179 results found
Oliver N, Avari P, Reddy M, 2020, Response to Letter by Seibold regarding "Glycemic Variability and Hypoglycemic Excursions With Continuous Glucose Monitoring Compared to Intermittently Scanned Continuous Glucose Monitoring in Adults With Highest Risk Type 1 Diabetes"., J Diabetes Sci Technol, Vol: 14, Pages: 697-698
Avari P, Reddy M, Oliver N, 2020, Is it possible to constantly and accurately monitor blood sugar levels, in people with Type 1 diabetes, with a discrete device (non-invasive or invasive)?, Diabetic Medicine, Vol: 37, Pages: 532-544, ISSN: 0742-3071
Real-time continuous glucose monitors using subcutaneous needle-type sensors continue to develop. The limitations of currently available systems, however, include time lag behind changes in blood glucose, the invasive nature of such systems, and in some cases, their accuracy. Non-invasive techniques have been developed, but, to date, no commercial device has been successful. A key research priority for people with Type 1 diabetes identified by the James Lind Alliance was to identify ways of monitoring blood glucose constantly and accurately using a discrete device, invasive or non-invasive. Integration of such a sensor is important in the development of a closed-loop system and the technology must be rapid, selective and acceptable for continuous use by individuals. The present review provides an update on existing continuous glucose-sensing technologies, and an overview of emergent techniques, including their accuracy and limitations.
Oliver N, Holt RIG, 2020, The James Lind Alliance Research Priorities for Diabetes revisited., Diabet Med, Vol: 37, Pages: 511-512
Misra S, hassanali N, Bennet A, et al., 2020, Homozygous hypomorphic HNF1A alleles are a novel cause of young-onset diabetes and result in sulphonylurea sensitive diabetes, Diabetes Care, Vol: 43, Pages: 909-912, ISSN: 0149-5992
OBJECTIVE Heterozygous loss-of-function mutations in HNF1A cause maturity-onset diabetes of the young (MODY). Affected individuals can be treated with low-dose sulphonylureas. Individuals with homozygous HNF1A mutations causing MODY have not been reported.RESEARCH DESIGN AND METHODS We phenotyped a kindred with young-onset diabetes and performed molecular genetic testing, a mixed meal tolerance test, a sulphonylurea challenge, and in vitro assays to assess variant protein function.RESULTS A homozygous HNF1A variant (p.A251T) was identified in three insulin-treated family members diagnosed with diabetes before 20 years of age. Those with the homozygous variant had low hs-CRP levels (0.2–0.8 mg/L), and those tested demonstrated sensitivity to sulphonylurea given at a low dose, completely transitioning off insulin. In silico modeling predicted a variant of unknown significance; however, in vitro studies supported a modest reduction in transactivation potential (79% of that for the wild type; P < 0.05) in the absence of endogenous HNF1A.CONCLUSIONS Homozygous hypomorphic HNF1A variants are a cause of HNF1A-MODY. We thus expand the allelic spectrum of variants in dominant genes causing diabetes.
Guemes M, Rahman SA, Kapoor RR, et al., 2020, Hyperinsulinemic hypoglycemia in children and adolescents: Recent advances in understanding of pathophysiology and management, REVIEWS IN ENDOCRINE & METABOLIC DISORDERS, ISSN: 1389-9155
Moscardó V, Herrero P, Reddy M, et al., 2020, Assessment of Glucose Control Metrics by Discriminant Ratio., Diabetes Technol Ther
OBJECTIVE: Increasing use of continuous glucose monitoring data has created an array of glucose metrics for glucose variability, temporal patterns and times in ranges. However, a gold standard metric has not been defined. We assess the performance of multiple glucose metrics to determine their ability to detect intra- and inter-person variability in order to determine a set of recommended metrics. METHODS: The Juvenile Diabetes Research Foundation (JDRF) dataset, a randomized controlled study of continuous glucose monitoring and self-monitored blood glucose conducted in children and adults with type 1 diabetes was used. To determine the ability of the evaluated glycemic metrics to discriminate between different subjects and attenuate the effect of within-subject variation, the Discriminant Ratio was calculated and compared for each metric. Then, the findings were confirmed using data from two other recent randomized clinical trials. RESULTS: Mean Absolute Glucose (MAG) has the highest discriminant ratio value (2.98 [95% CI 1.64-3.67]). In addition, Low Blood Glucose Index (LBGI) and Index of Glycemic Control (IGC) performed well (1.93 [95% CI 1.15-3.44] and 1.92 [95% CI 1.27-2.93], respectively). For percentage times in glucose target ranges, the optimal discriminator was percentage time in glucose target 70-180 mg/dL. CONCLUSIONS: Mean Absolute Glucose (MAG) is the optimal index to differentiate glucose variability in people with type 1 diabetes, and may be a complementary therapeutic monitoring tool in addition to HbA1c and a measure of hypoglycemia. Percentage time in glucose target 70-180 mg/dL is the optimal percentage time in range to report.
