Target Glucose Range Research Articles

Artificial Pancreas Technology Offers Hope for Childhood Diabetes.

Here, we provide a review of recent advancements in closed-loop or automated insulin delivery systems commonly referred to as the "artificial pancreas" (AP) for the management of type 1 diabetes (T1D). The use of hybrid closed-loop devices in children and adolescents with T1D consistently increases time in the target glucose range (70-180mg/dL) without increasing the risk of hypoglycemia. Although hybrid closed-loop systems are able to maintain fairly tight glycemic control overnight, daytime control remains challenging, primarily due to meals and exercise, and careful carbohydrate counting and meal boluses remain essential components of optimal diabetes control. Bihormonal and fully automated AP systems remain investigational at this time. While commercially available hybrid closed-loop AP systems improve glycemic control in children with T1D, more work is needed to achieve a fully automated AP system and decrease the burden of using diabetes technology.

Management of glucose profile throughout strict COVID-19 lockdown by patients with type 1 diabetes prone to hypoglycaemia using sensor-augmented pump.

AimsSpain has been one of the worst affected countries by the COVID-19 pandemic. A very strict lockdown at home was imposed with a tough restriction of mobility. We aimed to evaluate the impact of this exceptional scenario on glucose profile of patients with type 1 diabetes (T1D) prone to hypoglycaemia using sensor-augmented pump (SAP).MethodsPatients with T1D prone to hypoglycaemia using SAP (640G Medtronic-Minimed®) for at least 6 months under the funding of a National Health Service were included in an observational, retrospective study. Data were collected in two periods: pre-lockdown (PL), February 23rd–March 7th and within lockdown (WL), April 1st to 14th 2020. The primary outcome was the difference in the proportion of time in target glucose range of 70–180 mg/dL (TIR). Additional glucometric data and total daily insulin were also analysed.ResultsFifty-nine patients were included: 33 women, age 46.17 ± 13.0 years and disease duration of 30.2 ± 12.0 years. TIR 70–180 mg/dL (67.6 ± 11.8 vs. 69.8 ± 12.0%), time > 180 (28.1 ± 13.6 vs. 25.5 ± 13.1%), time > 250 (6.9 ± 6.1 vs. 5.1 ± 4.8) and estimated HbA1c (6.94 ± 0.8 vs. 6.75 ± 0.7%) significantly improved (PL vs. WL, respectively, p < 0.05). Time in hypoglycaemia, coefficient of variation, sensor usage and total daily insulin dose remained unchanged.ConclusionsLockdown conditions imposed by the COVID-19 pandemic may be managed successfully in terms of glycaemia control by population with DT1 prone to hypoglycaemia using SAP. The strict daily routine at home could probably explain the improvement in the time in glycemic target without increasing the time hypoglycaemia.

Efficacy and Safety of Tofogliflozin and Ipragliflozin for Patients with Type-2 Diabetes: A Randomized Crossover Study by Flash Glucose Monitoring.

IntroductionSodium-glucose cotransporter 2 (SGLT2) inhibitors promote urinary glucose excretion. However, the differences in the effects of various SGLT2 inhibitors are unknown. We used flash glucose monitoring (FGM) to identify the differences between tofogliflozin and ipragliflozin in terms of efficacy in reducing glycemic variability and mitigate hypoglycemia risk.MethodsIn this crossover study, 24 patients with type-2 diabetes mellitus (T2DM) receiving insulin glargine U300 therapy were randomly allocated to tofogliflozin and ipragliflozin or ipragliflozin and tofogliflozin group. Glycemic variability and hypoglycemia were compared using to the 3-day FGM data per treatment period.ResultsGlucose level 2 h after each meal was significantly lower with tofogliflozin administration than with ipragliflozin administration. Time below the target glucose range after tofogliflozin administration was significantly lower than that after ipragliflozin administration (2.1% ± 4.4% vs. 8.7% ± 11.7%). The 24-h standard deviation of glucose level, mean amplitude of glycemic excursion, and mean percent time with nocturnal hypoglycemia after tofogliflozin administration were significantly lower than those after ipragliflozin administration.ConclusionsTofogliflozin was more effective and safer than ipragliflozin in reducing glycemic variability and mitigating hypoglycemia risk in patients with T2DM treated with insulin glargine U300.Trial RegistrationThis trial was registered at the University Hospital Medical Information Network Clinical Trial Registry (no. UMIN000037158).Electronic MaterialThe online version of this article (10.1007/s13300-020-00940-9) contains supplementary material, which is available to authorized users.

