Adaptive bolus calculators for people with type 1 diabetes: A systematic review.

AIM: To conduct a systematic review of studies assessing adaptive insulin bolus calculators for people with type 1 diabetes (T1D). METHODS: Electronic databases (Medline, Embase and Web of Science) were systematically searched from date of inception to 13 October 2022 for single-arm or randomized controlled studies assessing adaptive bolus calculators only, in children or adults with T1D on multiple daily injections or insulin pumps with glycaemic outcomes reported. The Clinicaltrials.gov registry was searched for recently completed studies evaluating decision support in T1D. The quality of extracted studies was assessed using the Standard Quality Assessment criteria and the Cochrane Risk of Bias assessment tool. RESULTS: Six studies were identified. Extracted data were synthesized in a descriptive review because of heterogeneity. All the studies were small feasibility studies or were not suitably powered, and all were deemed to be at a high risk of performance and detection bias because they were unblinded. Overall, these studies did not show a significant glycaemic improvement. Two studies showed a reduction in postprandial time below range or an incremental change in blood glucose concentration; however, these were in controlled environments over a short duration. CONCLUSIONS: There are limited clinical trials evaluating adaptive bolus calculators. Although results from small trials or in-silico data are promising, further studies are required to support personalized and adaptive management of T1D.

The impact of socio-economic deprivation on access to diabetes technology in adults with type 1 diabetes.

BACKGROUND: With advances in technology, there is an emerging concern that inequalities exist in provision and diabetes outcomes in areas of greater deprivation. We assess the relationship between socio-economic status and deprivation with access to diabetes technology and their outcomes in adults with type 1 diabetes. METHODS: Retrospective, observational analysis of adults attending a tertiary centre, comprising three urban hospitals in the UK. Socio-economic deprivation was assessed by the English Indices of Deprivation 2019. Data analysis was performed using one-way ANOVAs and chi-squared tests. RESULTS: In total, 1631 adults aged 44 ± 15 years and 758 (47%) women were included, with 391 (24%) using continuous subcutaneous insulin infusion, 312 (19%) using real-time continuous glucose monitoring and 558 (34%) using intermittently scanned continuous glucose monitoring. The highest use of diabetes technology was in the least deprived quintile compared to the most deprived quintile (67% vs. 45%, respectively; p < 0.001). HbA1c outcomes were available in 400 participants; no association with deprivation was observed (p = 0.872). Participation in structured education was almost twice as high from the most deprived to the least deprived groups (23% vs. 43%; p < 0.001). Adults with white or mixed ethnicity were more likely to use technology compared to black ethnicity (60% vs. 40%; p < 0.001). CONCLUSIONS: Adults living in the most deprived quintile had less technology use. Irrespective of socio-economic status or ethnicity, glycaemia was positively affected in all groups. It is imperative that health disparities are further addressed.

Optimizing type 1 diabetes after multiple daily injections and capillary blood monitoring: Pump or sensor first? A meta-analysis using pooled differences in outcome measures.

AIMS: Most people living with type 1 diabetes self-manage using multiple daily injection (MDI) insulin regimens and self-monitoring of blood glucose (SMBG). Continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) are adjuncts to education and support self-management optimization. The aim of this systematic review and meta-analysis was to assess which first-line technology is most effective. METHODS: Electronic databases (MEDLINE, EMBASE and WEB OF SCIENCE) were systematically searched from 1999 to September 2020. Randomized controlled trials comparing either CSII with MDI or CGM with SMBG in adults with type 1 diabetes were included. Data were extracted in duplicate by two reviewers, and were analysed to assess individual and overall treatment effect measures (PROSPERO registration: CRD42020149915). RESULTS: Glycated haemoglobin was significantly reduced for CGM when compared with SMBG [Cohen's d - 0.62 (95% CI -0.79 to -0.45)] and for CSII when compared with MDI [Cohen's d - 0.44 (95% CI -0.67 to -0.22)]. Rates of severe hypoglycaemia were significantly reduced with CGM compared with SMBG, but did not change for CSII when compared with MDI. Episodes of diabetic ketoacidosis were more likely to occur with CSII than MDI. Both CSII and CGM reduced glucose standard deviation, compared with MDI and SMBG respectively. CONCLUSIONS: Both CGM and CSII remain impactful interventions compared with SMBG and MDI but in adults with type 1 diabetes and in the contexts in which they have been studied, CGM might have a greater positive impact on glycaemic variability and severe hypoglycaemia than CSII, when added to MDI and SMBG. A head-to-head study, including patient reported outcomes, is required to explore these findings further.

