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Aims: While cardiovascular disease in patients with type 2 diabetes commonly progresses with the occurrence of repeated events, most trials consider the impact of glucose lowering strategies only on the first event. We examined the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial and its observational follow-up study (ACCORDION) to investigate the impact of intensive glucose control on multiple events and further identify any subgroup effects. Materials and methods: A recurrent events analysis, using a negative binomial regression model, was applied to estimate the treatment effect on different consecutive cardiovascular disease (CVD) events including non-fatal myocardial infarction, non-fatal stroke, hospitalization from heart failure, and cardiovascular death. Interaction terms were used to identify potential effect modifiers. The robustness of the results were confirmed in sensitivity analyses using alternative models. Results: The median duration of follow-up was 7.7 years. Of the 5,128 participants in the intensive and 5,123 in the standard glucose control arm, respectively, 822 (16.0%) and 840 (16.4%) experienced a single event; 189 (3.7%) and 214 (4.2%) two events; 52 (1.0%) and 40 (0.8%) three events; and 1 (0.02%) and 1 (0.02%) four events. There was no evidence of a treatment effect, with a rate difference of 0.0 (-0.3, 0.3) per 100 person-years comparing intensive vs standard intervention, although with nonsignificantly lower event rates in younger patients with HbA1c<7% and higher event rates in older patients with HbA1c≥9%. Discussion: Intensive glucose control may not affect cardiovascular disease progression except in select subgroups. Since time-to-first event analysis may miss beneficial or harmful effects of glucose control on the risk of cardiovascular disease, recurrent events analysis should be routine in cardiovascular outcome trials, particularly when investigating long-term treatment effects. CLINICAL TRIAL REG: no. NCT0000

Walking pace is a simple and functional form of movement and a strong predictor of health status, but the nature of its association with leucocyte telomere length (LTL) is unclear. Here we investigate whether walking pace is associated with LTL, which is causally associated with several chronic diseases and has been proposed as a marker of biological age. Analyses were conducted in 405,981 UK Biobank participants. We show that steady/average and brisk walkers had significantly longer LTL compared with slow walkers, with accelerometer-assessed measures of physical activity further supporting this through an association between LTL and habitual activity intensity, but not with total amount of activity. Bi-directional mendelian randomisation analyses suggest a causal link between walking pace and LTL, but not the other way around. A faster walking pace may be causally associated with longer LTL, which could help explain some of the beneficial effects of brisk walking on health status. Given its simple measurement and low heritability, self-reported walking pace may be a pragmatic target for interventions.

BACKGROUND: The diagnosis of type 2 diabetes (T2D) in younger adults, an increasingly common public health issue, is associated with a higher risk of cardiovascular complications and mortality, which may be due to a more adverse cardiovascular risk profile in individuals diagnosed at a younger age. AIM: To investigate the association between age at diagnosis and the cardiovascular risk profile in adults with T2D. METHODS: A pooled dataset was used, comprised of data from five previous studies of adults with T2D, including 1409 participants of whom 196 were diagnosed with T2D under the age of 40 years. Anthropometric and blood biomarker measurements included body weight, body mass index (BMI), waist circumference, body fat percentage, glycaemic control (HbA1c), lipid profile and blood pressure. Univariable and multivariable linear regression models, adjusted for diabetes duration, sex, ethnicity and smoking status, were used to investigate the association between age at diagnosis and each cardiovascular risk factor. RESULTS: A higher proportion of participants diagnosed with T2D under the age of 40 were female, current smokers and treated with glucose-lowering medications, compared to participants diagnosed later in life. Participants diagnosed with T2D under the age of 40 also had higher body weight, BMI, waist circumference and body fat percentage, in addition to a more adverse lipid profile, compared to participants diagnosed at an older age. Modelling results showed that each one year reduction in age at diagnosis was significantly associated with 0.67 kg higher body weight [95% confidence interval (CI): 0.52-0.82 kg], 0.18 kg/m2 higher BMI (95%CI: 0.10-0.25) and 0.32 cm higher waist circumference (95%CI: 0.14-0.49), after adjustment for duration of diabetes and other confounders. Younger age at diagnosis was also significantly associated with higher HbA1c, total cholesterol, low-density lipoprotein cholesterol and triglycerides. CONCLUSION: The diagnosis of T2D

