Can the introduction of a 12-lead ECG help reduce mortality in those presenting with foot ulceration to multidisciplinary diabetic foot clinics? An observational evaluation of a real-world implementation pilot in England.

AIMS/HYPOTHESIS: The risk of dying within 2 years of presentation with diabetic foot ulceration is over six times the risk of amputation, with CVD the major contributor. Using an observational evaluation of a real-world implementation pilot, we aimed to assess whether for those presenting with diabetic foot ulceration in England, introducing a 12-lead ECG into routine care followed by appropriate clinical action was associated with reduced mortality. METHODS: Between July 2014 and December 2017, ten multidisciplinary diabetic foot services in England participated in a pilot project introducing 12-lead ECGs for new attendees with foot ulceration. Inception coincided with launch of the National Diabetes Footcare Audit (NDFA), whereby all diabetic footcare services in England were invited to enter data on new attendees with foot ulceration. Poisson regression models assessed the mortality RR at 2 and 5 years following first assessment of those receiving care in a participating pilot unit vs those receiving care in any other unit in England, adjusting for age, sex, ethnicity, deprivation, type and duration of diabetes, ulcer severity, and morbidity in the year prior to first assessment. RESULTS: Of the 3110 people recorded in the NDFA at a participating unit during the pilot, 33% (1015) were recorded as having received an ECG. A further 25,195 people recorded in the NDFA had attended another English footcare service. Unadjusted mortality in the pilot units was 16.3% (165) at 2 years and 37.4% (380) at 5 years for those who received an ECG, and 20.5% (430) and 45.2% (950), respectively, for those who did not receive an ECG. For people included in the NDFA at other units, unadjusted mortality was 20.1% (5075) and 42.6% (10,745), respectively. In the fully adjusted model, mortality was not significantly lower for those attending participating units at 2 (RR 0.93 [95% CI 0.85, 1.01]) or 5 years (RR 0.95 [95% CI 0.90, 1.01]). At participating units, mortality in those who received an ECG vs those who did not was lower at 5 years (RR 0.86 [95% CI 0.76, 0.97]), but not at 2 years (RR 0.87 [95% CI 0.72, 1.04]). Comparing just those that received an ECG with attendees at all other centres in England, mortality was lower at 5 years (RR 0.87 [95% CI 0.78, 0.96]), but not at 2 years (RR 0.86 [95% CI 0.74, 1.01]). CONCLUSIONS/INTERPRETATION: The evaluation confirms the high mortality seen in those presenting with diabetic foot ulceration. Overall mortality at the participating units was not significantly reduced at 2 or 5 years, with confidence intervals just crossing parity. Implementation of the 12-lead ECG into the routine care pathway proved challenging for clinical teams-overall a third of attendees had one, although some units delivered the intervention to over 60% of attendees-and the evaluation was therefore underpowered. Nonetheless, the signals of potential mortality benefit among those who had an ECG suggest that units in a position to operationalise implementation may wish to consider this. DATA AVAILABILITY: Data from the National Diabetes Audit can be requested through the National Health Service Digital Data Access Request Service process at: https://digital.nhs.uk/services/data-access-request-service-dars/dars-products-and-services/data-set-catalogue/national-diabetes-audit-nda.

Trends in weight gain recorded in English primary care before and during the Coronavirus-19 pandemic: An observational cohort study using the OpenSAFELY platform.

BACKGROUND: Obesity and rapid weight gain are established risk factors for noncommunicable diseases and have emerged as independent risk factors for severe disease following Coronavirus Disease 2019 (COVID-19) infection. Restrictions imposed to reduce COVID-19 transmission resulted in profound societal changes that impacted many health behaviours, including physical activity and nutrition, associated with rate of weight gain. We investigated which clinical and sociodemographic characteristics were associated with rapid weight gain and the greatest acceleration in rate of weight gain during the pandemic among adults registered with an English National Health Service (NHS) general practitioner (GP) during the COVID-19 pandemic. METHODS AND FINDINGS: With the approval of NHS England, we used the OpenSAFELY platform inside TPP to conduct an observational cohort study of routinely collected electronic healthcare records. We investigated changes in body mass index (BMI) values recorded in English primary care between March 2015 and March 2022. We extracted data on 17,742,365 adults aged 18 to 90 years old (50.1% female, 76.1% white British) registered with an English primary care practice. We estimated individual rates of weight gain before (δ-prepandemic) and during (δ-pandemic) the pandemic and identified individuals with rapid weight gain (>0.5 kg/m2/year) in each period. We also estimated the change in rate of weight gain between the prepandemic and pandemic period (δ-change = δ-pandemic-δ-prepandemic) and defined extreme accelerators as the 10% of individuals with the greatest increase in their rate of weight gain (δ-change ≥1.84 kg/m2/year) between these periods. We estimated associations with these outcomes using multivariable logistic regression adjusted for age, sex, index of multiple deprivation (IMD), and ethnicity. P-values were generated in regression models. The median BMI of our study population was 27.8 kg/m2, interquartile range (IQR) [24.3, 32.1] in 2019 (March 2019 to February 2020) and 28.0 kg/m2, IQR [24.4, 32.6] in 2021. Rapid pandemic weight gain was associated with sex, age, and IMD. Male sex (male versus female: adjusted odds ratio (aOR) 0.76, 95% confidence interval (95% CI) [0.76, 0.76], p < 0.001), older age (e.g., 50 to 59 years versus 18 to 29 years: aOR 0.60, 95% CI [0.60, 0.61], p < 0.001]); and living in less deprived areas (least-deprived-IMD-quintile versus most-deprived: aOR 0.77, 95% CI [0.77, 0.78] p < 0.001) reduced the odds of rapid weight gain. Compared to white British individuals, all other ethnicities had lower odds of rapid pandemic weight gain (e.g., Indian versus white British: aOR 0.69, 95% CI [0.68, 0.70], p < 0.001). Long-term conditions (LTCs) increased the odds, with mental health conditions having the greatest effect (e.g., depression (aOR 1.18, 95% CI [1.17, 1.18], p < 0.001)). Similar characteristics increased odds of extreme acceleration in the rate of weight gain between the prepandemic and pandemic periods. However, changes in healthcare activity during the pandemic may have introduced new bias to the data. CONCLUSIONS: We found female sex, younger age, deprivation, white British ethnicity, and mental health conditions were associated with rapid pandemic weight gain and extreme acceleration in rate of weight gain between the prepandemic and pandemic periods. Our findings highlight the need to incorporate sociodemographic, physical, and mental health characteristics when formulating research, policies, and interventions targeting BMI in the period of post pandemic service restoration and in future pandemic planning.

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.

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.

Care processes in people in remission from type 2 diabetes: A cohort study using the National Diabetes Audit.

AIMS: People with type 2 diabetes can enter remission but may relapse or develop legacy complications. This analysis assesses whether people with remission from type 2 diabetes continue receiving annual care processes recommended in national guidelines and the potential impacts of formal recognition of remission. METHODS: People with type 2 diabetes with and without formal recognition (diagnostic code) of remission, and with and without evidence of remission (HbA1c < 48 mmol/mol without prescription for glucose-lowering drugs in preceding 26 weeks), included in the 2018/19 National Diabetes Audit (NDA) for England and Wales were followed up to identify care processes received between 1 January 2019 and 31 March 2020. RESULTS: Of the 2,822,145 people with type 2 diabetes in the cohort, 16,460 (0.58%) were coded with remission in the 2018/19 NDA. After adjustment for age, sex, socioeconomic deprivation and ethnicity, people coded with remission were less likely to receive each care process than those without such coding irrespective of HbA1c measurements (relative risk (RR) of receiving all 8 care processes 0.70 (95% CI 0.69-0.72)). For the 339,235 people with evidence of remission, irrespective of diagnostic coding compared to those without such evidence, the RR for receiving all 8 care processes was 0.94 (95% CI 0.93-0.94). CONCLUSIONS: People coded with remission of type 2 diabetes were less likely to receive diabetes care processes than those without such coding. People with evidence of remission had only a slightly reduced likelihood of receiving care processes. Formal recognition of remission may affect the provision or uptake of care processes.

Effectiveness of digital and remote provision of the Healthier You: NHS Diabetes Prevention Programme during the COVID-19 pandemic.

AIMS: To assess weight change in the Healthier You: NHS Diabetes Prevention Programme (NHS DPP) delivered via video conferencing (remote) sessions or delivered via specific digital interventions through apps or websites, during the COVID-19 pandemic compared to group-based face-to-face interventions, pre-pandemic. METHODS: Prospectively collected national service-level data relating to individuals with non-diabetic hyperglycaemia (HbA1c 42-47 mmol/mol (6.0%-6.4%) or fasting plasma glucose 5.5-6.9 mmol/L) referred to the NHS DPP from June 2016 to March 2022. RESULTS: Between March 2020 and March 2022, 335,961 people were referred to the programme and were offered a choice of remote or digital intervention. This was preceded by 556,793 people referred to the face-to-face programme between June 2016 and February 2022. Uptakes to intervention sessions were 47% for those offered a choice and 39% for face-to-face. Remote and digital participants were significantly younger (60 and 56 vs. 65 years) and heavier (86.1 kg and 91.0 kg vs. 84.1 kg) compared to face-to-face. Weight change was assessed for 42,407 remote, 7699 digital and 97,205 face-to-face participants with sufficient time to have finished the programme and no missing data. Mean weight losses for participants attending at least one intervention session were: 2.40 (2.36-2.44) kg, 2.59 (2.49-2.68) kg and 2.01 (1.98-2.04) kg for remote, digital and face-to-face participants respectively. Corresponding mean weight losses for those who completed the programme were: 3.24 (3.19-3.30) kg, 4.76 (4.60-4.92) kg and 3.04 (3.00-3.07) kg. There were no significant differences in weight change between interventions by ethnicity and deprivation. CONCLUSIONS: Weight losses achieved through remote and digital interventions were greater than those previously achieved through face-to-face interventions, without evidence of exacerbation of health inequalities.

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.

Twenty-year trajectories of cardio-metabolic factors among people with type 2 diabetes by dementia status in England: a retrospective cohort study.

To assess 20-year retrospective trajectories of cardio-metabolic factors preceding dementia diagnosis among people with type 2 diabetes (T2D). We identified 227,145 people with T2D aged > 42 years between 1999 and 2018. Annual mean levels of eight routinely measured cardio-metabolic factors were extracted from the Clinical Practice Research Datalink. Multivariable multilevel piecewise and non-piecewise growth curve models assessed retrospective trajectories of cardio-metabolic factors by dementia status from up to 19 years preceding dementia diagnosis (dementia) or last contact with healthcare (no dementia). 23,546 patients developed dementia; mean (SD) follow-up was 10.0 (5.8) years. In the dementia group, mean systolic blood pressure increased 16-19 years before dementia diagnosis compared with patients without dementia, but declined more steeply from 16 years before diagnosis, while diastolic blood pressure generally declined at similar rates. Mean body mass index followed a steeper non-linear decline from 11 years before diagnosis in the dementia group. Mean blood lipid levels (total cholesterol, LDL, HDL) and glycaemic measures (fasting plasma glucose and HbA1c) were generally higher in the dementia group compared with those without dementia and followed similar patterns of change. However, absolute group differences were small. Differences in levels of cardio-metabolic factors were observed up to two decades prior to dementia diagnosis. Our findings suggest that a long follow-up is crucial to minimise reverse causation arising from changes in cardio-metabolic factors during preclinical dementia. Future investigations which address associations between cardiometabolic factors and dementia should account for potential non-linear relationships and consider the timeframe when measurements are taken.

