Personalizing Early-Stage Type 1 Diabetes in Children

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Cloud boundary height measurements using lidar and radar

Using only lidar or radar an accurate cloud boundary height estimate is often not possible. The combination of lidar and radar can give a reliable cloud boundary estimate in a much broader range of cases. However, also this combination with standard methods still can not measure the cloud boundaries in all cases. This will be illustrated with data from the Clouds and Radiation measurement campaigns, CLARA. Rain is a problem: the radar has problems to measure the small cloud droplets in the presence of raindrops. Similarly, few large particles below cloud base can obscure the cloud base in radar measurements. And the radar reflectivity can be very low at the cloud base of water clouds or in large regions of ice clouds, due to small particles. Multiple cloud layers and clouds with specular reflections can pose problems for lidar. More advanced measurement techniques are suggested to solve these problems. An angle scanning lidar can, for example, detect specular reflections, while using information from the radars Doppler velocity spectrum may help to detect clouds during rain.Comment: Reviewed conference contributio

Lower risk of severe hypoglycaemia with insulin glargine 300 U/mL versus glargine 100 U/mL in participants with type 1 diabetes : A meta‐analysis of 6‐month phase 3 clinical trials

Severe hypoglycaemia (SH) remains a challenge to people with type 1 diabetes (T1DM), and new‐generation basal insulins may improve patient outcomes. This post hoc meta‐analysis explored the risk of SH with insulin glargine 300 U/mL (Gla‐300) versus glargine 100 U/mL (Gla‐100) in a pooled population with T1DM from three randomized, multicentre, 6‐month similarly designed phase 3 trials: EDITION 4, EDITION JP 1 and EDITION JUNIOR. Endpoints included incidence and time to first occurrence of SH. Among 629 and 626 participants randomized to Gla‐300 and Gla‐100, respectively, glycated haemoglobin reductions were similar. Fewer participants experienced ≥1 SH event with Gla‐300 (6.2%) than with Gla‐100 (9.3%). From baseline to month 6, the risk of a first SH event was lower with Gla‐300: hazard ratio 0.65 [95% confidence interval (CI) 0.44–0.98; stratified log‐rank test P = 0.038]. SH event rates were numerically lower with Gla‐300 versus Gla‐100 from baseline to month 6 [relative risk (RR) 0.80 (95% CI 0.49–1.29); P = 0.356] and baseline to week 8 [RR 0.73 (95% CI 0.37–1.44); P = 0.369]. Thus, Gla‐300 demonstrated similar glycaemic control with lower risk of SH versus Gla‐100, particularly during the titration period

Criteria for Centers of Reference for pediatric diabetes--a European perspective

' SWEET' is an acronym standing for 'Better control in pediatric and adolescent diabeteS: Working to crEate CEnTers of Reference ( CORs)' and is based on a partnership of established national and European diabetes organizations such as International Diabetes Federation, Federation of European Nurses in Diabetes, and Primary Care Diabetes Europe (PCDE, www.sweet-project.eu). A three-level classification of centers has been put forward. In addition to centers for local care, SWEET collaborating centers on their way to being a COR have been defined. Peer-audited CORs with a continuous electronic documentation of at least 150 pediatric patients with diabetes treated by a multidisciplinary team based on the International Society for Pediatric and Adolescent Diabetes ( ISPAD) Clinical Practice recommendations have been created in 12 European countries. In 2011, they cared for between 150 to more than 700 youth with diabetes with an average hemoglobin A1c between 7.6 and 9.2%. Although these clinics should not be regarded as representative for the whole country, the acknowledgment as COR includes a common objective of targets and guidelines as well as recognition of expertise in treatment and education at the center. In a first step, the SWEET Online platform allows 12 countries using 11 languages to connect to one unified diabetes database. Aggregate data are de-identified and exported for longitudinal health and economic data analysis. Through their network, the CORs wish to obtain political influence on a national and international level and to facilitate dissemination of new approaches and techniques. The SWEET project hopes to extend from the initial group of centers within countries, throughout Europe, and beyond with the help of the ISPAD network

Quality control requirements for the correct annotation of lipidomics data.

10.1038/s41467-021-24984-yNature Communications121477

Sotagliflozin Added to Optimized Insulin Therapy Leads to Lower Rates of Clinically Relevant Hypoglycemic Events at Any HbA1c at 52 Weeks in Adults with Type 1 Diabetes

Background: Hypoglycemia rates usually increase when insulin treatment is intensified to improve glycemic control. We evaluated (post hoc) hypoglycemic rates in adult patients with type 1 diabetes (T1D) on sotagliflozin (a dual sodium-glucose cotransporter [SGLT] 1 and 2 inhibitor) in two phase 3, 52-week clinical trials (inTandem 1 and 2; NCT02384941 and NCT02421510). Materials and Methods: We analyzed rates of documented hypoglycemia (level 1, blood glucose 6554 to <70\u2009mg/dL) and clinically important hypoglycemia (level 2, glucose <54\u2009mg/dL) in a patient-level pooled analysis (n\u2009=\u20091362) using a negative binomial model adjusted for hemoglobin A1c (HbA1c) at 52 weeks in patients receiving placebo, sotagliflozin 200\u2009mg, and sotagliflozin 400\u2009mg. Results: Rates of level 1 hypoglycemia events per patient-year were 58.25 (95% confidence interval: 50.26-67.50) with placebo, 44.86 (38.83-51.82; P\u2009=\u20090.0138 vs. placebo) with sotagliflozin 200\u2009mg, and 45.68 (39.52-52.81; P\u2009=\u20090.0220) with sotagliflozin 400\u2009mg. Sotagliflozin was also associated with lower rates of level 2 hypoglycemia: 15.95 (14.37-17.70), 11.51 (10.39-12.76; P\u2009<\u20090.0001), and 11.13 (10.03-12.35; P\u2009<\u20090.0001) for placebo and sotagliflozin 200 and 400\u2009mg, respectively. The difference in rates of hypoglycemia with sotagliflozin versus placebo became more pronounced as HbA1c decreased. Conclusions: At week 52, level 1 and 2 hypoglycemia events were 22% to 30% less frequent with sotagliflozin added to optimized insulin therapy versus placebo in adults with T1D at any HbA1c level, with greater differences at lower HbA1c values. These findings support the use of sotagliflozin as an insulin adjunct in T1D

Exercise management in type 1 diabetes:a consensus statement

Type 1 diabetes is a challenging condition to manage for various physiological and behavioural reasons. Regular exercise is important, but management of different forms of physical activity is particularly difficult for both the individual with type 1 diabetes and the health-care provider. People with type 1 diabetes tend to be at least as inactive as the general population, with a large percentage of individuals not maintaining a healthy body mass nor achieving the minimum amount of moderate to vigorous aerobic activity per week. Regular exercise can improve health and wellbeing, and can help individuals to achieve their target lipid profile, body composition, and fitness and glycaemic goals. However, several additional barriers to exercise can exist for a person with diabetes, including fear of hypoglycaemia, loss of glycaemic control, and inadequate knowledge around exercise management. This Review provides an up-to-date consensus on exercise management for individuals with type 1 diabetes who exercise regularly, including glucose targets for safe and effective exercise, and nutritional and insulin dose adjustments to protect against exercise-related glucose excursions

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments