Hyperglycaemic crises in adults with diabetes: a consensus report.

The American Diabetes Association (ADA), European Association for the Study of Diabetes (EASD), Joint British Diabetes Societies for Inpatient Care (JBDS), American Association of Clinical Endocrinology (AACE) and Diabetes Technology Society (DTS) convened a panel of internists and diabetologists to update the ADA consensus statement on hyperglycaemic crises in adults with diabetes, published in 2001 and last updated in 2009. The objective of this consensus report is to provide up-to-date knowledge about the epidemiology, pathophysiology, clinical presentation, and recommendations for the diagnosis, treatment and prevention of diabetic ketoacidosis (DKA) and hyperglycaemic hyperosmolar state (HHS) in adults. A systematic examination of publications since 2009 informed new recommendations. The target audience is the full spectrum of diabetes healthcare professionals and individuals with diabetes.

Incidence, prevalence, and co-occurrence of autoimmune disorders over time and by age, sex, and socioeconomic status: a population-based cohort study of 22 million individuals in the UK.

BACKGROUND: A rise in the incidence of some autoimmune disorders has been described. However, contemporary estimates of the overall incidence of autoimmune diseases and trends over time are scarce and inconsistent. We aimed to investigate the incidence and prevalence of 19 of the most common autoimmune diseases in the UK, assess trends over time, and by sex, age, socioeconomic status, season, and region, and we examine rates of co-occurrence among autoimmune diseases. METHODS: In this UK population-based study, we used linked primary and secondary electronic health records from the Clinical Practice Research Datalink (CPRD), a cohort that is representative of the UK population in terms of age and sex and ethnicity. Eligible participants were men and women (no age restriction) with acceptable records, approved for Hospital Episodes Statistics and Office of National Statistics linkage, and registered with their general practice for at least 12 months during the study period. We calculated age and sex standardised incidence and prevalence of 19 autoimmune disorders from 2000 to 2019 and used negative binomial regression models to investigate temporal trends and variation by age, sex, socioeconomic status, season of onset, and geographical region in England. To characterise co-occurrence of autoimmune diseases, we calculated incidence rate ratios (IRRs), comparing incidence rates of comorbid autoimmune disease among individuals with a first (index) autoimmune disease with incidence rates in the general population, using negative binomial regression models, adjusted for age and sex. FINDINGS: Among the 22 009 375 individuals included in the study, 978 872 had a new diagnosis of at least one autoimmune disease between Jan 1, 2000, and June 30, 2019 (mean age 54·0 years [SD 21·4]). 625 879 (63·9%) of these diagnosed individuals were female and 352 993 (36·1%) were male. Over the study period, age and sex standardised incidence rates of any autoimmune diseases increased (IRR 2017-19 vs 2000-02 1·04 [95% CI 1·00-1·09]). The largest increases were seen in coeliac disease (2·19 [2·05-2·35]), Sjogren's syndrome (2·09 [1·84-2·37]), and Graves' disease (2·07 [1·92-2·22]); pernicious anaemia (0·79 [0·72-0·86]) and Hashimoto's thyroiditis (0·81 [0·75-0·86]) significantly decreased in incidence. Together, the 19 autoimmune disorders examined affected 10·2% of the population over the study period (1 912 200 [13·1%] women and 668 264 [7·4%] men). A socioeconomic gradient was evident across several diseases, including pernicious anaemia (most vs least deprived area IRR 1·72 [1·64-1·81]), rheumatoid arthritis (1·52 [1·45-1·59]), Graves' disease (1·36 [1·30-1·43]), and systemic lupus erythematosus (1·35 [1·25-1·46]). Seasonal variations were observed for childhood-onset type 1 diabetes (more commonly diagnosed in winter) and vitiligo (more commonly diagnosed in summer), and regional variations were observed for a range of conditions. Autoimmune disorders were commonly associated with each other, particularly Sjögren's syndrome, systemic lupus erythematosus, and systemic sclerosis. Individuals with childhood-onset type 1 diabetes also had significantly higher rates of Addison's disease (IRR 26·5 [95% CI 17·3-40·7]), coeliac disease (28·4 [25·2-32·0]), and thyroid disease (Hashimoto's thyroiditis 13·3 [11·8-14·9] and Graves' disease 6·7 [5·1-8·5]), and multiple sclerosis had a particularly low rate of co-occurrence with other autoimmune diseases. INTERPRETATION: Autoimmune diseases affect approximately one in ten individuals, and their burden continues to increase over time at varying rates across individual diseases. The socioeconomic, seasonal, and regional disparities observed among several autoimmune disorders in our study suggest environmental factors in disease pathogenesis. The inter-relations between autoimmune diseases are commensurate with shared pathogenetic mechanisms or predisposing factors, particularly among connective tissue diseases and among endocrine diseases. FUNDING: Research Foundation Flanders.

Diabetes and the COVID-19 pandemic.

Almost immediately after the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus emerged, it was evident that people with chronic diseases, including diabetes, were disproportionately affected, with an increased risk of hospitalisation and mortality. Over the ensuing 2 years, the indirect effects of the pandemic on healthcare delivery in the short term have become prominent, along with the lingering effects of the virus in those directly infected. In the wake of the pandemic and without any evidence from high quality studies, a number of national and international consensus recommendations were published, which were subsequently rapidly updated based on observational studies. There have been unprecedented disruptions from both direct and indirect impacts of coronavirus disease-2019 (COVID-19) in people with diabetes. In this review, we summarise the impact of acute COVID-19 in people with diabetes, discuss how the presentation and epidemiology during the pandemic, including presentation of diabetic ketoacidosis and new-onset diabetes, has changed, and we consider the wider impact of the pandemic on patients and healthcare service delivery, including some of the areas of uncertainty. Finally, we make recommendations on prioritising patients as we move into the recovery phase and also how we protect people with diabetes for the future, as COVID-19 is likely to become endemic.

The relationship between islet autoantibody status and the genetic risk of type 1 diabetes in adult-onset type 1 diabetes.

AIMS/HYPOTHESIS: The reason for the observed lower rate of islet autoantibody positivity in clinician-diagnosed adult-onset vs childhood-onset type 1 diabetes is not known. We aimed to explore this by assessing the genetic risk of type 1 diabetes in autoantibody-negative and -positive children and adults. METHODS: We analysed GAD autoantibodies, insulinoma-2 antigen autoantibodies and zinc transporter-8 autoantibodies (ZnT8A) and measured type 1 diabetes genetic risk by genotyping 30 type 1 diabetes-associated variants at diagnosis in 1814 individuals with clinician-diagnosed type 1 diabetes (1112 adult-onset, 702 childhood-onset). We compared the overall type 1 diabetes genetic risk score (T1DGRS) and non-HLA and HLA (DR3-DQ2, DR4-DQ8 and DR15-DQ6) components with autoantibody status in those with adult-onset and childhood-onset diabetes. We also measured the T1DGRS in 1924 individuals with type 2 diabetes from the Wellcome Trust Case Control Consortium to represent non-autoimmune diabetes control participants. RESULTS: The T1DGRS was similar in autoantibody-negative and autoantibody-positive clinician-diagnosed childhood-onset type 1 diabetes (mean [SD] 0.274 [0.034] vs 0.277 [0.026], p=0.4). In contrast, the T1DGRS in autoantibody-negative adult-onset type 1 diabetes was lower than that in autoantibody-positive adult-onset type 1 diabetes (mean [SD] 0.243 [0.036] vs 0.271 [0.026], p<0.0001) but higher than that in type 2 diabetes (mean [SD] 0.229 [0.034], p<0.0001). Autoantibody-negative adults were more likely to have the more protective HLA DR15-DQ6 genotype (15% vs 3%, p<0.0001), were less likely to have the high-risk HLA DR3-DQ2/DR4-DQ8 genotype (6% vs 19%, p<0.0001) and had a lower non-HLA T1DGRS (p<0.0001) than autoantibody-positive adults. In contrast to children, autoantibody-negative adults were more likely to be male (75% vs 59%), had a higher BMI (27 vs 24 kg/m2) and were less likely to have other autoimmune conditions (2% vs 10%) than autoantibody-positive adults (all p<0.0001). In both adults and children, type 1 diabetes genetic risk was unaffected by the number of autoantibodies (p>0.3). These findings, along with the identification of seven misclassified adults with monogenic diabetes among autoantibody-negative adults and the results of a sensitivity analysis with and without measurement of ZnT8A, suggest that the intermediate type 1 diabetes genetic risk in autoantibody-negative adults is more likely to be explained by the inclusion of misclassified non-autoimmune diabetes (estimated to represent 67% of all antibody-negative adults, 95% CI 61%, 73%) than by the presence of unmeasured autoantibodies or by a discrete form of diabetes. When these estimated individuals with non-autoimmune diabetes were adjusted for, the prevalence of autoantibody positivity in adult-onset type 1 diabetes was similar to that in children (93% vs 91%, p=0.4). CONCLUSIONS/INTERPRETATION: The inclusion of non-autoimmune diabetes is the most likely explanation for the observed lower rate of autoantibody positivity in clinician-diagnosed adult-onset type 1 diabetes. Our data support the utility of islet autoantibody measurement in clinician-suspected adult-onset type 1 diabetes in routine clinical practice.

Characteristics and care of young people with type 2 diabetes included in the national diabetes audit datasets for England.

INTRODUCTION: We report contemporary age-related prevalence, characteristics and care of children and young people with type 2 diabetes in England. METHODS: Individuals with a recorded diagnosis of type 2 diabetes between January 2019 and March 2020 were identified from a whole population register. Age, sex, ethnicity, deprivation quintile, weight, HbA1c and receipt of the nine National Institute for Health & Care Excellence (NICE) recommended annual care processes were extracted from electronic clinical records and analysed by pre-specified age bands. RESULTS: In total, 122,780 (4.6%) of 2,642,435 individuals in England with type 2 diabetes were aged under 40 years, comprising; 650 (0.5%) under 16 years, 910 (0.7%) aged 16-18 years, 8245 (6.7%) aged 19-25 and 112,975 (92%) aged 26-39 years. Compared to people with type 2 diabetes aged above 40 years, young people were significantly more likely to be from minority ethnic groups: 51% under 16 years, 41% 16-18 years, 38% 19-25 years, 38% 26-39 years, 27% 40-59 years and 15% 60-79 years were of Black or Asian ethnicity. In addition, those aged under 40 years were more likely to be obese, women, to live in the most-deprived socioeconomic areas and less likely to receive the NICE recommended annual care processes or achieve target HbA1c . INTERPRETATION: The substantial number of people under 40 years of age with type 2 diabetes, are more likely to have characteristics associated with inequalities and are less likely to achieve HbA1c targets and receive recommended care processes. These findings highlight the need to consider novel approaches to service provision for this high-risk group.

Addressing health inequalities in diabetes through research: Recommendations from Diabetes UK's 2022 health inequalities in diabetes workshop.

AIMS: To develop a position statement which identifies research priorities to address health inequalities in diabetes and provides recommendations to researchers and research funders on how best to conduct research in these areas. METHODS: A two-day research workshop was conducted bringing together research experts in diabetes, research experts in health inequalities, healthcare professionals and people living with diabetes. RESULTS: The following key areas were identified as needing increased focus: How can we improve patient and public involvement and engagement to make diabetes research more inclusive of and relevant to diverse communities? How can we improve research design so that the people who could benefit most are represented? How can we use theories from implementation science to facilitate the uptake of research findings into routine practice to reach the populations with highest need? How can we collate and evaluate local innovation projects and disseminate best practice around tackling health inequalities in diabetes? How can we best collect and use data to address health inequalities in diabetes, including the harnessing of real-world and routinely collected data? How could research funders allocate funds to best address health inequalities in diabetes? How do we ensure the research community is representative of the general population? CONCLUSIONS: This position statement outlines recommendations to address the urgent need to tackle health inequalities in diabetes through research and calls on the diabetes research community to act upon these recommendations to ensure future research works to eliminate unfair and avoidable disparities in health.

Extending precision medicine tools to populations at high risk of type 2 diabetes.

In this Perspective, Shivani Misra and Jose C Florez discuss the application of precision medicine tools in under-represented populations.

Developing services to support the delivery of care to people with early-onset type 2 diabetes.

Early-onset type 2 diabetes occurring in childhood or early adulthood carries a significant excess burden of microvascular diabetes complications, cardiovascular disease and premature death, compared to later onset type 2 diabetes along with adverse pregnancy outcomes in women of child-bearing age. National audit data in England reveal that 122,780 individuals under the age of 40 years are currently living with type 2 diabetes, with an over-representation of people from minority ethnicities and those in the most socioeconomically deprived quintiles. A diagnosis of type 2 diabetes earlier in life poses some unique challenges to healthcare providers that are not routinely encountered when type 2 diabetes presents later. These include; (1) the need to ensure correct diabetes classification in an age group that carries a higher probability of other types of diabetes, (2) overcoming difficulties in engaging with individuals who are of working age or in full-time education, (3) appreciating and addressing the lower attainment of diabetes treatment targets and (4) proactively supporting women of child-bearing age to optimise their future pregnancy outcomes through better preparation for pregnancy, including achieving optimum glycaemic control at the time of conception. Meanwhile, approaches to prevent type 2 diabetes in younger age groups are challenged by difficulties in identifying those at highest risk, by poorer attendance at lifestyle interventions to prevent or delay the onset of type 2 diabetes and by attenuation of associated weight loss in those that do attend. In this article, we discuss the importance of recognising and addressing the distinct challenges in delivering healthcare to those with early-onset type 2 diabetes, the greater challenges in preventing type 2 diabetes at younger ages, and key components of strategies that might address these challenges to drive improvements in pregnancy outcomes, microvascular and cardiovascular outcomes.

DR15-DQ6 remains dominantly protective against type 1 diabetes throughout the first five decades of life.

AIMS/HYPOTHESIS: Among white European children developing type 1 diabetes, the otherwise common HLA haplotype DR15-DQ6 is rare, and highly protective. Adult-onset type 1 diabetes is now known to represent more overall cases than childhood onset, but it is not known whether DR15-DQ6 is protective in older-adult-onset type 1 diabetes. We sought to quantify DR15-DQ6 protection against type 1 diabetes as age of onset increased. METHODS: In two independent cohorts we assessed the proportion of type 1 diabetes cases presenting through the first 50 years of life with DR15-DQ6, compared with population controls. In the After Diabetes Diagnosis Research Support System-2 (ADDRESS-2) cohort (n = 1458) clinician-diagnosed type 1 diabetes was confirmed by positivity for one or more islet-specific autoantibodies. In UK Biobank (n = 2502), we estimated type 1 diabetes incidence rates relative to baseline HLA risk for each HLA group using Poisson regression. Analyses were restricted to white Europeans and were performed in three groups according to age at type 1 diabetes onset: 0-18 years, 19-30 years and 31-50 years. RESULTS: DR15-DQ6 was protective against type 1 diabetes through to age 50 years (OR < 1 for each age group, all p < 0.001). The following ORs for type 1 diabetes, relative to a neutral HLA genotype, were observed in ADDRESS-2: age 5-18 years OR 0.16 (95% CI 0.08, 0.31); age 19-30 years OR 0.10 (0.04, 0.23); and age 31-50 years OR 0.37 (0.21, 0.68). DR15-DQ6 also remained highly protective at all ages in UK Biobank. Without DR15-DQ6, the presence of major type 1 diabetes high-risk haplotype (either DR3-DQ2 or DR4-DQ8) was associated with increased risk of type 1 diabetes. CONCLUSIONS/INTERPRETATION: HLA DR15-DQ6 confers dominant protection from type 1 diabetes across the first five decades of life.

A Computationally Lightweight Algorithm for Deriving Reliable Metabolite Panel Measurements from 1D 1H NMR.

Small Molecule Enhancement SpectroscopY (SMolESY) was employed to develop a unique and fully automated computational solution for the assignment and integration of 1H nuclear magnetic resonance (NMR) signals from metabolites in challenging matrices containing macromolecules (herein blood products). Sensitive and reliable quantitation is provided by instant signal deconvolution and straightforward integration bolstered by spectral resolution enhancement and macromolecular signal suppression. The approach is highly efficient, requiring only standard one-dimensional 1H NMR spectra and avoiding the need for sample preprocessing, complex deconvolution, and spectral baseline fitting. The performance of the algorithm, developed using >4000 NMR serum and plasma spectra, was evaluated using an additional >8800 spectra, yielding an assignment accuracy greater than 99.5% for all 22 metabolites targeted. Further validation of its quantitation capabilities illustrated a reliable performance among challenging phenotypes. The simplicity and complete automation of the approach support the application of NMR-based metabolite panel measurements in clinical and population screening applications.

Hyperinsulinemic hypoglycemia in children and adolescents: Recent advances in understanding of pathophysiology and management.

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.

Development of the Point-of-Care Key Evidence Tool (POCKET): a checklist for multi-dimensional evidence generation in point-of-care tests.

Background This study aimed to develop the Point-of-Care Key Evidence Tool (POCKET); a multi-dimensional checklist to guide the evaluation of point-of-care tests (POCTs) incorporating validity, utility, usability, cost-effectiveness and patient experience. The motivation for this was to improve the efficiency of evidence generation in POCTs and reduce the lead-time for the adoption of novel POCTs. Methods A mixed qualitative and quantitative approach was applied. Following a literature search, a three round Delphi process was undertaken incorporating a semi-structured interview study and two questionnaire rounds. Participants included clinicians, laboratory personnel, commissioners, regulators (including members of National Institute for Health and Care Excellence [NICE] committees), patients, industry representatives and methodologists. Qualitative data were analysed based on grounded theory. The final tool was revised at an expert stakeholder workshop. Results Forty-three participants were interviewed within the semi-structured interview study, 32 participated in the questionnaire rounds and nine stakeholders attended the expert workshop. The final version of the POCKET checklist contains 65 different evidence requirements grouped into seven themes. Face validity, content validity and usability has been demonstrated. There exists a shortfall in the evidence that industry and research methodologists believe should be generated regarding POCTs and what is actually required by policy and decision makers to promote implementation into current healthcare pathways. Conclusions This study has led to the development of POCKET, a checklist for evidence generation and synthesis in POCTs. This aims to guide industry and researchers to the evidence that is required by decision makers to facilitate POCT adoption so that the benefits they can bring to patients can be effectively realised.

Genetics of Monogenic Diabetes: Present Clinical Challenges.

PURPOSE OF REVIEW: Monogenic forms of diabetes have specific treatments that differ from the standard care provided for type 1 and type 2 diabetes, making the appropriate diagnosis essential. In this review, we discuss current clinical challenges that remain, including improving case-finding strategies, particularly those that have transethnic applicability, and understanding the interpretation of genetic variants as pathogenic, with clinically meaningful impacts. RECENT FINDINGS: Biomarker approaches to the stratification for genetic testing now appear to be most effective in identifying cases of monogenic diabetes, and use of genetic risk scores may also prove useful. However, applicability in all ethnic groups is lacking. Challenges remain in the classification of genes as diabetes-causing and the interpretation of genetic variants at the clinical interface. Since the discovery that genetic defects can cause neonatal or young-onset diabetes, multiple causal genes have been identified and there have been many advances in strategies to detect genetic forms of diabetes and their treatments. Approaches learnt from monogenic diabetes are now being translated to polygenic diabetes.