Johnson A, Hill NE, Godsland I, et al., 2020, Glycemic Tracking Before and After Insulin Pump Initiation., J Diabetes Sci Technol
Reddy M, Oliver N, 2020, Self-Monitoring of Blood Glucose Requirements with the Use of Intermittently Scanned Continuous Glucose Monitoring, DIABETES TECHNOLOGY & THERAPEUTICS, Vol: 22, Pages: 235-238, ISSN: 1520-9156
Rilstone S, Reddy M, Oliver N, 2020, A Pilot Study of Flat and Circadian Insulin Infusion Rates in Continuous Subcutaneous Insulin Infusion (CSII) in Adults with Type 1 Diabetes (FIRST1D)., J Diabetes Sci Technol
BACKGROUND: Initiation of continuous subcutaneous insulin therapy (CSII) in type 1 diabetes requires conversion of a basal insulin dose into a continuous infusion regimen. There are limited data to guide the optimal insulin profile to rapidly achieve target glucose and minimize healthcare professional input. The aim of this pilot study was to compare circadian and flat insulin infusion rates in CSII naïve adults with type 1 diabetes. METHODS: Adults with type 1 diabetes commencing CSII were recruited. Participants were randomized to circadian or flat basal profile calculated from the total daily dose. Basal rate testing was undertaken on days 7, 14 and 28 and basal rates were adjusted. The primary outcome was the between-group difference in absolute change in insulin basal rate over 24 hours following three rounds of basal testing. Secondary outcomes included the number of basal rate changes and the time blocks. RESULTS: Seventeen participants (mean age 33.3 (SD 8.6) years) were recruited. There was no significant difference in absolute change in insulin basal rates between groups (P = .85). The circadian group experienced significant variation in the number of changes made with the most changes in the morning and evening (P = .005). The circadian group received a greater reduction in total insulin (-14.1 (interquartile range (IQR) -22.5-12.95) units) than the flat group (-7.48 (IQR -11.90-1.23) units) (P = .021). CONCLUSION: The initial insulin profile does not impact on the magnitude of basal rate changes during optimization. The circadian profile requires changes at specific time points. Further development of the circadian profile may be the optimal strategy.
Oliver N, Johnston D, Godsland I, et al., 2020, A pragmatic and scalable strategy using mobile technology to promote sustained lifestyle changes to prevent Type 2 diabetes in India and the UK – a randomised controlled trial, Diabetologia, Vol: 63, Pages: 486-496, ISSN: 0012-186X
Aims/hypothesis This randomised controlled trial was performed in India and UK in people with prediabetes to study whether mobile phone short message services can be used to motivate and educate people to follow lifestyle modification, to prevent type 2 diabetes.Methods The study was performed in people with prediabetes (n=2062, control: n=1031; intervention: n=1031) identified by glycosylated haemoglobin A1c42 and 47mmol/mol (6.0% and 6.4%). Participants were recruited from public and private sector organisations in India and by the NHS Health Checks programme in the UK. Allocation to the study groups was performed using a computer generated sequence (1:1) in India and by stratified randomisation in permuted blocks in the UK. Investigators in both countries remained blinded throughout the study period. All participants received advice on healthy lifestyle at baseline. The intervention group in addition received supportive text messages using mobile phone short messaging services2-3 times per week. Participants were assessed at intervals for 2years. The primary outcome was conversion to diabetes and secondary outcomes included anthropometry, biochemistry, dietary and physical activity change, blood pressure and quality of life. Results At 2years follow-up, in the intention-to-treat population the hazard ratio for development of diabetes calculated using a discrete-time proportional hazards model was 0.89,95%CI(0.74-1.07) p=0.22. There were no significant differences in the secondary outcomes.Conclusions/Interpretation This trial in 2 countries with varied ethnic and cultural backgrounds showed no significant reduction in the progression in diabetes in 2 years by lifestyle modification using short messaging services (Hazard Ratio 0.89, 95% CI 0.74 – 1.07, p=0.22)
Liu C, Avari P, Leal Y, et al., 2020, A modular safety system for an insulin dose recommender: a feasibility study., Journal of Diabetes Science and Technology, Vol: 14, Pages: 87-96, ISSN: 1932-2968
BACKGROUND: Delivering insulin in type 1 diabetes is a challenging, and potentially risky, activity; hence the importance of including safety measures as part of any insulin dosing or recommender system. This work presents and clinically evaluates a modular safety system that is part of an intelligent insulin dose recommender platform developed within the EU-funded PEPPER project. METHODS: The proposed safety system is composed of four modules which use a novel glucose forecasting algorithm. These modules are predictive glucose alerts and alarms; a predictive low-glucose basal insulin suspension module; an advanced rescue carbohydrate recommender for resolving hypoglycemia; and a personalized safety constraint applied to insulin recommendations. The technical feasibility of the proposed safety system was evaluated in a pilot study including eight adult subjects with type 1 diabetes on multiple daily injections over a duration of six weeks. Glycemic control and safety system functioning were compared between the two-weeks run-in period and the end point at eight weeks. A standard insulin bolus calculator was employed to recommend insulin doses. RESULTS: Overall, glycemic control improved over the evaluated period. In particular, percentage time in the hypoglycemia range (<3.0 mmol/l) significantly decreased from 0.82% (0.05-4.79) at run-in to 0.33% (0.00-0.93) at endpoint ( P = .02). This was associated with a significant increase in percentage time in target range (3.9-10.0 mmol/l) from 52.8% (38.3-61.5) to 61.3% (47.5-71.7) ( P = .03). There was also a reduction in number of carbohydrate recommendations. CONCLUSION: A safety system for an insulin dose recommender has been proven to be a viable solution to reduce the number of adverse events associated to glucose control in type 1 diabetes.