The effectiveness of digital delivery versus group-based face-to-face delivery of the English National Health Service Type 2 Diabetes Prevention Programme: a non-inferiority retrospective cohort comparison study.

BACKGROUND: Face-to-face group-based diabetes prevention programmes have been shown to be effective in many settings. Digital delivery may suit some patients, but research comparing the effectiveness of digital with face-to-face delivery is scarce. The aim was to assess if digital delivery of the English National Health Service Diabetes Prevention Programme (NHS DPP) is non-inferior to group-based face-to-face delivery in terms of weight change, and evaluate factors associated with differential change. METHODS: The study included those recruited to the NHS DPP in 2017-2018. Individual-level data from a face-to-face cohort was compared to two cohorts on a digital pilot who (i) were offered no choice of delivery mode, or (ii) chose digital over face-to-face. Changes in weight at 6 and 12 months were analysed using mixed effects linear regression, having matched participants from the digital pilot to similar participants from face-to-face. RESULTS: Weight change on the digital pilot was non-inferior to face-to-face at both time points: it was similar in the comparison of those with no choice (difference in weight change: -0.284 kg [95% CI: -0.712, 0.144] at 6 months) and greater in digital when participants were offered a choice (-1.165 kg [95% CI: -1.841, -0.489]). Interactions between delivery mode and sex, ethnicity, age and deprivation were observed. CONCLUSIONS: Digital delivery of the NHS DPP achieved weight loss at least as good as face-to-face. Patients who were offered a choice and opted for digital experienced better weight loss, compared to patients offered face-to-face only.

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.

Cohort profile: National Diabetes Audit for England and Wales.

The National Diabetes Audit (NDA) collates and analyses data on the quality and variation in clinical care and outcomes for people with diabetes. It also provides opportunities to assess trends, determinants, and outcomes of diabetes to help guide clinical and public health priorities. COHORT: Between 1 January 2003 and 31 March 2020, a total of 5,280,885 people diagnosed with diabetes were included in at least one NDA data collection. To this date, median follow-up was 12 and 8 years for people with type 1 diabetes and type 2 diabetes respectively. Comparisons with the 2019/20 Quality and Outcomes Framework show it included 98% of adults in England and Wales with diagnosed type 1 and type 2 diabetes. Data include demographic characteristics (age, sex, ethnicity, age at diagnosis, deprivation), risk factors (HbA1c , blood pressure, cholesterol, body mass index, smoking status) diabetic and cardiovascular complications and deaths. SECONDARY ANALYSIS: Secondary analyses have included comparisons of HbA1c and blood pressure measurements in cohorts with similar characteristics to the Epidemiology of Diabetes Interventions and Complications study and the UK Prospective Diabetes Study; COVID-19 related mortality in people with type 1 and type 2 diabetes and incidence of type 2 diabetes following admission to intensive care units. FUTURE PLANS: Commissioned NDA reports will continue to inform service development in England and Wales. The same data, with or without linkages to other external datasets, are also a rich resource for clinically orientated research.

Completion of annual diabetes care processes and mortality: A cohort study using the National Diabetes Audit for England and Wales.