Continuous Glucose Monitoring in Type 1 Diabetes

Research Article| October 01 2020 Continuous Glucose Monitoring in Type 1 Diabetes AAP Grand Rounds (2020) 44 (4): 40. https://doi.org/10.1542/gr.44-4-40 Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Continuous Glucose Monitoring in Type 1 Diabetes. AAP Grand Rounds October 2020; 44 (4): 40. https://doi.org/10.1542/gr.44-4-40 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search toolbar search search input Search input auto suggest filter your search All PublicationsAll JournalsAAP Grand RoundsPediatricsHospital PediatricsPediatrics In ReviewNeoReviewsAAP NewsAll AAP Sites Search Advanced Search Topics: continuous glucose monitoring, diabetes mellitus, type 1, glycemic control Source: Laffel LM, L Kanapka LG, Beck RW, et al. Effect of continuous glucose monitoring on glycemic control in adolescents and young adults with type 1 diabetes: a randomized clinical trial. JAMA. 2020; 323(23): 2388– 2396; doi: https://doi.org/10.1001/jama.2020.6940Google Scholar Investigators from multiple institutions conducted a randomized controlled trial assessing the effect of continuous glucose monitoring (CGM) on glycemic control in adolescents and young adults with type 1 diabetes. Participants were 14–24 years old with a duration of diabetes of at least 1 year who had baseline hemoglobin A1c (HbA1c) levels ≥ 7.5% and < 11.0%. At enrollment, study participants were randomized to use CGM or continue with their regular finger stick blood glucose monitoring (BGM). The CGM system included a disposable sensor inserted under the skin that transmitted interstitial glucose levels every 5 minutes to a receiver or smartphone app; twice-daily finger stick glucose levels were required to calibrate the system. Participants were enrolled in the study for 26 weeks. The primary outcome was change in HbA1c level between baseline and week 26. Differences between groups were assessed using longitudinal linear regression. Secondary outcomes included change in HbA1c at 13 weeks and achieving a HbA1c level in the target range (< 7.5% for those < 19 years old and < 7.0% for those ≥ 19 years old) at 26 weeks. Those in the BGM group wore a CGM device during weeks 24–26 (glucose levels were not provided to the participant). Various glycemic control metrics, including mean glucose, time in the target glucose range (70–180 mg/dL), and time with glucose > 180 mg/dL and < 70 mg/dL, for those in the BGM and CGM groups were compared using regression analyses. A total of 153 participants were included in the study, with 74 randomized to CGM and 79 to the BGM group. The mean age of study participants was 17 years, and mean duration of diabetes was 9 years. Mean baseline HbA1c values were 8.9% for both groups. However, at 26 weeks, mean HbA1c values were 8.5% for those in the CGM group and 8.9% for those randomized to BGM (adjusted difference between groups −0.37%; 95% CI, −0.66%, −0.08%; P = .01). There was also a difference in change in HbA1c levels at 13 weeks between groups (mean values 8.4% and 8.9%, respectively, for the CGM and BGM groups; difference 0.50%; 95% CI, −0.79%, −0.21%; P < .001). At week 26, there was no difference between groups in percent of participants who met target HbA1c values (13% CGM, 10% BGM, P = .42). During CGM monitoring for both groups, those in the CGM group had significantly lower mean glucose levels (P = .003), longer time in the target glucose range (P < .001), and less time with glucose > 180 mg/dL (P = .007) or < 70 mg/dL (P = .02). The authors conclude that use of CGM led to small but statistically significant improvements... You do not currently have access to this content.

Insulin dose optimization using an automated artificial intelligence-based decision support system in youths with type 1 diabetes.

Despite the increasing adoption of insulin pumps and continuous glucose monitoring devices, most people with type 1 diabetes do not achieve their glycemic goals1. This could be related to a lack of expertise or inadequate time for clinicians to analyze complex sensor-augmented pump data. We tested whether frequent insulin dose adjustments guided by an automated artificial intelligence-based decision support system (AI-DSS) is as effective and safe as those guided by physicians in controlling glucose levels. ADVICE4U was a six-month, multicenter, multinational, parallel, randomized controlled, non-inferiority trial in 108 participants with type 1 diabetes, aged 10-21 years and using insulin pump therapy (ClinicalTrials.gov no. NCT03003806). Participants were randomized 1:1 to receive remote insulin dose adjustment every three weeks guided by either an AI-DSS, (AI-DSS arm, n = 54) or by physicians (physician arm, n = 54). The results for the primary efficacy measure-the percentage of time spent within the target glucose range (70-180 mg dl-1 (3.9-10.0 mmol l-1))-in the AI-DSS arm were statistically non-inferior to those in the physician arm (50.2 ± 11.1% versus 51.6 ± 11.3%, respectively, P < 1 × 10-7). The percentage of readings below 54 mg dl-1 (<3.0 mmol l-1) within the AI-DSS arm was statistically non-inferior to that in the physician arm (1.3 ± 1.4% versus 1.0 ± 0.9%, respectively, P < 0.0001). Three severe adverse events related to diabetes (two severe hypoglycemia, one diabetic ketoacidosis) were reported in the physician arm and none in the AI-DSS arm. In conclusion, use of an automated decision support tool for optimizing insulin pump settings was non-inferior to intensive insulin titration provided by physicians from specialized academic diabetes centers.

