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.

Coverage, completion and outcomes of COVID-19 risk assessments in a multi-ethnic nationwide cohort of UK healthcare workers: a cross-sectional analysis from the UK-REACH Study.

INTRODUCTION: There are limited data on the outcomes of COVID-19 risk assessment in healthcare workers (HCWs) or the association of ethnicity, other sociodemographic and occupational factors with risk assessment outcomes. METHODS: We used questionnaire data from UK-REACH (UK Research study into Ethnicity And COVID-19 outcomes in Healthcare workers), an ethnically diverse, nationwide cohort of UK HCWs. We derived four binary outcomes: (1) offered a risk assessment; (2) completed a risk assessment; (3) working practices changed as a result of the risk assessment; (4) wanted changes to working practices after risk assessment but working practices did not change.We examined the association of ethnicity, other sociodemographic/occupational factors and actual/perceived COVID-19 risk variables on our outcomes using multivariable logistic regression. RESULTS: 8649 HCWs were included in total. HCWs from ethnic minority groups were more likely to report being offered a risk assessment than white HCWs, and those from Asian and black ethnic groups were more likely to report having completed an assessment if offered. Ethnic minority HCWs had lower odds of reporting having their work change as a result of risk assessment. Those from Asian and black ethnic groups were more likely to report no changes to their working practices despite wanting them.Previous SARS-CoV-2 infection was associated with lower odds of being offered a risk assessment and having adjustments made to working practices. DISCUSSION: We found differences in risk assessment outcomes by ethnicity, other sociodemographic/occupational factors and actual/perceived COVID-19 risk factors. These findings are concerning and warrant further research using actual (rather than reported) risk assessment outcomes in an unselected cohort.

An external validation of the QCOVID3 risk prediction algorithm for risk of hospitalisation and death from COVID-19: An observational, prospective cohort study of 1.66m vaccinated adults in Wales, UK.

INTRODUCTION: At the start of the COVID-19 pandemic there was an urgent need to identify individuals at highest risk of severe outcomes, such as hospitalisation and death following infection. The QCOVID risk prediction algorithms emerged as key tools in facilitating this which were further developed during the second wave of the COVID-19 pandemic to identify groups of people at highest risk of severe COVID-19 related outcomes following one or two doses of vaccine. OBJECTIVES: To externally validate the QCOVID3 algorithm based on primary and secondary care records for Wales, UK. METHODS: We conducted an observational, prospective cohort based on electronic health care records for 1.66m vaccinated adults living in Wales on 8th December 2020, with follow-up until 15th June 2021. Follow-up started from day 14 post vaccination to allow the full effect of the vaccine. RESULTS: The scores produced by the QCOVID3 risk algorithm showed high levels of discrimination for both COVID-19 related deaths and hospital admissions and good calibration (Harrell C statistic: ≥ 0.828). CONCLUSION: This validation of the updated QCOVID3 risk algorithms in the adult vaccinated Welsh population has shown that the algorithms are valid for use in the Welsh population, and applicable on a population independent of the original study, which has not been previously reported. This study provides further evidence that the QCOVID algorithms can help inform public health risk management on the ongoing surveillance and intervention to manage COVID-19 related risks.

Study protocol for the use of time series forecasting and risk analyses to investigate the effect of the COVID-19 pandemic on hospital admissions associated with new-onset disability and frailty in a national, linked electronic health data setting.

INTRODUCTION: Older people were at particular risk of morbidity and mortality during COVID-19. Consequently, they experienced formal (externally imposed) and informal (self-imposed) periods of social isolation and quarantine. This is hypothesised to have led to physical deconditioning, new-onset disability and frailty. Disability and frailty are not routinely collated at population level but are associated with increased risk of falls and fractures, which result in hospital admissions. First, we will examine incidence of falls and fractures during COVID-19 (January 2020-March 2022), focusing on differences between incidence over time against expected rates based on historical data, to determine whether there is evidence of new-onset disability and frailty. Second, we will examine whether those with reported SARS-CoV-2 were at higher risk of falls and fractures. METHODS AND ANALYSIS: This study uses the Office for National Statistics (ONS) Public Health Data Asset, a linked population-level dataset combining administrative health records with sociodemographic data of the 2011 Census and National Immunisation Management System COVID-19 vaccination data for England. Administrative hospital records will be extracted based on specific fracture-centric International Classification of Diseases-10 codes in years preceding COVID-19 (2011-2020). Historical episode frequency will be used to predict expected admissions during pandemic years using time series modelling, if COVID-19 had not occurred. Those predicted admission figures will be compared with actual admissions to assess changes in hospital admissions due to public health measures comprising the pandemic response. Hospital admissions in prepandemic years will be stratified by age and geographical characteristics and averaged, then compared with pandemic year admissions to assess more granular changes. Risk modelling will assess risk of experiencing a fall, fracture or frail fall and fracture, if they have reported a positive case of COVID-19. The combination of these techniques will provide insight into changes in hospital admissions from the COVID-19 pandemic. ETHICS AND DISSEMINATION: This study has approval from the National Statistician's Data Ethics Advisory Committee (NSDEC(20)12). Results will be made available to other researchers via academic publication and shared via the ONS website.