AIM: To conduct an analysis to assess whether the completion of recommended diabetes care processes (glycated haemoglobin [HbA1c], creatinine, cholesterol, blood pressure, body mass index [BMI], smoking habit, urinary albumin, retinal and foot examinations) at least annually is associated with mortality. MATERIALS AND METHODS: A cohort from the National Diabetes Audit of England and Wales comprising 179 105 people with type 1 and 1 397 790 people with type 2 diabetes, aged 17 to 99 years on January 1, 2009, diagnosed before January 1, 2009 and alive on April 1, 2013 was followed to December 31, 2019. Cox proportional hazards models adjusting for demographic characteristics, smoking, HbA1c, blood pressure, serum cholesterol, BMI, duration of diagnosis, estimated glomerular filtration rate, prior myocardial infarction, stroke, heart failure, respiratory disease and cancer, were used to investigate whether care processes recorded January 1, 2009 to March 31, 2010 were associated with subsequent mortality. RESULTS: Over a mean follow-up of 7.5 and 7.0 years there were 26 915 and 388 093 deaths in people with type 1 and type 2 diabetes, respectively. Completion of five or fewer, compared to eight, care processes (retinal screening not included as data were not reliable) had a mortality hazard ratio (HR) of 1.37 (95% confidence interval [CI] 1.28-1.46) in people with type 1 and 1.32 (95% CI 1.30-1.35) in people with type 2 diabetes. The HR was higher for respiratory disease deaths and lower in South Asian ethnic groups. CONCLUSIONS: People with diabetes who have fewer routine care processes have higher mortality. Further research is required into whether different approaches to care might improve outcomes for this high-risk group.

National public health system responses to diabetes and other important noncommunicable diseases : Background, goals, and results of an international workshop at the Robert Koch Institute.

Diabetes mellitus and other noncommunicable diseases (NCDs) represent an emerging global public health challenge. In Germany, about 6.7 million adults are affected by diabetes according to national health surveys, including 1.3 million with undiagnosed diabetes. Complications of diabetes result in an increasing burden for individuals and society as well as enormous costs for the health care system. In response, the Federal Ministry of Health commissioned the Robert Koch Institute (RKI) to implement a diabetes surveillance system and the Federal Center for Health Education (BZgA) to develop a diabetes prevention strategy. In a two-day workshop jointly organized by the RKI and the BZgA, representatives from public health institutes in seven countries shared their expertise and knowledge on diabetes prevention and surveillance. Day one focused on NCD surveillance systems and emphasized both the strengthening of sustainable data sources and the timely and targeted dissemination of results using innovative formats. The second day focused on diabetes prevention strategies and highlighted the importance of involving all relevant stakeholders in the development process to facilitate its acceptance and implementation. Furthermore, the effective translation of prevention measures into real-world settings requires data from surveillance systems to identify high-risk groups and evaluate the effect of measures at the population level based on analyses of time trends in risk factors and disease outcomes. Overall, the workshop highlighted the close link between diabetes prevention strategies and surveillance systems. It was generally stated that only robust data enables effective prevention measures to encounter the increasing burden from diabetes and other NCDs.

Effectiveness of the influenza vaccine in preventing admission to hospital and death in people with type 2 diabetes.

BACKGROUND: The health burden caused by seasonal influenza is substantial. We sought to examine the effectiveness of influenza vaccination against admission to hospital for acute cardiovascular and respiratory conditions and all-cause death in people with type 2 diabetes. METHODS: We conducted a retrospective cohort study using primary and secondary care data from the Clinical Practice Research Datalink in England, over a 7-year period between 2003/04 and 2009/10. We enrolled 124 503 adults with type 2 diabetes. Outcome measures included admission to hospital for acute myocardial infarction (MI), stroke, heart failure or pneumonia/influenza, and death. We fitted Poisson regression models for influenza and off-season periods to estimate incidence rate ratios (IRR) for cohorts who had and had not received the vaccine. We used estimates for the summer, when influenza activity is low, to adjust for residual confounding. RESULTS: Study participants contributed to 623 591 person-years of observation during the 7-year study period. Vaccine recipients were older and had more comorbid conditions compared with nonrecipients. After we adjusted for covariates and residual confounding, vaccination was associated with significantly lower admission rates for stroke (IRR 0.70, 95% confidence interval [CI] 0.53-0.91), heart failure (IRR 0.78, 95% CI 0.65-0.92) and pneumonia or influenza (IRR 0.85, 95% CI 0.74-0.99), as well as all-cause death (IRR 0.76, 95% CI 0.65-0.83), and a nonsignificant change for acute MI (IRR 0.81, 95% CI 0.62-1.04) during the influenza seasons. INTERPRETATION: In this cohort of patients with type 2 diabetes, influenza vaccination was associated with reductions in rates of admission to hospital for specific cardiovascular events. Efforts should be focused on improvements in vaccine uptake in this important target group as part of comprehensive secondary prevention.