The impact of strict COVID-19 lockdown in spain on glycemic profiles in patients with type 1 Diabetes prone to hypoglycemia using standalone continuous glucose monitoring

Abstract Aims Spain has been one of the worst affected countries by the COVID-19 pandemic. A very strict lockdown at home was imposed with a tough restriction of mobility. We aimed to evaluate the impact of this exceptional scenario on glucose profile of patients with T1D prone to hypoglycemia using standalone continuous glucose monitoring. Methods Patients with T1D prone to hypoglycemia using multiple daily injections and either a Dexcom G5® or a Free Style Libre® CGM systems for at least 6 months under the funding of National Health Service were included in an observational, retrospective study. Data were collected in two periods: pre-lockdown (PL), February 23rd-March 7th and within lockdown (WL), April 1st–14th 2020. The primary outcome was the difference in the proportion of time in target glucose range of 70–180 mg/dL (TIR). Additional glucometric data were also analysed. Results 92 patients were included: 40 women, age 42.8 ± 3.9 years, disease duration of 23.1 ± 12.6 years. Seventeen patients used Dexcom G5® and 75 Free Style Libre®. TIR 70–180 mg/dL (59.3 ± 16.2 vs 62.6 ± 15.2%), time > 180 (34.4 ± 18.0 vs 30.7 ± 16.9%), >250 (11.1 ± 10.6 vs 9.2 ± 9.7%) and Glucose Management Indicator (7.2 ± 0.8 vs 7.0 ± 0.8%) significantly improved (PL vs WL, respectively, p Conclusions Lockdown conditions imposed by the COVID-19 pandemic may be managed successfully in terms of glycemic control by population with T1D prone to hypoglycemia using CGM. The strict daily routine at home could probably explain the improvement in the time in glycemic target without increasing the time in hypoglycemia.

Sodium-glucose cotransporter2 inhibitors reduce day-to-day glucose variability in patients with type1 diabetes.

Aims/IntroductionSodium–glucose cotransporter 2 inhibitors (SGLT2i) are used worldwide because of their multiple benefits for patients with type 2 diabetes. The purpose of this study was to determine the efficacy and safety of SGLT2i in patients with type 1 diabetes.Materials and MethodsPatients with type 1 diabetes who had been treated with SGLT2i for >12 weeks were included in this retrospective observation study. We recorded the changes in body mass, insulin dose, blood and urine test data, and adverse events. The changes in day‐to‐day glucose variability, as the primary end‐point, was evaluated using the interquartile range (P25/P75) of the ambulatory glucose data obtained using continuous glucose monitoring.ResultsA total of 51 patients (37 women; mean age 52.7 years) were included. Glycated hemoglobin and body mass significantly decreased by 0.4% and 1.6 kg, respectively. The total required insulin dose decreased by 9.4% (42.7 ± 26.6–38.7 ± 24.3 units/day). Continuous glucose monitoring data were obtained from 30 patients. P25/P75 decreased by 17.6 ± 20.7% during SGLT2i treatment (P < 0.001). The percentage of time per day within the target glucose range of 70–180 mg/dL significantly increased (from 42.2 to 55.5%, P < 0.001), without an increase in the percentage of time spent in the hypoglycemic range (<70 mg/dL). Urinary ketone bodies were detected in four patients (7.8%), but none developed ketoacidosis.ConclusionsSGLT2i improved day‐to‐day glucose variability and time in the target glucose range, without increasing frequency of hypoglycemia, in patients with type 1 diabetes, and reduced glycated hemoglobin, body mass and the required insulin dose.