Promoting inclusion in clinical trials-a rapid review of the literature and recommendations for action.

BACKGROUND: Without inclusion of diverse research participants, it is challenging to understand how study findings will translate into the real world. Despite this, a lack of inclusion of those from under-served groups in research is a prevailing problem due to multi-faceted barriers acting at multiple levels. Therefore, we rapidly reviewed international published literature, in relation to clinical trials, on barriers relating to inclusion, and evidence of approaches that are effective in overcoming these. METHODS: A rapid literature review was conducted searching PubMed for peer-reviewed articles that discussed barriers to inclusion or strategies to improve inclusion in clinical trial research published between 2010 and 2021. Grey literature articles were excluded. RESULTS: Seventy-two eligible articles were included. The main barriers identified were language and communication, lack of trust, access to trials, eligibility criteria, attitudes and beliefs, lack of knowledge around clinical trials, and logistical and practical issues. In relation to evidence-based strategies and enablers, two key themes arose: [1] a multi-faceted approach is essential [2]; no single strategy was universally effective either within or between trials. The key evidence-based strategies identified were cultural competency training, community partnerships, personalised approach, multilingual materials and staff, communication-specific strategies, increasing understanding and trust, and tackling logistical barriers. CONCLUSIONS: Many of the barriers relating to inclusion are the same as those that impact trial design and healthcare delivery generally. However, the presentation of these barriers among different under-served groups may be unique to each population's particular circumstances, background, and needs. Based on the literature, we make 15 recommendations that, if implemented, may help improve inclusion within clinical trials and clinical research more generally. The three main recommendations include improving cultural competency and sensitivity of all clinical trial staff through training and ongoing personal development, the need to establish a diverse community advisory panel for ongoing input into the research process, and increasing recruitment of staff from under-served groups. Implementation of these recommendations may help improve representation of under-served groups in clinical trials which would improve the external validity of associated findings.

Socioeconomic inequalities of Long COVID: a retrospective population-based cohort study in the United Kingdom.

OBJECTIVES: To estimate the risk of Long COVID by socioeconomic deprivation and to further examine the inequality by sex and occupation. DESIGN: We conducted a retrospective population-based cohort study using data from the ONS COVID-19 Infection Survey between 26 April 2020 and 31 January 2022. This is the largest nationally representative survey of COVID-19 in the UK with longitudinal data on occupation, COVID-19 exposure and Long COVID. SETTING: Community-based survey in the UK. PARTICIPANTS: A total of 201,799 participants aged 16 to 64 years and with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. MAIN OUTCOME MEASURES: The risk of Long COVID at least 4 weeks after SARS-CoV-2 infection by index of multiple deprivation (IMD) and the modifying effects of socioeconomic deprivation by sex and occupation. RESULTS: Nearly 10% (n = 19,315) of participants reported having Long COVID. Multivariable logistic regression models, adjusted for a range of variables (demographic, co-morbidity and time), showed that participants in the most deprived decile had a higher risk of Long COVID (11.4% vs. 8.2%; adjusted odds ratio (aOR): 1.46; 95% confidence interval (CI): 1.34, 1.59) compared to the least deprived decile. Significantly higher inequalities (most vs. least deprived decile) in Long COVID existed in healthcare and patient-facing roles (aOR: 1.76; 95% CI: 1.27, 2.44), in the education sector (aOR: 1.68; 95% CI: 1.31, 2.16) and in women (aOR: 1.56; 95% CI: 1.40, 1.73) than men (aOR: 1.32; 95% CI: 1.15, 1.51). CONCLUSIONS: This study provides insights into the heterogeneous degree of inequality in Long COVID by deprivation, sex and occupation. These findings will help inform public health policies and interventions in incorporating a social justice and health inequality lens.