Incentives in Diabetic Eye Assessment by Screening (IDEAS): study protocol of a three-arm randomized controlled trial using financial incentives to increase screening uptake in London.

BACKGROUND: Diabetes is an increasing public health problem in the UK and globally. Diabetic retinopathy is a microvascular complication of diabetes, and is one of the leading causes of blindness in the UK working age population. The diabetic eye screening programme in England aims to invite all people with diabetes aged 12 or over for retinal photography to screen for the presence of diabetic retinopathy. However, attendance rates are only 81 %, leaving many people at risk of preventable sight loss. METHODS: This is a three arm randomized controlled trial to investigate the impact of different types of financial incentives (based on principles from behavioral economics) on increasing attendance at diabetic eye screening appointments in London. Eligible participants will be aged 16 or over, and are those who have been invited to screening appointments annually, but who have not attended, or telephoned to rearrange an appointment, within the last 24 months. Eligible participants will be randomized to one of three conditions: 1. Control condition (usual invitation letter) 2. Fixed incentive condition (usual invitation letter, including a voucher for £10 if they attend their appointment) 3. Probabilistic incentive condition (invitation letter, including a voucher for a 1 in 100 chance of winning £1000 if they attend their appointment). Participants will be sent invitation letters, and the primary outcome will be whether or not they attend their appointment. One thousand participants will be included in total, randomized with a ratio of 1.4:1:1. In order to test whether the incentive scheme has a differential impact on patients from different demographic or socio-economic groups, information will be recorded on age, gender, distance from screening center, socio-economic status and length of time since they were last screened. A cost-effectiveness analysis will also be performed. DISCUSSION: This study will be the first trial of financial incentives for improving uptake of diabetic eye screening. If effective, the intervention may suggest a cost-effective way to increase screening rates, thus reducing unnecessary blindness. TRIAL REGISTRATION: ISRCTN14896403, 25 February 2016.

Prediabetes, participation in the English National Health Service Diabetes Prevention Programme, and associations with COVID-19-related mortality: A whole population study.

AIMS: To assess the effects of non-diabetic hyperglycaemia (NDH, also known as pre-diabetes), including the impact of the NHS Diabetes Prevention Programme (NHS DPP), on COVID-19-related mortality during the pandemic. METHODS: This study included all 61,438,225 individuals registered with General Practices in England and alive on 1st March 2020. We assessed COVID-19-related mortality in the 2,290,280(3.7 %) individuals with diagnosed NDH between March 2020 and February 2022 compared to those without diagnosed NDH or diabetes using Cox regression to adjust for demographic factors and cardiovascular comorbidities. Individuals with diagnosed NDH were further sub-categorised based on their contact with the NHS DPP (N = 376,590). Analyses were stratified by age (years) (<50, 50-69 and ≥ 70). RESULTS: There were 158,070 COVID-19 deaths; 17,280(11 %) for people with diagnosed NDH. The adjusted hazard ratio (HR) was 0.95(0.93-0.96),p < 0.001 for those with diagnosed NDH compared to those without diagnosed diabetes or NDH. By age (years), HRs were, 2.53(2.23-2.88),p < 0.001 for < 50, 1.29(1.24-1.35),p < 0.001 for 50-69 and 0.87(0.85-0.89),p < 0.001 for ≥ 70. NHS DPP attendance was associated with lower COVID-19 mortality with a dose-response relationship with engagement. CONCLUSIONS: Younger people with diagnosed NDH were at higher relative risk of COVID-19 mortality. Attendance at the NHS DPP was associated with significantly lower COVID-19-related mortality.