Rationale and protocol for the Assessment of Impact of Real-time Continuous Glucose Monitoring on people presenting with severe Hypoglycaemia (AIR-CGM) study.

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 72 h), 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 (< 3.0 mmol/L, 55 mg/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. TRIAL REGISTRATION: NCT03748433 , November 2018 (UK).

Long-Term Glucose Forecasting Using a Physiological Model and Deconvolution of the Continuous Glucose Monitoring Signal.

(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 prediction horizon, the percentage improvement on prediction accuracy measured with the root mean square error, A-region of error grid analysis (EGA), and hypoglycaemia prediction calculated by the Matthews correlation coefficient, was 18.8 % , 17.9 % , and 80.9 % , respectively. Although showing a trend towards improvement, the addition of meal absorption information did not provide clinically significant improvements. (4) Conclusion: The proposed glucose forecasting algorithm is potentially well-suited for T1D management applications which require long-term glucose predictions.

Switching from Intermittently Scanned Continuous Glucose Monitoring to Real-Time Continuous Glucose Monitoring with a Predictive Urgent Low Soon Alert Reduces Exposure to Hypoglycemia.

Differences in the effectiveness of real-time continuous glucose monitoring (rtCGM) and intermittently scanned continuous glucose monitoring (isCGM) in type 1 diabetes (T1D) are reported. The impact on percent time in range of switching from an isCGM with glucose threshold-based optional alerts only (FreeStyle Libre 2 [FSL2]) to an rtCGM (Dexcom G7) with an urgent low soon predictive alert was assessed, alongside other secondary outcomes including hemoglobin A1c (HbA1c) and other continuous glucose monitoring metrics. Adults with T1D using FSL2 were switched to Dexcom G7 for 12 weeks. HbA1c and continuous glucose data during FSL2 and Dexcom G7 use were compared. Data from 29 participants (aged 44.8 ± 16.5 years, 12 male and 17 female) were analyzed. After switching to rtCGM, participants spent less time in hypoglycemia below 3.9 mmol/L (70 mg/dL) (3.0% [1.0%, 5.0%] vs. 2.0% [1.0%, 3.0%], P = 0.006) and had higher percentage achievement of time below 3.9 mmol/L (70 mg/dL) of <4% (55.2% vs. 82.8%, P = 0.005). Coefficient of variation was lower (39.3 ± 6.6% vs. 37.2 ± 5.6%, P = 0.008). In conclusion, adults with T1D who switched from isCGM to rtCGM may benefit from reduced exposure to hypoglycemia and glycemic variability.

Extraocular muscle Diffusion Weighted Imaging as a quantitative metric of posterior orbital involvement in thyroid associated orbitopathy.