COVID-19 and Diabetes.

The prevalence of diabetes in people with coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has varied worldwide. Most of the available evidence suggests a significant increase in severity and mortality of COVID-19 in people with either type 1 (T1DM) or type 2 diabetes mellitus (T2DM), especially in association with poor glycemic control. While new-onset hyperglycemia and new-onset diabetes (both T1DM and T2DM) have been increasingly recognized in the context of COVID-19 and have been associated with worse outcome, no conclusive evidence yet suggests direct tropism of SARS-CoV-2 on the ß cells of pancreatic islets. While all approved oral antidiabetic agents appear to be safe in people with T2DM having COVID-19, no conclusive data are yet available to indicate a mortality benefit with any class of these drugs, in the absence of large randomized controlled trials.

Corrigendum to "The prevalence and long-term health effects of long Covid among hospitalised and non-hospitalised populations: a systematic review and meta-analysis".

[This corrects the article DOI: 10.1016/j.eclinm.2022.101762.].

Ethnic differences in cellular and humoral immune responses to SARS-CoV-2 vaccination in UK healthcare workers: a cross-sectional analysis.

Background: Few studies have compared SARS-CoV-2 vaccine immunogenicity by ethnic group. We sought to establish whether cellular and humoral immune responses to SARS-CoV-2 vaccination differ according to ethnicity in UK Healthcare workers (HCWs). Methods: In this cross-sectional analysis, we used baseline data from two immunological cohort studies conducted in HCWs in Leicester, UK. Blood samples were collected between March 3, and September 16, 2021. We excluded HCW who had not received two doses of SARS-CoV-2 vaccine at the time of sampling and those who had serological evidence of previous SARS-CoV-2 infection. Outcome measures were SARS-CoV-2 spike-specific total antibody titre, neutralising antibody titre and ELISpot count. We compared our outcome measures by ethnic group using univariable (t tests and rank-sum tests depending on distribution) and multivariable (linear regression for antibody titres and negative binomial regression for ELISpot counts) tests. Multivariable analyses were adjusted for age, sex, vaccine type, length of interval between vaccine doses and time between vaccine administration and sample collection and expressed as adjusted geometric mean ratios (aGMRs) or adjusted incidence rate ratios (aIRRs). To assess differences in the early immune response to vaccination we also conducted analyses in a subcohort who provided samples between 14 and 50 days after their second dose of vaccine. Findings: The total number of HCWs in each analysis were 401 for anti-spike antibody titres, 345 for neutralising antibody titres and 191 for ELISpot. Overall, 25.4% (19.7% South Asian and 5.7% Black/Mixed/Other) were from ethnic minority groups. In analyses including the whole cohort, neutralising antibody titres were higher in South Asian HCWs than White HCWs (aGMR 1.47, 95% CI [1.06-2.06], P = 0.02) as were T cell responses to SARS-CoV-2 S1 peptides (aIRR 1.75, 95% CI [1.05-2.89], P = 0.03). In a subcohort sampled between 14 and 50 days after second vaccine dose, SARS-CoV-2 spike-specific antibody and neutralising antibody geometric mean titre (GMT) was higher in South Asian HCWs compared to White HCWs (9616 binding antibody units (BAU)/ml, 95% CI [7178-12,852] vs 5888 BAU/ml [5023-6902], P = 0.008 and 2851 95% CI [1811-4487] vs 1199 [984-1462], P < 0.001 respectively), increments which persisted after adjustment (aGMR 1.26, 95% CI [1.01-1.58], P = 0.04 and aGMR 2.01, 95% CI [1.34-3.01], P = 0.001). SARS-CoV-2 ELISpot responses to S1 and whole spike peptides (S1 + S2 response) were higher in HCWs from South Asian ethnic groups than those from White groups (S1: aIRR 2.33, 95% CI [1.09-4.94], P = 0.03; spike: aIRR, 2.04, 95% CI [1.02-4.08]). Interpretation: This study provides evidence that, in an infection naïve cohort, humoral and cellular immune responses to SARS-CoV-2 vaccination are stronger in South Asian HCWs than White HCWs. These differences are most clearly seen in the early period following vaccination. Further research is required to understand the underlying mechanisms, whether differences persist with further exposure to vaccine or virus, and the potential impact on vaccine effectiveness. Funding: DIRECT and BELIEVE have received funding from UK Research and Innovation (UKRI) through the COVID-19 National Core Studies Immunity (NCSi) programme (MC_PC_20060).