Could accreditation bodies facilitate the implementation of medical guidelines in laboratories?

Several studies have shown that recommendations related to how laboratory testing should be performed and results interpreted are limited in medical guidelines and that the uptake and implementation of the recommendations that are available need improvement. The EFLM/UEMS Working Group on Guidelines conducted a survey amongst the national societies for clinical chemistry in Europe regarding development of laboratory-related guidelines. The results showed that most countries have guidelines that are specifically related to laboratory testing; however, not all countries have a formal procedure for accepting such guidelines and few countries have guideline committees. Based on this, the EFLM/UEMS Working Group on Guidelines conclude that there is still room for improvement regarding these processes in Europe and raise the question if the accreditation bodies could be a facilitator for an improvement.

Why are clinical practice guidelines not followed?

Clinical practice guidelines (CPG) are written with the aim of collating the most up to date information into a single document that will aid clinicians in providing the best practice for their patients. There is evidence to suggest that those clinicians who adhere to CPG deliver better outcomes for their patients. Why, therefore, are clinicians so poor at adhering to CPG? The main barriers include awareness, familiarity and agreement with the contents. Secondly, clinicians must feel that they have the skills and are therefore able to deliver on the CPG. Clinicians also need to be able to overcome the inertia of "normal practice" and understand the need for change. Thirdly, the goals of clinicians and patients are not always the same as each other (or the guidelines). Finally, there are a multitude of external barriers including equipment, space, educational materials, time, staff, and financial resource. In view of the considerable energy that has been placed on guidelines, there has been extensive research into their uptake. Laboratory medicine specialists are not immune from these barriers. Most CPG that include laboratory tests do not have sufficient detail for laboratories to provide any added value. However, where appropriate recommendations are made, then it appears that laboratory specialist express the same difficulties in compliance as front-line clinicians.

Optimized Protocol for Generating Functional Pancreatic Insulin-secreting Cells from Human Pluripotent Stem Cells.

Human pluripotent stem cells (hPSCs) can differentiate into any kind of cell, making them an excellent alternative source of human pancreatic ß-cells. hPSCs can either be embryonic stem cells (hESCs) derived from the blastocyst or induced pluripotent cells (hiPSCs) generated directly from somatic cells using a reprogramming process. Here a video-based protocol is presented to outline the optimal culture and passage conditions for hPSCs, prior to their differentiation and subsequent generation of insulin-producing pancreatic cells. This methodology follows the six-stage process for ß-cell directed differentiation, wherein hPSCs differentiate into definitive endoderm (DE), primitive gut tube, posterior foregut fate, pancreatic progenitors, pancreatic endocrine progenitors, and ultimately pancreatic ß-cells. It is noteworthy that this differentiation methodology takes a period of 27 days to generate human pancreatic ß-cells. The potential of insulin secretion was evaluated through two experiments, which included immunostaining and glucose-stimulated insulin secretion.

Newly detected diabetes during the COVID-19 pandemic: What have we learnt?

The SARS-CoV-2 pandemic has had an unprecedented effect on global health, mortality and healthcare provision. Diabetes has emerged as a key disease entity over the pandemic period, influencing outcomes from COVID-19 but also a tantalising hypothesis that the virus itself may be inducing diabetes. An uptick in diabetes cases over the pandemic has been noted for both type 1 diabetes (in children) and type 2 diabetes but understanding how this increase in incidence relates to the pandemic is challenging. It remains unclear whether indirect effects of the pandemic on behaviour, lifestyle and health have contributed to the increase; whether the virus itself has somehow mediated new-onset diabetes or whether other factors such as stress hyperglycaemic of steroid treatment during COVID-19 infection have played a roll. Within the myriad possibilities are some real challenges in interpreting epidemiological data, assigning diabetes type and understanding what in vitro data are telling us. In this review article we address the issue of newly-diagnosed diabetes during the pandemic, reviewing both epidemiological and basic science data and bringing together both strands of this emerging story.

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.