OBJECTIVES: The clinical activity score (CAS) and European severity scale (ESS) are established clinical tools to assess thyroid eye disease (TED) but are limited in terms of subjectivity and their reliability in non-Caucasian individuals, and can underestimate significant disease in the posterior orbit. Preliminary data from pilot studies have shown that diffusion-weighted imaging (DWI) using extraocular muscle (EOM) apparent diffusion coefficient (ADC) measurements may provide complementary information in TED. This study expands on previous research to assess for correlations between clinical scores and EOM-ADCs in stratifying disease activity and severity in a large patient cohort from an ethnically diverse population. METHODS: A retrospective review of TED clinics between 2011 and 2021 identified 96 patients with a documented CAS and ESS and an orbital MRI that included DWI. From regions of interest manually placed on EOM bellies, the highest ADC was computed for each patient and analysed for correlations and associations with CAS and ESS using Spearman Rank correlation and Mann-Whitney U tests, and any potential discriminatory cut-offs using Receiver Operator Curve analyses. A p-value < 0.05 indicated statistical significance. RESULTS: EOM-ADCs showed a positive association with CAS (p ≤ 0.001). EOM-ADCs were higher in sight-threatening compared to mild disease (p ≤ 0.01). A cut-off of 995 mm2/s achieved AUC = 0.7744, equating to 77% sensitivity and 67% specificity for discrimination between mild-moderate and sight-threatening disease. CONCLUSION: EOM-ADCs correlate with higher scores of disease severity and activity in TED. Besides providing quantitative data to support clinical tools, EOM-ADC cut-offs may identify patients at risk of developing sight-threatening diseases. CRITICAL RELEVANCE STATEMENT: This study critically evaluates the limitations of conventional clinical assessment tools for TED and demonstrates the utility of DWI scans with ADC measurements in identifying active disease, offering valuable insights to advance clinical radiology practice. KEY POINTS: Conventional tools for TED assessment have subjective limitations. ADCs from non-echoplanar diffusion-weighted imaging correlate with clinical activity. Non-echoplanar diffusion-weighted imaging offers quantitative assessment to aid clinical practice reliability.

Adjustment of Maternal Variable Rate Insulin Infusions Using Real-Time Continuous Glucose Monitoring in Pregnant Women with Type 1 Diabetes.

Real-time continuous glucose monitoring (CGM) in hospital holds promise; however, further evidence is required on its use to guide adjustment of variable rate intravenous insulin infusion (VRIII). We retrospectively analyzed data from 20 women with type 1 diabetes during the peripartum period who were commenced on VRIII. Data were analyzed for CGM accuracy (Dexcom G6) using point-of-care glucose-CGM matched pairs. The study was entirely observational, with no deviation from standard clinical care. Twenty women were included; median age 30 (26-35) years with first glycated hemoglobin in pregnancy of 57 (49-60) mmol/mol. Overall median absolute relative difference was 6.1 (1.6-17.3)%. The total simulated CGM-adjusted VRIII was 2.5 U per hour, compared with 2.4 U per hour with capillary blood glucose-adjusted VRIII. In this retrospective analysis of CGM adjustment of maternal VRIII, we demonstrate early feasibility and considerable accuracy. Further prospective studies are required to confirm the safety and potential efficacy of CGM-based insulin titration.

Insulin Pumps and Hybrid Close Loop Systems Within Hospital: A Scoping Review and Practical Guidance From the Joint British Diabetes Societies for Inpatient Care.

This article is the second of a two-part series providing a scoping review and summary of the Joint British Diabetes Societies for Inpatient Care (JBDS-IP) guidelines on the use of diabetes technology in people with diabetes admitted to hospital. The first part reviewed the use of continuous glucose monitoring (CGM) in hospital. In this article, we focus on the use of continuous subcutaneous insulin infusion (CSII; insulin pumps) and hybrid closed-loop systems in hospital. JBDS-IP advocates enabling people who can self-manage and are willing and capable of using CSII to continue doing so as they would do out of hospital. CSII should be discontinued if the individual is critically ill or hemodynamically unstable. For individuals on hybrid closed-loop systems, the system should be discontinued from auto-mode, and may be used individually (as CGM only or CSII only, if criteria are met). Continuing in closed-loop mode may only be done so under specialist guidance from the Diabetes Team, where the diabetes teams are comfortable and knowledgeable about the specific devices used. Health care organizations need to have clear local policies and guidance to support individuals using these wearable technologies, and ensure the relevant workforce is capable and skilled enough to ensure their safe use within the hospital setting.

Continuous Glucose Monitoring Within Hospital: A Scoping Review and Summary of Guidelines From the Joint British Diabetes Societies for Inpatient Care.