Oliver N, Reddy M, Marriott C, et al., 2019, Open source automated insulin delivery: addressing the challenge, npj Digital Medicine, Vol: 2, ISSN: 2398-6352
Do-it-yourself automated insulin delivery systems for people living with type 1 diabetes use commercially available continuous glucose sensors and insulin pumps linked by unregulated open source software. Uptake of these systems is increasing, with growing evidence suggesting that positive glucose outcomes may be feasible. Increasing interest from people living with, or affected by, type 1 diabetes presents challenges to healthcare professionals, device manufacturers and regulators as the legal, governance and risk frameworks for such devices are not defined.We discuss the data, education, policy, technology and medicolegal obstacles to wider implementation of DIY systems and outline the next steps required for a co-ordinated approach to reducing variation in access to a technology that has potential to enable glucose self-management closer to target.
Avari P, Uduku C, George D, et al., 2019, Differences for Percentage Times in Glycemic Range Between Continuous Glucose Monitoring and Capillary Blood Glucose Monitoring in Adults with Type 1 Diabetes: Analysis of the REPLACE-BG Dataset., Diabetes Technol Ther
Background: Self-monitored blood glucose (SMBG) and real-time continuous glucose monitoring (rtCGM) are used by people living with type 1 diabetes (T1D) to assess glucose and inform decision-making. Percentage time in range (%TIR) between 3.9 and 10 mmol/L has been associated with incident microvascular complications using historical SMBG data. However, the association between %TIR calculated from rtCGM data has not been identified. This study investigates whether %TIR values generated from rtCGM and SMBG data significantly differ from each other in adults with T1D. Materials and Methods: rtCGM and SMBG data from the REPLACE-BG study were obtained and analyzed. The dataset contained rtCGM (Dexcom G4 Platinum) and SMBG (Contour Next) values for 226 participants during a run-in phase lasting up to 10 weeks, followed by the 26-week trial. Percentages times in hypoglycemic, euglycemia and hyperglycemic ranges were generated from rtCGM and SMBG data using last observation carry forward method (zero-order hold) and linear interpolation (first-order hold). Results: Participants had a median (interquartile range [IQR]) age of 43.0 (31.0-55.0) years, and hemoglobin A1C of 53 (49-57) mmol/mol [7.0 (6.6-7.4)%]. The median (IQR) %TIR was significantly higher with rtCGM than with SMBG; 63.0 (55.9-71.0)% versus 54.6 (45.6-63.0)%, respectively, P < 0.001. Median %times in hypoglycemia and hyperglycemia were significantly different with SMBG than rtCGM (P < 0.001). SMBG-derived data using linear interpolation significantly differed from the carry forward method (P < 0.001 for all glycemic ranges). Differences reported were greater at night than during the day (P < 0.001 for all glycemic ranges). Conclusion: The %time in all glycemic ranges reported by SMBG an
Herrero P, El-Sharkawy M, Daniels J, et al., 2019, The bio-inspired artificial pancreas for type 1 diabetes control in the home: System architecture and preliminary results, Journal of Diabetes Science and Technology, Vol: 13, Pages: 1017-1025, ISSN: 1932-2968
BACKGROUND: Artificial pancreas (AP) technology has been proven to improve glucose and patient-centered outcomes for people with type 1 diabetes (T1D). Several approaches to implement the AP have been described, clinically evaluated, and in one case, commercialized. However, none of these approaches has shown a clear superiority with respect to others. In addition, several challenges still need to be solved before achieving a fully automated AP that fulfills the users' expectations. We have introduced the Bio-inspired Artificial Pancreas (BiAP), a hybrid adaptive closed-loop control system based on beta-cell physiology and implemented directly in hardware to provide an embedded low-power solution in a dedicated handheld device. In coordination with the closed-loop controller, the BiAP system incorporates a novel adaptive bolus calculator which aims at improving postprandial glycemic control. This paper focuses on the latest developments of the BiAP system for its utilization in the home environment. METHODS: The hardware and software architectures of the BiAP system designed to be used in the home environment are described. Then, the clinical trial design proposed to evaluate the BiAP system in an ambulatory setting is introduced. Finally, preliminary results corresponding to two participants enrolled in the trial are presented. RESULTS: Apart from minor technical issues, mainly due to wireless communications between devices, the BiAP system performed well (~88% of the time in closed-loop) during the clinical trials conducted so far. Preliminary results show that the BiAP system might achieve comparable glycemic outcomes to the existing AP systems (~73% time in target range 70-180 mg/dL). CONCLUSION: The BiAP system is a viable platform to conduct ambulatory clinical trials and a potential solution for people with T1D to control their glucose control in a home environment.
Avari P, Ramli R, Reddy M, et al., 2019, Rationale and protocol for the Assessment of Impact of Real-time Continuous Glucose Monitoring on people presenting with severe hypoglycaemia (AIR-CGM) study, BMC Endocrine Disorders, Vol: 19, ISSN: 1472-6823
Background: Severe hypoglycaemia carries a significant risk of morbidity and mortality for people with type 1 diabetes. Economic costs are also high, estimated at approximately £13 million annually in England, UK. Continuous glucose monitoring (CGM) has been shown to reduce hypoglycaemia and associated fear, improve overall glycaemia and quality of life, and is cost-effective. Despite effective pathways in place with high levels of resource utilization, it has been reported there are low levels of follow-up, therapy change and specialist intervention after severe hypoglycaemia. This study is designed to assess the impact of providing real-time CGM to people with type 1 diabetes, who have had a recent episode of severe hypoglycaemia (within 72hours), compared to standard care.Methods/Design: Fifty-five participants with type 1 diabetes and a recent episode of severe hypoglycaemia, who are CGM naïve, will be recruited to the study. Participants will be randomised to CGM or standard care. The primary outcome is percentage time spent in hypoglycaemia (<3.0mmol/L, 55mg/dL). Secondary outcomes include other measures of hypoglycaemia, time in euglycaemia, overall glucose status and patient reported qualitative measures.Discussion: This study assesses the impact of providing continuous glucose monitoring at the outset in individuals at highest risk of hypoglycaemia. Changing demand means that novel approaches need to be taken to healthcare provision. This study has the potential to shape future national standards.
Liu C, Vehí J, Avari P, et al., 2019, Long-term glucose forecasting using a physiological model and deconvolution of the continuous glucose monitoring signal, Sensors, Vol: 19, Pages: 1-19, ISSN: 1424-8220
(1) Objective: Blood glucose forecasting in type 1 diabetes (T1D) management is a maturing field with numerous algorithms being published and a few of them having reached the commercialisation stage. However, accurate long-term glucose predictions (e.g., >60 min), which are usually needed in applications such as precision insulin dosing (e.g., an artificial pancreas), still remain a challenge. In this paper, we present a novel glucose forecasting algorithm that is well-suited for long-term prediction horizons. The proposed algorithm is currently being used as the core component of a modular safety system for an insulin dose recommender developed within the EU-funded PEPPER (Patient Empowerment through Predictive PERsonalised decision support) project. (2) Methods: The proposed blood glucose forecasting algorithm is based on a compartmental composite model of glucose–insulin dynamics, which uses a deconvolution technique applied to the continuous glucose monitoring (CGM) signal for state estimation. In addition to commonly employed inputs by glucose forecasting methods (i.e., CGM data, insulin, carbohydrates), the proposed algorithm allows the optional input of meal absorption information to enhance prediction accuracy. Clinical data corresponding to 10 adult subjects with T1D were used for evaluation purposes. In addition, in silico data obtained with a modified version of the UVa-Padova simulator was used to further evaluate the impact of accounting for meal absorption information on prediction accuracy. Finally, a comparison with two well-established glucose forecasting algorithms, the autoregressive exogenous (ARX) model and the latent variable-based statistical (LVX) model, was carried out. (3) Results: For prediction horizons beyond 60 min, the performance of the proposed physiological model-based (PM) algorithm is superior to that of the LVX and ARX algorithms. When comparing the performance of PM against the secondly ranked method (ARX) on a 120 min
Dimakopoulou A, Jayasena CN, Radia UK, et al., 2019, Animal models of diabetes-related male hypogonadism, Frontiers in Endocrinology, Vol: 10, ISSN: 1664-2392
Hypogonadism is the clinical syndrome associated with low testosterone secretion in men. Hypogonadism affects ~37–57% men with diabetes mellitus (1). Male reproduction is orchestrated by the hypothalamo-pituitary-gonadal (HPG) axis, which regulates the biosynthesis of testosterone from the testes. Diabetes may cause hypogonadism through multiple mechanisms including suppression of hypothalamic gonadotrophin-releasing hormone (GnRH) secretion, or direct disruption of spermatogenesis (2). Clinical stigmata of hypogonadism include reduced libido, erectile dysfunction (ED) and reduced physical strength. This article will summarize the evidence from animal models including how diabetes affects male reproductive endocrine function and predisposes to hypogonadism.
Oliver N, Gimenez M, Calhoun P, et al., 2019, Continuous glucose monitoring in people with type 1 diabetes on multiple-dose injection therapy: the relationship between glycemic control and hypoglycemia, Diabetes Care, Vol: 43, Pages: 53-58, ISSN: 0149-5992
OBJECTIVE: The inverse relationship between overall glucose control and hypoglycemia risk is weakened by the use of real-time continuous glucose monitoring (rtCGM). We assess the relationship between glucose control and hypoglycemia in people with type 1 diabetes using multiple-dose injection (MDI) regimens, including those at highest risk of hypoglycemia. RESEARCH DESIGN AND METHODS: CGM data from the intervention (rtCGM) and control (self-monitored blood glucose [SMBG]) phases of the Multiple Daily Injections and Continuous Glucose Monitoring in Diabetes (DIAMOND) and HypoDE studies were analyzed. The relationship between glucose control (HbA1c and mean rtCGM glucose levels) and percentage time spent in hypoglycemia was explored for thresholds of 3.9 mmol/L (70 mg/dL) and 3.0 mmol/L (54 mg/dL), and ANOVA across the range of HbA1c and mean glucose was performed. RESULTS: A nonlinear relationship between mean glucose and hypoglycemia was identified at baseline, with the steepest relationship seen at lower values of mean glucose. The use of rtCGM reduces the exposure to hypoglycemia at all thresholds and flattens the relationship between overall glucose and hypoglycemia, with the most marked impact at lower values of mean glucose and HbA1c. Exposure to hypoglycemia varied at all thresholds across the range of overall glucose at baseline, in the SMBG group, and with rtCGM, but the relationships were weaker in the rtCGM group. CONCLUSIONS: Usage of rtCGM can flatten and attenuate the relationship between overall glucose control and hypoglycemia, exerting its greatest impact at lower values of HbA1c and mean glucose in people with type 1 diabetes using MDI regimens and at highest risk of hypoglycemia.
Guemes A, Cappon G, Hernandez B, et al., 2019, Predicting quality of overnight glycaemic control in type 1 diabetes using binary classifiers, IEEE Journal of Biomedical and Health Informatics, ISSN: 2168-2194
In type 1 diabetes management, maintaining nocturnal blood glucose within target range can be challenging. Although semi-automatic systems to modulate insulin pump delivery, such as low-glucose insulin suspension and the artificial pancreas, are starting to become a reality, their elevated cost and performance below user expectations is hindering their adoption. Hence, a decision support system that helps people with type 1 diabetes, on multiple daily injections or insulin pump therapy, to avoid undesirable overnight blood glucose fluctuations (hyper- or hypoglycaemic) is an attractive alternative. In this paper, we introduce a novel data-driven approach to predict the quality of overnight glycaemic control in people with type 1 diabetes by analyzing commonly gathered data during the day-time period (continuous glucose monitoring data, meal intake and insulin boluses). The proposed approach is able to predict whether overnight blood glucose concentrations are going to remain within or outside the target range, and therefore allows the user to take the appropriate preventive action (snack or change in basal insulin). For this purpose, a number of popular established machine learning algorithms for classification were evaluated and compared on a publicly available clinical dataset (i.e. OhioT1DM). Although there is no clearly superior classification algorithm, this study indicates that, by using commonly gathered data in type 1 diabetes management, it is possible to predict the quality of overnight glycaemic control with reasonable accuracy (AUC-ROC= 0.7).
Bhattarai S, Godsland IF, Misra S, et al., 2019, Metabolic health and vascular complications in type 1 diabetes, Journal of Diabetes and its Complications, Vol: 33, Pages: 634-640, ISSN: 1056-8727
AIMS: Optimal glycaemic control benefits risk of microvascular and macrovascular complications in type 1 diabetes (T1DM) but the importance of other components of metabolic health is less certain, particularly in the context of routine clinical practice. METHODS: Data for this cross-sectional analysis derived from a database covering inner North West London adult diabetes clinics. People with T1DM and with complete information for height, weight, blood pressure and serum high and low-density lipoprotein cholesterol (HDL-c and LDL-c) and triglyceride concentration measurements were included. RESULTS: Among the 920 participants, those with complications were older and had longer duration of diabetes but had similar HbA1c to people without complications. Systolic hypertension and low HDL-c were independently associated with complications. From having 0 risk factors, the prevalence of micro and macrovascular disease increased with increasing number of risk factors. Relative to those with ≥1 risk factor, those with 0 risk factors (n = 179) were at lower risk of retinopathy (OR 0.6 (0.4-0.9), p = 0.01) and nephropathy [OR 0.1 (0.04-0.3), p = 0.002], independent of individual characteristics. CONCLUSIONS: In routine clinical management of T1DM, associations between lipid and blood pressure risk factors and prevalent micro and macrovascular disease remain, implying that more intensive risk factor management may be beneficial.
Humphreys A, Bravis V, Kaur A, et al., 2019, Individual and diabetes presentation characteristics associated with partial remission status in children and adults evaluated up to 12 months following diagnosis of type 1 diabetes: An ADDRESS-2 (After Diagnosis Diabetes Research Support System-2) study analysis, Diabetes Research and Clinical Practice, Vol: 155, ISSN: 0168-8227
AIMS: People with recently-diagnosed type 1 diabetes mellitus (T1D) may undergo a transient period of glycaemic control with less exogenous insulin. Identification of predictors of this 'remission' could inform a better understanding of glycaemic control. METHODS: Participants in the ADDRESS-2 study were included who had 1 or 2 assessments of remission status (coincident insulin dose and HbA1c measurement, with remission defined by ≤0.4 units insulin/kg-body-weight/day with HbA1c < 53 mmol/mol). Demographic and clinical presentation characteristics were compared according to remission status and predictors of remission were explored by logistic regression analysis. RESULTS: 1470 first and 469 second assessments of remission status were recorded within 12 months of diagnosis of T1D. Step increases in the probability of remission were identified at age-at-diagnosis 20 years and 3 months after diagnosis (both p < 0.001). Among those aged < 20 years, remission was associated with male gender (p = 0.02), no ketoacidosis (p = 0.02) and fewer than 2 symptoms at presentation (p = 0.004). None of these characteristics predicted remission in those aged ≥ 20 years. In the subgroup with two assessments, transition to remission was independently associated with first remission assessment in months 1-2 post-diagnosis (p = 0.01), with age-at-diagnosis ≥ 20 years (p = 0.01) and, in those aged < 20 years, with an early HbA1c of <57 mmol/mol. Adiposity, ethnicity, autoantibody status and other autoimmune disease were unrelated to remission. CONCLUSIONS: For those diagnosed before 20 years of age, males, ketoacidosis-free, with fewer symptoms and low early HbA1c were more likely to experience remission, but remission was most likely in anyone aged ≥ 20 at diagnosis.
Avari P, Moscardo V, Jugnee N, et al., 2019, Glycemic variability and hypoglycemic excursions with continuous glucose monitoring compared to intermittently scanned continuous glucose monitoring in adults With highest risk type 1 diabetes, Journal of Diabetes Science and Technology, Pages: 1-8, ISSN: 1932-2968
BACKGROUND: The I-HART CGM study has shown that real-time continuous glucose monitoring (rtCGM) has greater beneficial impact on hypoglycemia than intermittently scanned continuous glucose monitoring (iscCGM) in adults with type 1 diabetes at high risk (Gold score ≥4 or recent severe hypoglycemia using insulin injections). In this subanalysis, we present the impact of rtCGM and iscCGM on glycemic variability (GV). METHODS: Forty participants were recruited to this parallel group study. Following two weeks of blinded rtCGM (DexcomG4), participants were randomized to rtCGM (Dexcom G5; n = 20) or iscCGM (Freestyle Libre; n = 20) for eight weeks. An open-extension phase enabled participants on rtCGM to continue for a further eight weeks and those on iscCGM to switch to rtCGM over this period. Glycemic variability measures at baseline, 8- and 16-week endpoints were compared between groups. RESULTS: At the eight-week endpoint, between-group differences demonstrated significant reduction in several GV measures with rtCGM compared to iscCGM (GRADE%hypoglycemia, index of glycemic control [IGC], and average daily risk range [ADRR]; P < .05). Intermittently scanned continuous glucose monitoring reduced mean average glucose and glycemic variability percentage and GRADE%hyperglycemia compared with rtCGM (P < .05). At 16 weeks, the iscCGM group switching to rtCGM showed significant improvement in GRADE%hypoglycemia, personal glycemic status, IGC, and ADRR. CONCLUSION: Our data suggest most, but not all, GV measures improve with rtCGM compared with iscCGM, particularly those measures associated with the risk of hypoglycemia. Selecting appropriate glucose monitoring technology to address GV in this high-risk cohort is important to minimize the risk of glucose extremes and severe hypoglycemia. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT03028220.
Rilstone S, Reddy M, Oliver N, 2019, Glycemic index, extended bolusing, and diabetes education in insulin pump therapy (GLIDE: A pilot study), Diabetes Technology and Therapeutics, Vol: 21, Pages: 452-455, ISSN: 1520-9156
Background: There is no published evidence on whether advanced bolus education affects outcomes in insulin pump-treated type 1 diabetes. We assess the feasibility of delivering a clinical education program on rates of digestion and bolusing, and to assess its preliminary impact.Methods: An interactive education session on glycemic index (GI), extended bolusing, and superbolusing was developed and assessed in a nonrandomized single-arm study for 12 weeks. Insulin pump-treated participants with type 1 diabetes were recruited. Glucose outcomes were assessed by blinded continuous glucose monitoring after the consumption of high-fat and high-GI test meal. The primary outcome measure was 8-h glucose area under the curve (AUC) after high-fat meals, before and after intervention. Secondary outcomes included time spent in hypoglycemia, quality of life, treatment satisfaction, HbA1c, frequency of use of extended boluses, and postprandial AUC.Results: Eleven participants completed the study [mean (SD) age 42.3 (12.8) years, baseline HbA1c 57.3 (10.0) mmol/mol, duration of diabetes 19.5 (9.9) years]. AUC for glucose after test meals did not differ significantly after education except for in the first 2 h after the high-GI meal [precourse 83.1 (0.23–88.9), postcourse 5.38 (−16.2 to 50.8)]. Percentage time spent in hypoglycemia (<3.9 and <3.3 mmol/L) fell at week 12 compared with baseline [5.8 (IQR 2.1–8.3) % to 4.3 (IQR 2.1–5.4) %, P = 0.013, and 2.9 (IQR 1.2–3.9) % to 1.6 (IQR 0.7–2.4) %, P = 0.029, respectively].Conclusion: Delivering an education program to support advanced boluses is feasible and may reduce exposure to hypoglycemia. A further trial is required to confirm the findings.
Ramli R, Reddy M, Oliver N, 2019, Artificial pancreas: current progress and future outlook in the treatment of type 1 diabetes., Drugs, Vol: 79, Pages: 1089-1101, ISSN: 1179-1950
Type 1 diabetes is characterised by insulin deficiency caused by autoimmune destruction of the pancreatic beta cells. The treatment of type 1 diabetes is exogenous insulin in the form of multiple daily injections or continuous subcutaneous insulin infusion. Advances in diabetes technology have been exponential in the past few decades, culminating in studies to develop an automated artificial pancreas, also known as the closed-loop system. This has recently led to a commercially available, hybrid artificial pancreas in the USA and Europe. This review article aims to provide an overview of the rationale for an artificial pancreas system and an update of the current state of artificial pancreas development. We explore the different types of artificial pancreas systems being studied, including the use of adjunctive therapy, and the use of these systems in different groups of users. In addition, we discuss the potential psychosocial impact and the challenges and limitations of implementing artificial pancreas use into clinical practice.
Srivanichakorn W, Godsland IF, Washirasaksiri C, et al., 2019, Cardiometabolic risk factors in Thai individuals with prediabetes treated in a high-risk, prevention clinic - unexpected relationship between HDL cholesterol and glycaemia in men, Journal of Diabetes Investigation, Vol: 10, Pages: 771-779, ISSN: 2040-1124
BACKGROUND: Relationships between cardiometabolic risk and glycaemia have been rarely studied in people under clinical evaluation and treatment for cardiometabolic risk and with prediabetes. We investigated relationships between glycaemia and cardiometabolic risk factors in clinic participants with prediabetes. METHODS: This was a cross-sectional analysis of data collected at a centre in Thailand. Clinic attendees were at high-risk of diabetes or cardiovascular disease, with HbA1c 39-<48 mmol/mol or fasting plasma glucose (FPG) 5.6-<7.0 mmol/L. The relationships between glycaemia and cardiometabolic risk factors were explored. RESULTS: Of 357 participants, two or more insulin resistance-related metabolic disturbances were present in 84%; 61% took a statin and 75% an antihypertensive agent. Independently of age, gender, adiposity, medication use, possible NAFLD and gender-glycaemia interaction, neither FPG nor HbA1c were associated with variation in any other cardiometabolic risk factors. HDL cholesterol decreased with HbA1c in women (female*HbA1c interaction, p=0.03) but, unexpectedly, increased with FPG in men (male*FPG interaction, p=0.02). CONCLUSION: Overall, in Thai people treated for high-cardiometabolic risk and with prediabetes defined by FPG and/or HbA1c, neither FPG nor HbA1c were associated with other cardiometabolic risk factors. However, according to gender, HDL cholesterol showed the expected relationship with glycaemia in women but the reverse in men.