Inequalities in SARS-CoV-2 case rates by ethnicity, religion, measures of socioeconomic position, English proficiency, and self-reported disability: cohort study of 39 million people in England during the alpha and delta waves.

Objective: To examine sociodemographic inequalities in people with SARS-CoV-2 during the second (alpha) and third (delta) waves of the covid-19 pandemic. Design: Retrospective, population based cohort study. Setting: Resident population of England. Participants: 39 006 194 people aged 10 years and older who were enumerated in the 2011 census, registered with the NHS, and alive on 1 September 2020. Main outcome measures: Age standardised SARS-CoV-2 case rates (ie, the number of people who received a positive test result per 100 000 person weeks at risk) during the second wave (1 September 2020 to 22 May 2021) or third wave (23 May to 10 December 2021) of the pandemic. Age standardised rates were calculated by sociodemographic characteristics and adjusted rate ratios were estimated using generalised linear regression models with a Poisson distribution (models were adjusted for covariates including sex, age, geographical variables, and sociodemographic characteristics). Results: During the study period, 5 767 584 people (14.8% of the study population) tested positive for SARS-CoV-2. In the second wave, the fully adjusted relative risks of having a positive test were highest for the Bangladeshi and Pakistani ethnic groups compared with the white British group, with rate ratios of 1.75 (95% confidence interval 1.73 to 1.77) and 1.69 (1.68 to 1.70), respectively. Muslim and Sikh religious groups had fully adjusted rate ratios of 1.51 (1.50 to 1.51) and 1.64 (1.63 to 1.66), respectively, compared with the Christian group. Greater area deprivation, disadvantaged socioeconomic position, living in a care home, and low English language proficiency were also associated with higher relative risk of having a positive test. However, the inequalities among groups varied over time. Being Christian, white British, without a disability, and from a more advantaged socioeconomic position were associated with increased relative risk of testing positive during the third wave. Conclusion: Research is urgently needed to understand the large sociodemographic inequalities in SARS-CoV-2 case rates in order to inform policy interventions in future waves or pandemics.

Digital health, cardiometabolic disease and ethnicity: an analysis of United Kingdom government policies from 2010 to 2022.

Recent health policies in the United Kingdom (UK) and internationally have focussed on digitisation of healthcare. We examined UK policies for evidence of government action addressing health inequalities and digital health, using cardiometabolic disease as an exemplar. Using a systematic search methodology, we identified 87 relevant policy documents published between 2010 and 2022. We found increasing emphasis on digital health, including for prevention, diagnosis and management of cardiometabolic disease. Several policies also focused on tackling health inequalities and improving digital access. The COVID-19 pandemic amplified inequalities. No policies addressed ethnic inequalities in digital health for cardiometabolic disease, despite high prevalence in minority ethnic communities. Our findings suggest that creating opportunities for digital inclusion and reduce longer-term health inequalities, will require future policies to focus on: the heterogeneity of ethnic groups; cross-sectoral disadvantages which contribute to disease burden and digital accessibility; and disease-specific interventions which lend themselves to culturally tailored solutions.

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.

Ethnic disparities in COVID-19 outcomes: a multinational cohort study of 20 million individuals from England and Canada.

