S, MITRE Corporation.

OBJECTIVEGlycemia 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.RESEARCH DESIGN AND METHODSWe 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).RESULTSWe 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%.CONCLUSIONSOur study shows clinically applicable accuracy and reliability of Dexcom G6 CGM in postoperative ICU patients and a feasible alternative sensor placement site.

Continuous glucose monitoring (CGM) is widely used in the outpatient setting for people with diabetes and has been limited to investigational use only for the inpatient population. In April 2020, the US FDA exercised enforcement discretion for the temporary use of inpatient CGM during the pandemic, thus hospitals were presented the opportunity to implement this technology. We sought to investigate the accuracy of CGM in hospitalized patients on general care floors and the intensive care unit (ICU) in attempts to decrease healthcare professional exposure to COVID-19 and ultimately improve glycemic management of patients affected by COVID-19. Point of care (POC) and laboratory (Lab) glucose values were matched with simultaneous CGM glucose values and measures of accuracy were performed to evaluate the safety and usability of CGM in this population. Our data are presented drawing a distinction between POC and Lab as reference glucose sources. In 808 paired samples obtained from 28 patients (10 ICU, 18 general floor), overall mean absolute relative difference (MARD) for all patients using either POC or Lab as reference was 13.2%. When using POC as the reference glucose MARD was 13.9% and using Lab glucose as reference 10.9%. Using both POC and Lab reference glucose pairs the overall MARD for critical care patients was 12.1% and for general floor patients 14%. We determined, with proper protocols and safeguards in place, use of CGM in the hospitalized patient is a reasonable alternative to standard of care to achieve the goal of reducing healthcare professional exposure. Further study is necessary to validate safety, accuracy, and efficacy of this technology. Investigation and analysis are necessary for the development of protocols to utilize CGM trend arrows, alerts, and alarms.

Using the standard venous reference for the evaluation of continuous glucose monitoring (CGM) systems could possibly negatively affect measured CGM accuracy since CGM are generally calibrated with capillary glucose and venous and capillary glucose concentrations differ. We therefore aimed to quantify the effect of using capillary versus venous glucose reference samples on estimated accuracy in capillary calibrated CGM. We evaluated 41 individuals with type 1 diabetes mellitus (T1DM) using the Dexcom G4 CGM system over 6 days. Patients calibrated their CGM devices with capillary glucose by means of the HemoCue system. During 2 visits, capillary and venous samples were simultaneously measured by HemoCue and compared to concomitantly obtained CGM readings. The mean absolute relative difference (MARD) was calculated using capillary and venous reference samples. Venous glucose values were 0.83 mmol/L (15.0 mg/dl) lower than capillary values over all glycemic ranges, P < .0001. Below 4 mmol/l (72 mg/dl), the difference was 1.25 mmol/l (22.5 mg/dl), P = .0001, at 4-10 mmol/l (72-180 mg/dl), 0.67 mmol/l (12.0 mg/dl), P < .0001 and above 10 mmol/l (180 mg/dl), 0.95 mmol/l (17.1 mg/dl), P < .0001. MARD was 11.7% using capillary values as reference compared to 13.7% using venous samples, P = .037. Below 4 mmol/l (72 mg/dl) MARD was 16.6% and 31.8%, P = .048, at 4-10 mmol/l (72-180 mg/dl) 12.1% and 12.6%, P = .32, above 10 mmol/l (180 mg/dl) 8.7% and 9.2%, P = .82. Using capillary glucose concentrations as reference to evaluate the accuracy of CGM calibrated with capillary samples is associated with a lower MARD than using venous glucose as the reference. Capillary glucose concentrations were significantly higher than venous in all glycemic ranges.

Continuous glucose monitoring (CGM) during intravenous insulin infusions (IVII) could reduce blood glucose (BG) testing burden in hospital, however CGM accuracy concerns exist. We aimed to assess CGM accuracy during IVII. This multi-centre observational study included adults with type 1 diabetes (T1D) who required IVII treatment during hospital admission whilst wearing their own CGM devices (Abbott FreeStyle Libre 2, Medtronic Guardian 3, Dexcom G6). IVII dose adjustments were performed based upon standard of care BG measures. Accuracy was assessed according to mean absolute relative difference (MARD) and Consensus error grid (CEG) analysis, using time-matched (±5 minutes) pairs of CGM glucose and reference BG (point-of-care [POC], blood gas [GAS]) obtained during IVII. In total, 736 time-matched glucose pairs were obtained from 56 hospital admissions (52% with diabetic ketoacidosis; 32% requiring intensive care). Median IVII duration was 16 hours (IQR 7.2-28). Overall MARD was 12.5% (11.9% for CGM-POC pairs; 14.1% for CGM-GAS pairs). In CEG analysis, 99.0% of glucose pairs were within zones A/B. Based on local hospital IVII dose titration protocols for non-intensive care wards, if CGM measures had been used instead of POC, dose adjustments would have been the same in 77% of instances. This real-world study of adults with T1D demonstrated high concordance of CGM measures with BG during IVII. The accuracy of CGM during IVII might enable its greater clinical utility when treating inpatients receiving IVII. More inpatient studies are required to validate the use of CGM during IVII.