Agha-Jaffar R, Oliver NS, Kostoula M, et al., 2019, Hyperglycemia recognised in early pregnancy is phenotypically type 2 diabetes mellitus not gestational diabetes mellitus: a case control study, Journal of Maternal-Fetal and Neonatal Medicine, Pages: 1-7, ISSN: 1476-4954
OBJECTIVE: Gestational diabetes mellitus is defined as "diabetes recognized in the second or third trimester that is not clearly overt diabetes". Evidence relating to women with hyperglycemia early in pregnancy is limited. We aimed to evaluate women diagnosed with hyperglycemia early in pregnancy (eGDM) and compared them to those with pregestational established type 2 diabetes mellitus (T2DM) and gestational diabetes diagnosed routinely at 24-28-week gestation (rtGDM) to determine if the length of exposure to hyperglycemia adversely affected outcomes. METHODS: Forty consecutive women with eGDM who attended a multidisciplinary antenatal clinic were reviewed. Two separate BMI-matched control groups were identified, recognized pregestational T2DM (n = 80) and rtGDM (n = 80). Baseline demographics and outcomes were compared. RESULTS: A higher proportion of women in the eGDM and T2DM group required insulin and the incidence of hypertensive disorders was similarly increased compared with the rtGDM group (88.6, 77.0 versus 8.1%, p < .001 and 42.5%, 37.5 versus 12.5% p < .001, respectively). The proportion of infants born small for gestational age varied (eGDM 11.1%, T2DM 13.0%, and rtGDM 2.5%, p=.049). Postpartum, 7.5% of eGDM women were diagnosed with T2DM versus 1.3% in the rtGDM group (p<.001). CONCLUSIONS: These novel data demonstrate that the length of exposure to glucose adversely affects materno-foetal outcomes independent of maternal adiposity.
Oliver N, Holt RIG, 2019, The James Lind Alliance research priorities for diabetes., Diabet Med, Vol: 36, Pages: 267-268
Reddy M, Oliver N, 2019, Reply to Letter by Seibold regarding Monika Reddy, Narvada Jugnee, Sinthuka Anantharaja, and Nick Oliver, Switching from Flash Glucose Monitoring to Continuous Glucose Monitoring on Hypoglycemia in Adults with Type 1 Diabetes at High Hypoglycemia Risk: The Extension Phase of the I HART CGM Study., Diabetes Technol Ther, Vol: 21, Pages: 99-100
Hill NE, Rilstone S, Stacey M, et al., 2018, Changes in northern hemisphere male international rugby union players body mass and height between 1955 and 2015, BMJ Open Sport and Exercise Medicine, Vol: 4, ISSN: 2055-7647
Objectives We sought to establish the effects of professionalism, which officially began in 1995, on the body mass and height of northern hemisphere male international rugby union (RU) players. We hypothesised that mass would significantly increase following professionalism. We also investigated the changes in size of players according to their playing position, and we compared changes to rugby league (RL) players and the public.Methods The body mass and height of players representing their international team for that country’s first game of the Five Nations in 1955, 1965, 1975, 1985 and 1995 and, for 2005 and 2015, the Six Nations, were collected from matchday programmes. RL players’ data were collected from the Challenge Cup final games played in the same years.Results International RU player body mass has significantly increased since 1995. In 1955 mean (±SD) player body mass was 84.8 kg (±8.2); in 2015, it was 105.4 kg (±12.1), an increase of 24.3%. Between 1955 and 2015, the body mass of forwards increased steadily, whereas that of backs has mostly gone up since 1995. RU player body mass gain has exceeded that of RL, but the age-matched difference between RU players and the public has remained relatively constant.Conclusions The factors influencing the gain in body mass of rugby players are legion; however, we believe that the interpretation of the law relating to the scrum put-in and changes allowing substitutions have, at least in part, contributed to the observed changes. Injury severity is increasing, and this may be linked to greater forces (caused by greater body mass) occurring in contact. RU law makers should adjust the rules to encourage speed and skill at the expense of mass.
Oliver N, Reddy M, 2018, Reply to Seibold and Schlaeger: Comparison of continuous and flash glucose monitoring in Type 1 diabetes: methodological inconsistency precludes hypoglycaemia conclusions, Diabetic Medicine, Vol: 35, Pages: 1619-1620, ISSN: 0742-3071
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