The impact of strict COVID-19 lockdown in Spain on glycemic profiles in patients with type 1 Diabetes prone to hypoglycemia using standalone continuous glucose monitoring

AimsSpain has been one of the worst affected countries by the COVID-19 pandemic. A very strict lockdown at home was imposed with a tough restriction of mobility. We aimed to evaluate the impact of this exceptional scenario on glucose profile of patients with T1D prone to hypoglycemia using standalone continuous glucose monitoring. MethodsPatients with T1D prone to hypoglycemia using multiple daily injections and either a Dexcom G5® or a Free Style Libre® CGM systems for at least 6 months under the funding of National Health Service were included in an observational, retrospective study. Data were collected in two periods: pre-lockdown (PL), February 23rd-March 7th and within lockdown (WL), April 1st–14th 2020. The primary outcome was the difference in the proportion of time in target glucose range of 70–180 mg/dL (TIR). Additional glucometric data were also analysed. Results92 patients were included: 40 women, age 42.8 ± 3.9 years, disease duration of 23.1 ± 12.6 years. Seventeen patients used Dexcom G5® and 75 Free Style Libre®. TIR 70–180 mg/dL (59.3 ± 16.2 vs 62.6 ± 15.2%), time > 180 (34.4 ± 18.0 vs 30.7 ± 16.9%), >250 (11.1 ± 10.6 vs 9.2 ± 9.7%) and Glucose Management Indicator (7.2 ± 0.8 vs 7.0 ± 0.8%) significantly improved (PL vs WL, respectively, p < 0.05). Time in hypoglycemia remained unchanged. ConclusionsLockdown conditions imposed by the COVID-19 pandemic may be managed successfully in terms of glycemic control by population with T1D prone to hypoglycemia using CGM. The strict daily routine at home could probably explain the improvement in the time in glycemic target without increasing the time in hypoglycemia.

Patient Satisfaction and Clinical Efficacy of Flash Glucose Monitoring in Patients with Type 1 Diabetes: A Prospective, Single-Center, Single-Arm Study.

IntroductionFrequent self-monitoring of blood glucose (SMBG) is usually required in patients with type 1 diabetes (T1D). However, the fear of self-testing, hygiene, and social obstacles may deter some patients from SMBG. Flash glucose monitoring (FGM), a less-invasive glucose monitoring method, was launched in Japan in September 2017. The aim of this study was to evaluate patient satisfaction and the clinical efficacy of FGM in Japanese patients with T1D.MethodsPatient satisfaction with FGM was assessed using the Diabetes Treatment Satisfaction Questionnaire (DTSQ) and Diabetes Therapy-Related Quality of Life (DTR-QOL) questionnaire before (baseline) and 4 and 12 weeks after initiating FGM use in 20 Japanese patients with T1D. Clinical parameters related to glucose metabolism, such as glycated hemoglobin (HbA1c) levels, were assessed, and glucose fluctuations were evaluated using the FGM data. Values at 4 and 12 weeks after initiating FGM were compared with baseline data using the Wilcoxon signed-rank test. The mean absolute relative difference (MARD) between glucose values detected using the FGM device and by SMBG was also calculated.ResultsThe DTSQ scores significantly improved 12 weeks after initiating FGM (P < 0.001). The DTR-QOL scores related to “burden in social activities” and “treatment satisfaction” also significantly improved 12 weeks after initiating FGM (P = 0.024 and 0.007, respectively). The HbA1c values and the percentage of time within the target glucose range (3.9–7.8 mmol/L) at the 12-week time point also improved, from 58 ± 5 (baseline) to 54 ± 4 mmol/mol (P = 0.002) and from 36% (interquartile range [IQR] 25–44.5%) (baseline) to 43% (IQR 39–50%) (P = 0.016), respectively. The MARD between glucose values detected using FGM and those detected using SMBG was 12.2% throughout the study period.ConclusionsFlash glucose monitoring contributed to improved patient satisfaction and the adjustment of blood glucose levels in patients with T1D.Trial RegistrationUniversity Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR): UMIN000029673Electronic Supplementary MaterialThe online version of this article (10.1007/s13300-020-00859-1) contains supplementary material, which is available to authorized users.

869-P: Using CGM as Feedback Tool in Diabetes Mellitus Patients Management: A Retrospective Real-World Evidence Study Conducted in India

Introduction: Since many new diabetic medications are costly and often have side effects, quick feedback would allow for timely decisions. The current study present the role of CGM in titrate medication to achieve glycemic target of diabetes mellitus patients using 14 days CGM report (AGP). Methodology: Retrospective AGP of 214 patients was collected from 2017 to 2019. Target glucose range was considered as 70-180 mg/dL, hypoglycemia was categorized as low (54-69 mg/dL) and very low (&amp;lt;54 mg/dL) and hyperglycemia as high (180-250 mg/dL) and very high (&amp;gt;250 mg/dL). The % of time a patient spent in above ranges was illustrated as time in target range (TIR), time below range (TBR), and time above range (TAR), respectively. The glycemic variability (GV) parameters included standard deviation (SD) and coefficient of variation (CV). Changes in diabetic medications were done, if required, after first week of CGM. Variation in TIR, TAR, TBR and CV were analyzed before (first week) and after medication (last week). Results: Improvement was observed in mean glucose values and SD from 152.1 to 135.5 and 41.0 to 35.1 mg/dL, respectively, % of time in TIR from 57.9 to 64.5% and TAR from 25.9 to 16.9% (high: 16.9 to 12.6% and very high: 9.0 to 4.3%) from first to last week. However, % of time in hypoglycemia (TBR) was increased from 7.9 to 11.2% (low: 6.6 to 8.8% and very low: 1.3 to 2.4%). The patients count with high glycemic variability (CV &amp;gt;36) was reduced from 27 to 21. The average eA1C was improved by 0.6 units (6.9 to 6.3). Conclusion: The patients who were hyperglycemic were well controlled with medication, albeit with episodes of hypoglycemia during night-time. The treating clinicians can focus on these soft spots after first week instead of waiting long to intervene if they use CGM to titrate the medication. Thus, CGM can be instrumental in giving quick feedback in maintaining desired glycemic targets. Disclosure M. Sabharwal: None. S. Palukuri: None. S. Deka: None. G. Chanana: None. R. Kumar: None.

988-P: Do-It-Yourself Artificial Pancreas Systems for Type 1 Diabetes Reduce Hyperglycemia without Increasing Hypoglycemia

Background: Patient-driven innovation has led to the development of do-it-yourself artificial pancreas systems (DIYAPS) for the management of type 1 diabetes (T1D). There have been few studies comparing glycemic outcomes for DIYAPS compared to conventional sensor-augmented pump (SAP) therapy. Methods: A retrospective double cohort study was performed. The DIY group consisted of people with T1D using DIYAPS (OpenAPS, Loop, and AndroidAPS) who contributed data to the OpenAPS Data Commons. The SAP group included age-matched SAP users whose sensor data was obtained through the Tidepool Big Data Donation Project. The primary outcome of percent of sensor glucoses (SG) in low glucose range (&amp;lt;70 mg/dL) was determined for both groups and compared. Secondary outcomes included mean SG, number of &amp;gt;=15-minute hypoglycemic episodes (&amp;lt;70 mg/dL) per month, and percent of SG in high glucose range (&amp;gt;=180 mg/dL) and in target range (70-180 mg/dL). Results: The DIY group included 90 days of data from 74 individuals with mean age of 36 ± 15 years and 24 ± 16 years since T1D diagnosis. The SAP group had 98 individuals with mean age of 35 ± 14 years and 20 ± 13 years since diagnosis. There was no significant difference in percent of SG &amp;lt;70 mg/dL between the two groups (3.8% for DIY vs. 4.7% for SAP, p=0.17). There was also no difference in number of hypoglycemic episodes per month (32.9 for DIY vs. 33.4 for SAP, p=0.87) or in percent of SG &amp;lt;54 mg/dL (0.8% for DIY vs. 1.3% for SAP, p=0.09). Mean SG was lower for the DIY group (134.9 ± 19.1 mg/dL for DIY vs. 150.3 ± 25.7 mg/dL for SAP, p&amp;lt;0.0001). Percent of SG &amp;gt;=180 mg/dL was lower (16.9% for DIY vs. 26.1% for SAP, p&amp;lt;0.0001) and percent in target glucose range was greater for the DIY group (79.3% for DIY vs. 69.2% for SAP, p&amp;lt;0.0001). Conclusion: Users of DIYAPS had a comparable amount of hypoglycemia to those using SAP and had less hyperglycemia. This study suggests that the glycemic benefit of DIYAPS is in reducing hyperglycemia without compromising the low occurrence of hypoglycemia. Disclosure J. Zabinsky: None. H. Howell: None. A. Ghezavati: None. D.M. Lewis: Research Support; Self; JDRF. A. Nguyen: None. J.C. Wong: Consultant; Self; pH Pharma. Research Support; Self; Dexcom, Inc. Funding JDRF

539-P: Time in Glucose Target Range Indicates the Risk of DPN in Chinese Type 1 Diabetes Patients

Objective: Previous studies have indicated that in addition to poor glycemic control, glucose variability, obesity and hypertension may also have impacts on DPN in T2DM patients. Not much researches have been taken on T1DM patients. Our study aims to use the data derived from CGMs to assess the association between DPN and glucose variety as well as to find out the potential risk factors for DPN among T1DM patients. Methods: In this cross-sectional study, a total of 116 type 1 diabetes inpatients were recruited. Patients age range from 14 to 75 years old. All patients were screened for DPN and then divided into 2 groups, DPN and non-DPN group. A 3-day CGMs was conducted on each patient. Information regarding BMI, smoking and drinking habits, medical history were collected from the patients’ medical record book. Results: 1. Among the type 1 diabetes patients enrolled in our study, the average age is 47.8 years old, with a known diabetes duration of 9.56 years. 40 (34.48%) presented with DPN. The prevalence of DPN increased steadily with increasing duration of diabetes, from 12.1% in those diagnosed diabetes within 5 years to 53.7% in those have diabetes longer than 10 years. 2. Compared with the control group, DPN patients are older, have longer duration, higher BMI, waist circumstance, HbA1c, GA and lower TIR (p&amp;lt;0.05). The prevalence of hypertension, carotid artery plaque, current drinking and smoking were higher in DPN group (p &amp;lt; 0.05). Meanwhile, glucose variability, evaluated by SD and MAGE; insulin function are comparable between two groups(p&amp;lt;0.05) 3. Multivariate logistic regression analysis showed that TIR quartiles(Q1: &amp;gt;71%; Q2: 56-71%; Q3: 41-56%; Q4≤41%) (OR 2.18, CI 1.35-3.51, p =0.001) and duration (OR 1.17, CI 1.08-1.27, p &amp;lt;0.001)were significantly correlating with DPN. Discussion: In T1DM patients, glycemic variability is not a risk factor for DPN. TIR is a significantly independent risk factor for DPN. Components of the metabolic syndrome may also play an important role in the development of DPN. Disclosure W. Shen: None. F. Liu: None.

Safety and Efficacy of Glucostabilizer in the Management of Diabetic Ketoacidosis

Objective: To evaluate the safety and efficacy of GlucoStabilizer software intravenous insulin (IV) dosing in comparison to American Diabetes Association protocol-directed provider-guided insulin dose adjustment (PGIA). Methods: GlucoStabilizer calculates the dose of IV insulin required to reach a prescribed target glucose range. GlucoStabilizer has not been fully studied in DKA. This retrospective study compared outcomes in patients with DKA before and after the implementation of GlucoStabilizer. Insulin doses were administered based on GlucoStabilizer calculations or PGIA. The analysis evaluated before-after changes in the amount of insulin used, time to target, hypoglycemia or hypokalemia events, and the time to DKA resolution. Results: We studied 77 patients with insulin doses calculated by GlucoStabilizer and 69 patients with PGIA dosing. GlucoStabilizer was superior to PGIA. Patients treated with GlucoStabilizer-calculated doses did not experience hypoglycemia (N = 0 versus N = 10; P<.001). The 10 unique PGIA patients had a total of 18 episodes with 17 between 55 to 69 mg/dL; 1 <54 mg/dL, and no episodes <40 mg/dL. The GlucoStabilizer group required less insulin to reach DKA resolution (59.2 versus 101.2 units; P<.001). Time to glycemic target and DKA resolution were similar (6.7 versus 4.6 hours; P = .132) and (9.8 versus 9.9 hours; P = .803), respectively. No difference in the incidence of hypokalemia was seen (N = 9 versus N = 11; P = .48). Conclusion: This study demonstrates the Gluco Stabilizer settings that can be successfully used in the management of DKA with the avoidance of hypoglycemia. Patients treated with GlucoStabilizer-calculated doses experienced no hypoglycemia and required less insulin as compared to those managed with PGIA. Abbreviations: ADA = American Diabetes Association; DKA = diabetic ketoacidosis; ED = emergency department; eGMS = electronic glycemic management systems; ICU = intensive care unit; IV = intravenous; PGIA = protocol-directed provider-guided insulin dose adjustment.

Time spent outside of target glucose range for young children with type 1 diabetes: a continuous glucose monitor study.