Identifying subtypes of type 2 diabetes mellitus with machine learning: development, internal validation, prognostic validation and medication burden in linked electronic health records in 420 448 individuals.

INTRODUCTION: None of the studies of type 2 diabetes (T2D) subtyping to date have used linked population-level data for incident and prevalent T2D, incorporating a diverse set of variables, explainable methods for cluster characterization, or adhered to an established framework. We aimed to develop and validate machine learning (ML)-informed subtypes for type 2 diabetes mellitus (T2D) using nationally representative data. RESEARCH DESIGN AND METHODS: In population-based electronic health records (2006-2020; Clinical Practice Research Datalink) in individuals ≥18 years with incident T2D (n=420 448), we included factors (n=3787), including demography, history, examination, biomarkers and medications. Using a published framework, we identified subtypes through nine unsupervised ML methods (K-means, K-means++, K-mode, K-prototype, mini-batch, agglomerative hierarchical clustering, Birch, Gaussian mixture models, and consensus clustering). We characterized clusters using intracluster distributions and explainable artificial intelligence (AI) techniques. We evaluated subtypes for (1) internal validity (within dataset; across methods); (2) prognostic validity (prediction for 5-year all-cause mortality, hospitalization and new chronic diseases); and (3) medication burden. RESULTS: Development: We identified four T2D subtypes: metabolic, early onset, late onset and cardiometabolic. Internal validity: Subtypes were predicted with high accuracy (F1 score >0.98). Prognostic validity: 5-year all-cause mortality, hospitalization, new chronic disease incidence and medication burden differed across T2D subtypes. Compared with the metabolic subtype, 5-year risks of mortality and hospitalization in incident T2D were highest in late-onset subtype (HR 1.95, 1.85-2.05 and 1.66, 1.58-1.75) and lowest in early-onset subtype (1.18, 1.11-1.27 and 0.85, 0.80-0.90). Incidence of chronic diseases was highest in late-onset subtype and lowest in early-onset subtype. Medications: Compared with the metabolic subtype, after adjusting for age, sex, and pre-T2D medications, late-onset subtype (1.31, 1.28-1.35) and early-onset subtype (0.83, 0.81-0.85) were most and least likely, respectively, to be prescribed medications within 5 years following T2D onset. CONCLUSIONS: In the largest study using ML to date in incident T2D, we identified four distinct subtypes, with potential future implications for etiology, therapeutics, and risk prediction.

Early outcomes of referrals to the English National Health Service Digital Weight Management Programme.

OBJECTIVE: The study objective was to assess participant weight change for the English National Health Service (NHS) Digital Weight Management Programme, the first such digital intervention to achieve population coverage. METHODS: A service evaluation was used to assess intervention effectiveness for adults with obesity and a diagnosis of hypertension and/or diabetes, between April 2021 and March 2022, using prospectively collected, national service-level data in England. RESULTS: Of the 63,937 referrals made from general practices, within the time period, 31,861 (50%) chose to take up the 12-week Programme. There were 31,718 participants who had time to finish the Programme; of those, 14,268 completed the Programme (defined as attending ≥60%), a 45% completion rate. The mean weight change for those who had time to finish the Programme was -2.2 kg (95% CI: -2.25 to -2.16), for those who completed it was -3.9 kg (95% CI: -3.99 to -3.84), and for those who had time to finish the Programme but did not complete it was -0.74 kg (95% CI: -0.79 to -0.70). CONCLUSIONS: The NHS Digital Weight Management Programme is effective at achieving clinically meaningful weight loss. The outcomes compare favorably to web-based weight management interventions tested in randomized trials and those delivered as face-to-face interventions, and results suggest that the approach may, with increased participation, bring population-level benefits.