BACKGROUND: Heterogeneous studies have demonstrated ethnic inequalities in the risk of SARS-CoV-2 infection and adverse COVID-19 outcomes. This study evaluates the association between ethnicity and COVID-19 outcomes in two large population-based cohorts from England and Canada and investigates potential explanatory factors for ethnic patterning of severe outcomes. METHODS: We identified adults aged 18 to 99 years in the QResearch primary care (England) and Ontario (Canada) healthcare administrative population-based datasets (start of follow-up: 24th and 25th Jan 2020 in England and Canada, respectively; end of follow-up: 31st Oct and 30th Sept 2020, respectively). We harmonised the definitions and the design of two cohorts to investigate associations between ethnicity and COVID-19-related death, hospitalisation, and intensive care (ICU) admission, adjusted for confounders, and combined the estimates obtained from survival analyses. We calculated the 'percentage of excess risk mediated' by these risk factors in the QResearch cohort. RESULTS: There were 9.83 million adults in the QResearch cohort (11,597 deaths; 21,917 hospitalisations; 2932 ICU admissions) and 10.27 million adults in the Ontario cohort (951 deaths; 5132 hospitalisations; 1191 ICU admissions). Compared to the general population, pooled random-effects estimates showed that South Asian ethnicity was associated with an increased risk of COVID-19 death (hazard ratio: 1.63, 95% CI: 1.09-2.44), hospitalisation (1.53; 1.32-1.76), and ICU admission (1.67; 1.23-2.28). Associations with ethnic groups were consistent across levels of deprivation. In QResearch, sociodemographic, lifestyle, and clinical factors accounted for 42.9% (South Asian) and 39.4% (Black) of the excess risk of COVID-19 death. CONCLUSION: International population-level analyses demonstrate clear ethnic inequalities in COVID-19 risks. Policymakers should be cognisant of the increased risks in some ethnic populations and design equitable health policy as the pandemic continues.

Risk of death following COVID-19 vaccination or positive SARS-CoV-2 test in young people in England.

Several studies have reported associations between COVID-19 vaccination and risk of cardiac diseases, especially in young people; the impact on mortality, however, remains unclear. We use national, linked electronic health data in England to assess the impact of COVID-19 vaccination and positive SARS-CoV-2 tests on the risk of cardiac and all-cause mortality in young people (12 to 29 years) using a self-controlled case series design. Here, we show there is no significant increase in cardiac or all-cause mortality in the 12 weeks following COVID-19 vaccination compared to more than 12 weeks after any dose. However, we find an increase in cardiac death in women after a first dose of non mRNA vaccines. A positive SARS-CoV-2 test is associated with increased cardiac and all-cause mortality among people vaccinated or unvaccinated at time of testing.

Ethnic minority representation in UK COVID-19 trials: systematic review and meta-analysis.

BACKGROUND: The COVID-19 pandemic has highlighted health disparities affecting ethnic minority communities. There is growing concern about the lack of diversity in clinical trials. This study aimed to assess the representation of ethnic groups in UK-based COVID-19 randomised controlled trials (RCTs). METHODS: A systematic review and meta-analysis were undertaken. A search strategy was developed for MEDLINE (Ovid) and Google Scholar (1st January 2020-4th May 2022). Prospective COVID-19 RCTs for vaccines or therapeutics that reported UK data separately with a minimum of 50 participants were eligible. Search results were independently screened, and data extracted into proforma. Percentage of ethnic groups at all trial stages was mapped against Office of National Statistics (ONS) statistics. Post hoc DerSimonian-Laird random-effects meta-analysis of percentages and a meta-regression assessing recruitment over time were conducted. Due to the nature of the review question, risk of bias was not assessed. Data analysis was conducted in Stata v17.0. A protocol was registered (PROSPERO CRD42021244185). RESULTS: In total, 5319 articles were identified; 30 studies were included, with 118,912 participants. Enrolment to trials was the only stage consistently reported (17 trials). Meta-analysis showed significant heterogeneity across studies, in relation to census-expected proportions at study enrolment. All ethnic groups, apart from Other (1.7% [95% CI 1.1-2.8%] vs ONS 1%) were represented to a lesser extent than ONS statistics, most marked in Black (1% [0.6-1.5%] vs 3.3%) and Asian (5.8% [4.4-7.6%] vs 7.5%) groups, but also apparent in White (84.8% [81.6-87.5%] vs 86%) and Mixed 1.6% [1.2-2.1%] vs 2.2%) groups. Meta-regression showed recruitment of Black participants increased over time (p = 0.009). CONCLUSIONS: Asian, Black and Mixed ethnic groups are under-represented or incorrectly classified in UK COVID-19 RCTs. Reporting by ethnicity lacks consistency and transparency. Under-representation in clinical trials occurs at multiple levels and requires complex solutions, which should be considered throughout trial conduct. These findings may not apply outside of the UK setting.