Increasing numbers of people, particularly with type 1 diabetes (T1D), are using wearable technologies. That is, continuous subcutaneous insulin infusion (CSII) pumps, continuous glucose monitoring (CGM) systems, and hybrid closed-loop systems, which combine both these elements. Given over a quarter of all people admitted to hospital have diabetes, there is a need for clinical guidelines for when people using them are admitted to hospital. The Joint British Diabetes Societies for Inpatient Care (JBDS-IP) provide a scoping review and summary of guidelines on the use of diabetes technology in people with diabetes admitted to hospital.JBDS-IP advocates enabling people who can self-manage and use their own diabetes technology to continue doing so as they would do out of hospital. Whilst people with diabetes are recommended to achieve a target of 70% time within range (3.9-10.0 mmol/L [70-180 mg/dL]), this can be very difficult to achieve whilst unwell. We therefore recommend targeting hypoglycemia prevention as a priority, keeping time below 3.9 mmol/L (70 mg/dL) at < 1%, being aware of looming hypoglycemia if glucose is between 4.0 and 5.9 mmol/L (72-106 mg/dL), and consider intervening, particularly if there is a downward CGM trend arrow.Health care organizations need clear local policies and guidance to support individuals using diabetes technologies, and ensure the relevant workforce is capable and skilled enough to ensure their safe use within the hospital setting. The current set of guidelines is divided into two parts. Part 1, which follows below, outlines the guidance for use of CGM in hospital. The second part outlines guidance for use of CSII and hybrid closed-loop in hospital.

Using Technology to Improve Diabetes Care in Hospital: The Challenge and the Opportunity.

The past 10 years have seen a revolution in technology improving the lives of people with diabetes. This has implications for diabetes care in hospitalized inpatients. These technological developments have the potential to significantly improve the care of people with diabetes in hospital. Combining point of care glucose monitoring, electronic prescribing, electronic observations with electronic referral, and electronic health records allow teams to daily oversee the whole hospital population. To make the most of these tools as well as developing the use of pumps and glucose sensors in hospital, the diabetes team needs to work in new ways. To date, very little work has described how these should be combined. We describe how this technology can be combined to improve diabetes care in hospital.

How Can Point-of-Care Technologies Support In-Hospital Diabetes Care?

People with diabetes admitted to hospital are at risk of diabetes related complications including hypoglycaemia and diabetic ketoacidosis. Point-of-care (POC) tests undertaken at the patient bedside, for glucose, ketones, and other analytes, are a key component of monitoring people with diabetes, to ensure safety. POC tests implemented with a quality framework are critical to ensuring accuracy and veracity of results and preventing erroneous clinical decision making. POC results can be used for self-management of glucose levels in those well-enough and/or by healthcare professionals to identify unsafe levels. Connectivity of POC results to electronic health records further offers the possibility of utilising these results proactively to identify patients 'at risk' in real-time and for audit purposes. In this article, the key considerations when implementing POC tests for diabetes in-patient management are reviewed and potential to drive improvements using networked glucose and ketone measurements are discussed. In summary, new advances in POC technology should allow people with diabetes and the teams looking after them whilst in hospital to integrate to provide safe and effective care.

Variation in the Current Use of Technology to Support Diabetes Management in UK Hospitals: Results of a Survey of Health Care Professionals.

BACKGROUND: There has been a significant increase in the use of wearable diabetes technologies in the outpatient setting over recent years, but this has not consistently translated into inpatient use. METHODS: An online survey was undertaken to understand the current use of technology to support inpatient diabetes care in the United Kingdom. RESULTS: Responses were received from 42 different organizations representing 104 hospitals across the United Kingdom. Significant variation was found between organizations in the use of technology to support safe, effective inpatient diabetes care. Benefits of the use of technology were reported, and areas of good practice identified. CONCLUSION: Technology supports good inpatient diabetes care, but there is currently variation in its use. Guidance has been developed which should drive improvements in the use of technology and hence improvements in the safety and effectiveness of inpatient diabetes care. Key recommendations include implementation of this guidance (especially for continuous glucose monitoring), ensuring specialist support is available for the use of wearable diabetes technology in hospital, optimizing information sharing across the health care system, and making full use of data from networked glucose and ketone meters.

