Publications
385 results found
Rilstone S, Oliver N, 2020, A survey of UK dietitians on current advice to people with type 1 diabetes using insulin pump therapy in 2019, Publisher: WILEY, Pages: 114-114, ISSN: 0742-3071
Sharma A, Khan S, Chicco M, et al., 2020, New onset diabetes presenting with DKA , spontaneous pneumomediastinum and subcutaneous emphysema: a case series, Practical Diabetes, Vol: 37, Pages: 183-187, ISSN: 2047-2897
Ji H, Godsland I, Oliver NS, et al., 2020, Loss of association between HbA1c and vascular disease in older adults with type 1 diabetes, PLOS ONE, Vol: 15, ISSN: 1932-6203
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- Citations: 1
Misra S, Godsland IF, Bhardwaj N, et al., 2020, Type 2 Diabetes Diagnosed between 16-30 Years in South Asian and White Individuals Is Phenotypically Similar, 80th Scientific Sessions of the American-Diabetes-Association (ADA), Publisher: AMER DIABETES ASSOC, ISSN: 0012-1797
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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", Journal of Diabetes Science and Technology, Vol: 14, Pages: 697-698, ISSN: 1932-2968
Guemes A, Cappon G, Hernandez B, et al., 2020, Predicting quality of overnight glycaemic control in type 1 diabetes using binary classifiers, IEEE Journal of Biomedical and Health Informatics, Vol: 24, Pages: 1439-1446, 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).
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, DIABETIC MEDICINE, Vol: 37, Pages: 511-512, ISSN: 0742-3071
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 and Metabolic Disorders, Vol: 21, Pages: 577-597, ISSN: 1389-9155
Hyperinsulinemic hypoglycemia (HH) is characterized by unregulated insulin release, leading to persistently low blood glucose concentrations with lack of alternative fuels, which increases the risk of neurological damage in these patients. It is the most common cause of persistent and recurrent hypoglycemia in the neonatal period. HH may be primary, Congenital HH (CHH), when it is associated with variants in a number of genes implicated in pancreatic development and function. Alterations in fifteen genes have been recognized to date, being some of the most recently identified mutations in genes HK1, PGM1, PMM2, CACNA1D, FOXA2 and EIF2S3. Alternatively, HH can be secondary when associated with syndromes, intra-uterine growth restriction, maternal diabetes, birth asphyxia, following gastrointestinal surgery, amongst other causes. CHH can be histologically characterized into three groups: diffuse, focal or atypical. Diffuse and focal forms can be determined by scanning using fluorine-18 dihydroxyphenylalanine-positron emission tomography. Newer and improved isotopes are currently in development to provide increased diagnostic accuracy in identifying lesions and performing successful surgical resection with the ultimate aim of curing the condition. Rapid diagnostics and innovative methods of management, including a wider range of treatment options, have resulted in a reduction in co-morbidities associated with HH with improved quality of life and long-term outcomes. Potential future developments in the management of this condition as well as pathways to transition of the care of these highly vulnerable children into adulthood will also be discussed.