To assess the associations between demographic and clinical characteristics and sensor glucose metrics in young children with type 1 diabetes, using masked, continuous glucose monitoring data from children aged 2 to < 8 years. The analysis included 143 children across 14 sites in the USA, enrolled in a separate clinical trial. Eligibility criteria were: age 2 to <8 years; type 1 diabetes duration ≥3 months; no continuous glucose monitoring use for past 30 days; and HbA1c concentration 53 to <86 mmol/mol (7.0 to <10.0%). All participants wore masked continuous glucose monitors up to 14 days. On average, participants spent the majority (13 h) of the day in hyperglycaemia (>10.0 mmol/l) and a median of ~1 h/day in hypoglycaemia (<3.9 mmol/l). Participants with minority race/ethnicity and higher parent education levels spent more time in target range, 3.9-10.0 mmol/l, and less time in hyperglycaemia. More time in hypoglycaemia was associated with minority race/ethnicity and younger age at diagnosis. Continuous glucose monitoring metrics were similar in pump and injection users. Given that both hypo- and hyperglycaemia negatively impact neurocognitive development, strategies to increase time in target glucose range for young children are needed.

Assessing the effect of closed-loop insulin delivery from onset of type 1 diabetes in youth on residual beta-cell function compared to standard insulin therapy (CLOuD study): a randomised parallel study protocol

IntroductionManagement of newly diagnosed type 1 diabetes (T1D) in children and adolescents is challenging for patients, families and healthcare professionals. The objective of this study is to determine whether continued...

Experts opinion: implantable continuous glucose monitoring system — innovation in the management of diabetes

Continuous glucose monitoring (CGM) systems have revolutionized the treatment and monitoring of diabetes. These devices are recommended for diabetic patients treated with insulin, especially with recurring episodes of hypoglycemia or large circadian variation of glucose levels. CGM allows more effective adjustment of insulin doses to blood glucose trends, resulting in better metabolic control: more time spend in glucose target range, lower time spend in hypoglycemic range, lower glucose variability and improved quality of life of patients and their family members. Real time CGM provides patients not only with continuous information on glucose levels but also alerts for hypo- or hyperglycemic events. Traditional transcutaneous CGM have some limitations, which can be resolved by the system with an implantable sensor. The Eversense CGM is the only long-term implantable rtCGM. The subcutaneous implantation procedure has proved to be simple and uncomplicated. This CGM system can be recommended in particular for patients who, due to their profession and sports discipline, cannot or do not want to use traditional transcutaneous sensors. Further groups are patients with skin complications associated with the use of traditional sensors, people who perceive frequent sensor replacement as a burden or would benefit from on-body vibration alerts. The studies showed that the patients were satisfied with Eversense, and the majority used it several times after the study ended. The main reason for resigning from the next implantation was cost of the device.

Individualizing Glycemic Control in the Critically Ill.

Hyperglycemia is a common phenomenon in critically ill patients, even in those without diabetes. Two landmark studies established the benefits of tight glucose control (blood glucose target 80-110 mg/dL) in surgical and medical patients. Since then, literature has consistently demonstrated that both hyperglycemia and hypoglycemia are independently associated with increased morbidity and mortality in a variety of critically ill patients. However, tight glycemic control has subsequently come into question due to risks of hypoglycemia and increased mortality. More recently, strategies targeting euglycemia (blood glucose ≤180 mg/dL) have been associated with improved outcomes, although the risk of hypoglycemia remains. More complex targets (ie, glycemic variability and time within target glucose range) and the impact of individual patient characteristics (ie, diabetic status and prehospital glucose control) have more recently been shown to influence the relationship between glycemic control and outcomes in critically ill patients. Although our understanding has increased, the optimal glycemic target is still unclear and glucose management strategies may require adjustment for individual patient characteristics. As glucose management increases in complexity, we realize that traditional means of using meters and strips and paper insulin titration algorithms are potential limitations to our success. To achieve these complex goals for glycemic control, the use of continuous or near-continuous glucose monitoring combined with computerized insulin titration algorithms may be required. The purpose of this review is to discuss the evidence surrounding the various domains of glycemic control and the emerging data supporting the need for individualized glucose targets in critically ill patients.

Biosynthetic Human Insulin and Insulin Analogs.