Accuracy and impact on quality of life of real-time continuous glucose monitoring in children with hyperinsulinaemic hypoglycaemia.

Objective: Continuous glucose monitoring (CGM) is the standard of care for glucose monitoring in children with diabetes, however there are limited data reporting their use in hyperinsulinaemic hypoglycaemia (HH). Here, we evaluate CGM accuracy and its impact on quality of life in children with HH. Methods: Real-time CGM (Dexcom G5 and G6) was used in children with HH aged 0-16years. Data from self-monitoring capillary blood glucose (CBG) and CGM were collected over a period of up to 28days and analysed. Quality of life was assessed by the PedsQL4.0 general module and PedsQL2.0 family impact module, completed by children and their parents/carers before and after CGM insertion. Analysis of accuracy metrics included mean absolute relative difference (MARD) and proportion of CGM values within 15, 20, and 30% or 15, 20, and 30 mg/dL of reference glucose values >100 mg/dL or ≤100 mg/dL, respectively (% 15/15, % 20/20, % 30/30). Clinical reliability was assessed with Clarke error grid (CEG) analyses. Results: Prospective longitudinal study with data analysed from 40 children. The overall MARD between reference glucose and paired CGM values (n=4,928) was 13.0% (Dexcom G5 12.8%, Dexcom G6 13.1%). The proportion of readings meeting %15/15 and %20/20 were 77.3% and 86.4%, respectively, with CEG analysis demonstrating 97.4% of all values in zones A and B. Within the hypoglycaemia range (<70 mg/dL), the median ARD was 11.4% with a sensitivity and specificity of 64.2% and 91.3%, respectively. Overall PedsQL child report at baseline and endpoint were 57.6 (50.5 - 75.8) and 87.0 (82.9 - 91.2), and for parents were 60.3 (44.8 - 66.0) and 85.3 (83.7 - 91.3), respectively (both p<0.001). Conclusion: Use of CGM for children with HH is feasible, with clinically acceptable accuracy, particularly in the hypoglycaemic range. Quality of life measures demonstrate significant improvement after CGM use. These data are important to explore use of CGM in disease indications, including neonatal and paediatric diabetes, cystic fibrosis and glycogen storage disorders.

A Novel Somatic Mutation Implicates ATP6V0D1 in Proinsulin Processing.

Context: Prohormone convertase 1/3 (PC1/3), encoded by protein convertase subtilisin kexin type 1 (PCSK1), converts inactive prohormones into biologically active peptides. Somatic mutations of insulinomas are associated with genetic defects interfering with control of insulin secretion from pancreatic beta cells. However, somatic mutations in proinsulinomas have not been described. Objective: We report a case of a proinsulinoma, with suppressed insulin and C-peptide levels. Methods: A 70-year-old woman presented with a 20-year history of "blackouts." During a 72-hour fast, blood glucose level dropped to 1.9 mmol/L with suppressed plasma insulin and C-peptide levels, but proinsulin levels were raised at 37 pmol/L (<10 pmol/L). Results: Imaging revealed 3 distinct DOTATATE-avid pancreatic lesions. Laparoscopic spleen-preserving distal pancreatomy was performed. In view of discordant insulin, C-peptide, and proinsulin levels, whole exome sequencing analysis was performed on the tumor. In the somatic exome of the tumor, we found mutations in PCSK expression regulators, as well as a novel truncating somatic mutation in ATP6V0D1, a subunit of the ion pump that acidifies the ß-cell compartments where the PCSKs act. Conclusion: Appropriately suppressed insulin levels in the context of hypoglycemia do not always indicate the absence of a neuroendocrine islet cell tumor and proinsulin levels may be indicated to solidify the diagnosis. In the context of elevated proinsulin levels, low insulin and C-peptide levels might be explained by somatic mutations that likely implicate proinsulin processing within the tumor. Furthermore, we propose several mechanistic candidates, including ATP6V0D1. Experimental validation using cellular approaches may in future confirm pathomechanisms involved in this rare condition.