Johnson A, Hill NE, Godsland I, et al., 2020, Glycemic Tracking Before and After Insulin Pump Initiation., J Diabetes Sci Technol, Pages: 1932296820910506-1932296820910506
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
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Spence R, Li K, Uduku C, et al., 2020, A NOVEL HAND-HELD INTERFACE SUPPORTING THE SELF-MANAGEMENT OF TYPE 1 DIABETES, Publisher: MARY ANN LIEBERT, INC, Pages: A58-A58, ISSN: 1520-9156
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Daniels J, Zhu T, Li K, et al., 2020, Arises: an advanced clinical decision support platform for the management of type 1 diabetes, The conference name (including place and date(s) of the conference): 13th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD 2020), Publisher: Mary Ann Liebert, Pages: A57-A57, ISSN: 1520-9156
Zhu T, Li K, Uduku C, et al., 2020, PERSONALIZED MEAL INSULIN BOLUS FOR TYPE 1 DIABETES USING DEEP REINFORCEMENT LEARNING, Publisher: MARY ANN LIEBERT, INC, Pages: A115-A116, ISSN: 1520-9156
Herrero P, Alalitei A, Reddy M, et al., 2020, Robust determination of the optimal continuous glucose monitoring length of intervention to evaluate long-term glycaemic control, 13th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD 2020), Publisher: Mary Ann Liebert, Pages: A130-A130, ISSN: 1520-9156
Rilstone S, Oliver N, 2020, A SURVEY OF UK DIETITIANS ON CURRENT ADVICE TO PEOPLE WITH TYPE 1 DIABETES USING INSULIN PUMP THERAPY IN 2019 COMPARED WITH 2015, Publisher: MARY ANN LIEBERT, INC, Pages: A175-A176, ISSN: 1520-9156
Ranjani H, Nitika S, Hariharan R, et al., 2020, SYSTEMATIC REVIEW AND SCIENTIFIC RATING OF COMMERCIAL APPS AVAILABLE IN INDIA FOR HEALTHY LIFESTYLE/ FITNESS/DIABETES PREVENTION, Publisher: MARY ANN LIEBERT, INC, Pages: A197-A197, ISSN: 1520-9156
Avari P, Leal Y, Wos M, et al., 2020, Efficacy and safety of the patient empowerment through predictive personalised decision support (pepper) system: an open-label randomised controlled trial, The conference name (including place and date(s) of the conference): 13th International Conference on Advanced Technologies & Treatments for Diabetes (ATTD 2020), Publisher: Mary Ann Liebert, Pages: A104-A104, ISSN: 1520-9156
Waite M, Aldea A, Avari P, et al., 2020, TRUST AND CONTEXTUAL ENGAGEMENT WITH THE PEPPER SYSTEM: THE QUALITATIVE FINDINGS OF A CLINICAL FEASIBILITY STUDY, Publisher: MARY ANN LIEBERT, INC, Pages: A18-A19, ISSN: 1520-9156
Rilstone S, Oliver N, 2020, A SURVEY OF UK DIETITIANS ON CURRENT ADVICE TO PEOPLE WITH TYPE 1 DIABETES USING INSULIN PUMP THERAPY IN 2019, Publisher: MARY ANN LIEBERT, INC, Pages: A175-A175, ISSN: 1520-9156
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)
Duce DA, Martin C, Russell A, et al., 2020, Visualizing Usage Data from a Diabetes Management System, Pages: 1-9
This article explores the role for visualization in interpreting data collected by a customised analytics framework within a healthcare technology project. It draws on the work of the EU-funded PEPPER project, which has created a personalised decision-support system for people with type 1 diabetes. Our approach was an exercise in exploratory visualization, as described by Bergeron's three category taxonomy. The charts revealed different patterns of interaction, including variability in insulin dosing schedule, and potential causes of rejected advice. These insights into user behaviour are of especial value to this field, as they may help clinicians and developers understand some of the obstacles that hinder the uptake of diabetes technology.
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.
Uduku C, Reddy M, Oliver N, 2020, Clinical impact of CGM use, Glucose Monitoring Devices: Measuring Blood Glucose to Manage and Control Diabetes, Pages: 135-158, ISBN: 9780128168844
Blood glucose monitoring is essential for making safe and informed therapeutic changes in individuals on insulin treatment. Fingerprick capillary glucose monitoring is recommended at least four times daily as a mean of improving glycemic control and reducing the risk of diabetes-related complications. Continuous glucose monitoring (CGM) facilitates real-time treatment optimization and empowers self-management by delivering automated glucose levels at 5-min intervals. In reducing the burden of fingerprick tests and providing low- and high-glucose alerts, CGM overcomes many limitations of self-monitoring of blood glucose and longitudinal measures of glycemic control such as HbA1c. This chapter addresses the clinical benefits and limitations of CGM as an adjunctive tool alongside capillary blood glucose self-monitoring. The current clinical application of CGM and commercially available systems will be discussed and linked to a review of CGM clinical trial outcomes. Lastly, the successful integration of CGM in sensor-augmented pumps and closed-loop artificial pancreas systems will be introduced.
Barron E, Misra S, English E, et al., 2020, Experience of point-of-care HbA1c testing in the English National Health Service Diabetes Prevention Programme: an observational study, BMJ OPEN DIABETES RESEARCH & CARE, Vol: 8
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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.
Oliver N, Reddy M, Marriott C, et al., 2019, Open source automated insulin delivery: addressing the challenge., NPJ Digit Med, Vol: 2
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.
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, 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
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