Biosynthetic human insulins and analogs have replaced animal insulins and permitted structural modifications to alter the rate of absorption, duration of action, improve reproducibility of effects, and modulate relative efficacy in various target tissues. Several forms of rapidly acting insulins nearly achieve rapid pharmacokinetics and pharmacodynamics similar to first-phase insulin release. There is need for even faster-acting analogs to mimic normal physiology and improve control of postprandial glycemic excursions. Two biosynthetic insulin analogs have sufficiently long duration of action for use as once-daily basal insulins; controversy persists regarding their respective risks of hypoglycemia and relative glycemic variability. Basal-bolus therapy and insulin pump therapy, including closed-loop automated insulin delivery, require rapid-acting insulin analogs. The longer acting insulins can provide stable, reproducible basal insulin with reduced rates of hypoglycemia, particularly nocturnal hypoglycemia, greater efficacy in reducing mean glucose and glucose variability while increasing time in glucose target range. Inhalable human insulin provides very rapid action. Premixture of rapid-acting analogs with protamine has been useful for some patients with type 2 diabetes. An insulin analog with preferential efficacy at the liver has been developed and tested clinically but not marketed. Current research is aimed at developing even faster-acting insulin analogs. Long-acting basal insulins coformulated with GLP-1 receptor agonists or with a rapidly acting insulin analog have valuable clinical applications. Excipients, chaperones, local heating of the infusion site, and hyaluronidase have also been used to accelerate the absorption of insulin analogs. Biosynthetic human insulins have radically revolutionized management of both type 1 and type 2 diabetes worldwide. The ability to manipulate the structure and formulation of insulin provides for more physiologic pharmacokinetics and pharmacodynamics, enabling improved glycemic control, reduced risk of hypoglycemia, and reduced rates of long-term complications.

Insulin Therapy in Hospitalized Patients.

Hyperglycemia is prevalent and is associated with an increase in morbidity and mortality in hospitalized patients. Insulin therapy is the most appropriate method for controlling glycemia in hospital, but is associated with increased risk of hypoglycemia, which is a barrier to achieving glycemic goals. Optimal glycemic targets have not been established in the critical and noncritical hospitalized patients, and there are different modalities of insulin therapy. The primary purpose of this review is to discuss controversy regarding appropriate glycemic targets and summarize the evidence about the safety and efficacy of insulin therapy in critical and noncritical care settings. A literature search was conducted through PubMed with the following key words (inpatient hyperglycemia, inpatient diabetes, glycemic control AND critically or non-critically ill patient, Insulin therapy in hospital). In critically ill patient, blood glucose levels >180 mg/dL may increase the risk of hospital complications, and blood glucose levels <110 mg/dL have been associated with an increased risk of hypoglycemia. Continuous intravenous insulin infusion is the best method for achieving glycemic targets in the critically ill patient. The ideal glucose goals for noncritically ill patients remain undefined and must be individualized according to the characteristics of the patients. A basal-bolus insulin strategy resulted in better glycemic control than sliding scale insulin and lower risk of hypoglycemia than premixed insulin regimen. Extremes of blood glucose lead to poor outcomes, and target glucose range of 110-180 mg/dL may be appropriate for most critically ill patients and noncritically ill patients. Insulin is the most appropriate pharmacologic agent for effectively controlling glycemia in hospital. A continuous intravenous insulin infusion and scheduled basal-bolus-correction insulin are the preferred modalities for glycemic control in critically and noncritically ill hospitalized patients, respectively.

Hypoglycemia and Glycemic Control in Older Adults With Type 1 Diabetes: Baseline Results From the WISDM Study.

Knowledge regarding the burden and predictors of hypoglycemia among older adults with type 1 diabetes (T1D) is limited. We analyzed baseline data from the Wireless Innovations for Seniors with Diabetes Mellitus (WISDM) study, which enrolled participants at 22 sites in the United States. Eligibility included clinical diagnosis of T1D, age ≥60 years, no real-time continuous glucose monitoring (CGM) use in prior three months, and HbA1c <10.0%. Blinded CGM data from 203 participants with at least 240 hours were included in the analyses. Median age of the cohort was 68 years (52% female, 93% non-Hispanic white, and 53% used insulin pumps). Mean HbA1c was 7.5%. Median time spent in the glucose range <70 mg/dL was 5.0% (72 min/day) and <54 mg/dL was 1.6% (24 min/day). Among all factors analyzed, only reduced hypoglycemia awareness was associated with greater time spent <54 mg/dL (median time of 2.7% vs 1.3% [39 vs 19 minutes per day] for reduced awareness vs aware/uncertain, respectively, P = .03). Participants spent a mean 56% of total time in target glucose range of 70-180 mg/dL and 37% of time above 180 mg/dL. Over half of older T1D participants spent at least an hour a day with glucose levels <70 mg/dL. Those with reduced hypoglycemia awareness spent over twice as much time than those without in a serious hypoglycemia range (glucose levels <54 mg/dL). Interventions to reduce exposure to clinically significant hypoglycemia and increase time in range are urgently needed in this age group.