The Accuracy of Continuous Glucose Sensors in People with Diabetes Undergoing Hemodialysis (ALPHA Study).

Objectives: Real-time and intermittently scanned continuous glucose monitoring are increasingly used for glucose monitoring in people with diabetes requiring renal replacement therapy, with limited data reporting their accuracy in this cohort. We evaluated the accuracy of Dexcom G6 and Abbott Freestyle Libre 1 glucose monitoring systems in people with diabetes undergoing hemodialysis. Methods: Participants on hemodialysis with diabetes (on insulin or sulfonylureas) were recruited. Paired sensor glucose from Dexcom G6 and Freestyle Libre 1 were recorded with plasma glucose analyzed using the Yellow Springs Instrument (YSI) method at frequent intervals during hemodialysis. Analysis of accuracy metrics included mean absolute relative difference (MARD), Clarke error grid (CEG) analysis and proportion of CGM values within 15% and 20% or 15 and 20 mg/dL of YSI reference values for blood glucose >100 or ≤100 mg/dL, respectively (% 15/15, % 20/20). Results: Forty adults (median age 64.7 [60.2-74.4] years) were recruited. Overall MARD for Dexcom G6 was 22.7% (2656 matched glucose pairs), and 11.3% for Libre 1 (n = 2785). The proportions of readings meeting %15/15 and %20/20 were 29.1% and 45.4% for Dexcom G6, respectively, and 73.5% and 85.6% for Libre 1. CEG analysis showed 98.9% of all values in zones A and B for Dexcom G6 and 99.8% for Libre 1. Conclusions: Our results indicate Freestyle Libre 1 is a reliable tool for glucose monitoring in adults on hemodialysis. Further studies are required to evaluate Dexcom G6 accuracy in people on hemodialysis.

Improved glycaemia during the Covid-19 pandemic lockdown is sustained post-lockdown and during the "Eat Out to Help Out" Government Scheme, in adults with Type 1 diabetes in the United Kingdom.

AIMS: The majority of studies report that the Covid-19 pandemic lockdown did not have a detrimental effect on glycaemia. We sought to explore the impact of lockdown on glycaemia and whether this is sustained following easing of restrictions. METHODS: Retrospective, observational analysis in adults and children with type 1 diabetes attending a UK specialist centre, using real-time or intermittently scanned continuous glucose monitoring. Data from the following 28-day time periods were collected: (i) pre-lockdown; (ii) during lockdown; (iii) immediately after lockdown; and (iv) a month following relaxation of restrictions (coinciding with Government-subsidised restaurant food). Data were analysed for times in glycaemic ranges and are expressed as median (IQR). RESULTS: 145 adults aged 35.5 (25.8-51.3) years with diabetes duration of 19.0 (7.0-29.0) years on multiple daily injections of insulin (60%) and continuous insulin infusion (40%) were included. In adults, % time in range (70-180mg/dL) increased during lockdown (60.2 (45.2-69.3)%) compared to pre-lockdown (56.7 (43.5-65.3)%; p<0.001). This was maintained in the post-lockdown time periods. Similarly, % time above range (>180mg/dL) reduced in lockdown compared to pre-lockdown (p = 0.01), which was sustained thereafter. In children, no significant changes to glycaemia were observed during lockdown. In multivariable analysis, a greater increase in %TIR 3.9-10mmol/L (70-180mg/dL) during lockdown was associated with higher levels of deprivation (coefficient: 4.208, 95% CI 0.588 to 7.828; p = 0.02). CONCLUSIONS: Glycaemia in adults improved during lockdown, with people from more deprived areas most likely to benefit. This effect was sustained after easing of restrictions, with government-subsidised restaurant eating having no adverse impact on glycaemia.