&lt;p dir="ltr"&gt;Objective: Continuous glucose monitoring (CGM) is widely used to monitor glucose levels in patients with diabetes and guide insulin dosing in outpatients. In inpatient care, special regulatory requirements necessitate CGM accuracy as a prerequisite for its integration into clinical decision support. &lt;/p&gt;&lt;p dir="ltr"&gt;Research Design and Methods: To meet the specific demands of in-hospital care, CGM accuracy was retrospectively evaluated in 226 patients using paired CGM and point-of-care (POC) glucose measurements, assessed via Mean Absolute Relative Difference (MARD), Clarke Error Grid (CEG) analysis and the FDA agreement rule. A dynamic, patient-specific algorithm incorporating time lag correction and linear modeling was developed to minimize MARD and applied in a second cohort of 24 patients within the clinical workflow. &lt;/p&gt;&lt;p dir="ltr"&gt;Results: Data analysis showed an initial MARD of 10.3%, with 99.02% of data points located in zones A and B of the CEG. The application of the patient-specific optimization algorithm improved the MARD by 4.33%. Evaluation of the patient-specific algorithm on an inpatient cohort (n=24) demonstrated a 5.58% reduction in intrapersonal MARD, indicating its potential applicability within clinical workflows. &lt;/p&gt;&lt;p dir="ltr"&gt;Conclusion: Patient-specific algorithmic refinements of CGM data demonstrate the potential to adequately address the unique demands of inpatient diabetes care by reducing intrapersonal MARD, paving the way for the adoption of CGM systems into hospital environments. &lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;

&lt;p dir="ltr"&gt;Objective: Continuous glucose monitoring (CGM) is widely used to monitor glucose levels in patients with diabetes and guide insulin dosing in outpatients. In inpatient care, special regulatory requirements necessitate CGM accuracy as a prerequisite for its integration into clinical decision support. &lt;/p&gt;&lt;p dir="ltr"&gt;Research Design and Methods: To meet the specific demands of in-hospital care, CGM accuracy was retrospectively evaluated in 226 patients using paired CGM and point-of-care (POC) glucose measurements, assessed via Mean Absolute Relative Difference (MARD), Clarke Error Grid (CEG) analysis and the FDA agreement rule. A dynamic, patient-specific algorithm incorporating time lag correction and linear modeling was developed to minimize MARD and applied in a second cohort of 24 patients within the clinical workflow. &lt;/p&gt;&lt;p dir="ltr"&gt;Results: Data analysis showed an initial MARD of 10.3%, with 99.02% of data points located in zones A and B of the CEG. The application of the patient-specific optimization algorithm improved the MARD by 4.33%. Evaluation of the patient-specific algorithm on an inpatient cohort (n=24) demonstrated a 5.58% reduction in intrapersonal MARD, indicating its potential applicability within clinical workflows. &lt;/p&gt;&lt;p dir="ltr"&gt;Conclusion: Patient-specific algorithmic refinements of CGM data demonstrate the potential to adequately address the unique demands of inpatient diabetes care by reducing intrapersonal MARD, paving the way for the adoption of CGM systems into hospital environments. &lt;/p&gt;&lt;p&gt;&lt;br&gt;&lt;/p&gt;

Continuous glucose monitors (CGMs) are widely used for individuals with diabetes mellitus, particularly those with type 1 diabetes (T1D). Advancements in CGM technology allow for glycemic assessment without capillary glucose measurements as many come factory calibrated. However, exercise, an essential component of diabetes care, has been reported to alter accuracy of earlier generation CGM. Considering the importance of physical activity for individuals with T1D and the progression of CGM technology, we aimed to investigate the accuracy of the Dexcom G6 during physical activity. Adolescents (ages 13-20 years) exercised on a treadmill for 40 minutes, with a 10-minute break at minute 20. We obtained paired CGM and glucometer measurements before and every 10 minutes during and after exercise. Accuracy analysis was determined by mean absolute relative difference (MARD), mean absolute difference (MAD), and Clarke Error Grid Analyses. Mean absolute relative difference and MAD increased during exercise (14%-33% and 24.3-34 mg/dL) but improved after exercise. We noted certain CGM locations produced greater changes in accuracy as MARD and MAD increased markedly when the CGM was on the buttocks (18%-46% and 30-41 mg/dL). We also noted decreased odds of Zone A in the Clarke error grid when the CGM was on the buttocks compared to the abdomen (odds ratio [OR]: 0.146; P = 0.0003; 95% CI = 0.052-0.415). This CGM system showed alterations in accuracy during exercise. Our findings additionally suggest interstitial fluid changes in muscles during exercise alter accuracy of CGM; however, additional research is required.

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.