Association of Other Autoimmune Diseases With Thyroid Eye Disease.

Background: Thyroid eye disease (TED) is a potentially disfiguring and sight-threatening autoimmune (AI) orbitopathy, affecting up to 400,000 people in the UK. There are no accurate early predictors of TED severity. Although polyautoimmunity has been shown to affect AI disease severity, its influence on TED severity has never been investigated. The prevalence of polyautoimmunity among TED patients is also unclear, with discordant results reported in the literature. This study evaluates the prevalence of non-thyroid/"other" AI (OAI) conditions in an ethnically diverse TED cohort and assesses how polyautoimmunity affects TED severity and activity. Methods: A retrospective study of patients presenting to multidisciplinary TED clinics across three North-West London hospitals between 2011 and 2019. Data collected included: 1) demographics; 2) OAI conditions and management; 3) endocrine management of thyroid dysfunction; 4) details of TED and clinical activity score at presentation. Results: Two hundred and sixty-seven patients with a median age of 46 (35-54) years were included, 79.4% were female and 55% were Black, Asian and minority ethnic (BAME). Thirty-seven patients (13.9%) had OAI conditions, with rheumatoid arthritis (3.7%), vitiligo (3.0%) and psoriasis (3.0%) among the most prevalent. Of patients with OAI conditions, 43.2% (16/37) required immunosuppression prior to TED onset. Non-immunosuppressed patients with OAI conditions had a significantly higher clinical activity score at presentation than TED-only and previously immunosuppressed patients (p=0.02). No significant differences were observed in thyroid receptor antibody titers between these groups. Conclusions: This study finds a 13.9% prevalence of OAI conditions among TED patients. Patients with OAI conditions overall have a tendency for more severe and significantly more clinically active TED than those without OAI conditions. Larger, prospective studies are warranted to further evaluate polyautoimmunity as an early predictor of TED severity.

Safety and Feasibility of the PEPPER Adaptive Bolus Advisor and Safety System: A Randomized Control Study.

Background: The Patient Empowerment through Predictive Personalized Decision Support (PEPPER) system provides personalized bolus advice for people with type 1 diabetes. The system incorporates an adaptive insulin recommender system (based on case-based reasoning, an artificial intelligence methodology), coupled with a safety system, which includes predictive glucose alerts and alarms, predictive low-glucose suspend, personalized carbohydrate recommendations, and dynamic bolus insulin constraint. We evaluated the safety and efficacy of the PEPPER system compared to a standard bolus calculator. Methods: This was an open-labeled multicenter randomized controlled crossover study. Following 4-week run-in, participants were randomized to PEPPER/Control or Control/PEPPER in a 1:1 ratio for 12 weeks. Participants then crossed over after a washout period. The primary end-point was percentage time in range (TIR, 3.9-10.0 mmol/L [70-180 mg/dL]). Secondary outcomes included glycemic variability, quality of life, and outcomes on the safety system and insulin recommender. Results: Fifty-four participants on multiple daily injections (MDI) or insulin pump completed the run-in period, making up the intention-to-treat analysis. Median (interquartile range) age was 41.5 (32.3-49.8) years, diabetes duration 21.0 (11.5-26.0) years, and HbA1c 61.0 (58.0-66.1) mmol/mol. No significant difference was observed for percentage TIR between the PEPPER and Control groups (62.5 [52.1-67.8] % vs. 58.4 [49.6-64.3] %, respectively, P = 0.27). For quality of life, participants reported higher perceived hypoglycemia with the PEPPER system despite no objective difference in time spent in hypoglycemia. Conclusions: The PEPPER system was safe, but did not change glycemic outcomes, compared to control. There is wide scope for integrating PEPPER into routine diabetes management for pump and MDI users. Further studies are required to confirm overall effectiveness. Clinical trial registration: ClinicalTrials.gov NCT03849755.