Obesity and ethnicity are known risk factors for COVID-19 outcomes, but their combination has not been extensively examined. We investigate the association between body mass index (BMI) and COVID-19 mortality across different ethnic groups using linked national Census, electronic health records and mortality data for adults in England from the start of pandemic (January 2020) to December 2020. There were 30,067 (0.27%), 1,208 (0.29%), 1,831 (0.29%), 845 (0.18%) COVID-19 deaths in white, Black, South Asian and other ethnic minority groups, respectively. Here we show that BMI was more strongly associated with COVID-19 mortality in ethnic minority groups, resulting in an ethnic risk of COVID-19 mortality that was dependant on BMI. The estimated risk of COVID-19 mortality at a BMI of 40 kg/m2 in white ethnicities was equivalent to the risk observed at a BMI of 30.1 kg/m2, 27.0 kg/m2, and 32.2 kg/m2 in Black, South Asian and other ethnic minority groups, respectively.

OBJECTIVE: To assess trends in primary and specialist care consultation rates and average length of consultation by cardiovascular disease (CVD), type 2 diabetes mellitus (T2DM), or cardiometabolic multimorbidity exposure status. METHODS: Observational, retrospective cohort study used linked Clinical Practice Research Datalink primary care data from 01/01/2000 to 31/12/2018 to assess consultation rates in 141,328 adults with newly diagnosed T2DM, with or without CVD. Patients who entered the study with either a diagnosis of T2DM or CVD and later developed the second condition during the study are classified as the cardiometabolic multimorbidity group. Face to face primary and specialist care consultations, with either a nurse or general practitioner, were assessed over time in subjects with T2DM, CVD, or cardiometabolic multimorbidity. Changes in the average length of consultation in each group were investigated. RESULTS: 696,255 (mean 4.9 years [95% CI, 2.02-7.66]) person years of follow up time, there were 10,221,798 primary and specialist care consultations. The crude rate of primary and specialist care consultations in patients with cardiometabolic multimorbidity (N = 11,881) was 18.5 (95% CI, 18.47-18.55) per person years, 13.5 (13.50, 13.52) in patients with T2DM only (N = 83,094) and 13.2 (13.18, 13.21) in those with CVD (N = 57,974). Patients with cardiometabolic multimorbidity had 28% (IRR 1.28; 95% CI: 1.27, 1.31) more consultations than those with only T2DM. Patients with cardiometabolic multimorbidity had primary care consultation rates decrease by 50.1% compared to a 45.0% decrease in consultations for those with T2DM from 2000 to 2018. Specialist care consultation rates in both groups increased from 2003 to 2018 by 33.3% and 54.4% in patients with cardiometabolic multimorbidity and T2DM, respectively. For patients with T2DM the average consultation duration increased by 36.0%, in patients with CVD it increased by 74.3%, and in those with cardiometaboli

OBJECTIVE: To assess the association between household size and risk of non-severe or severe COVID-19. DESIGN: A longitudinal observational study. SETTING: This study utilised UK Biobank linked to national SARS-CoV-2 laboratory test data. PARTICIPANTS: 401,910 individuals with available data on household size in UK Biobank. MAIN OUTCOME MEASURES: Household size was categorised as single occupancy, two-person households and households of three or more. Severe COVID-19 was defined as a positive SARS-CoV-2 test on hospital admission or death with COVID-19 recorded as the underlying cause; and non-severe COVID-19 as a positive test from a community setting. Logistic regression models were fitted to assess associations, adjusting for potential confounders. RESULTS: Of 401,910 individuals, 3612 (1%) were identified as having suffered from a severe COVID-19 infection and 11,264 (2.8%) from a non-severe infection, between 16 March 2020 and 16 March 2021. Overall, the odds of severe COVID-19 was significantly higher among individuals living alone (adjusted odds ratio: 1.24 [95% confidence interval: 1.14 to 1.36], or living in a household of three or more individuals (adjusted odds ratio: 1.28 [1.17 to 1.39], when compared to individuals living in a household of two. For non-severe COVID-19 infection, individuals living in a single-occupancy household had lower odds compared to those living in a household of two (adjusted odds ratio: 0.88 [0.82 to 0.93]. CONCLUSIONS: Odds of severe or non-severe COVID-19 infection were associated with household size. Increasing understanding of why certain households are more at risk is important for limiting spread of the infection.

BACKGROUND: Despite generally high coronavirus disease 2019 (COVID-19) vaccination rates in the UK, vaccination hesitancy and lower take-up rates have been reported in certain ethnic minority communities. METHODS: We used vaccination data from the National Immunisation Management System (NIMS) linked to the 2011 Census and individual health records for subjects aged ≥40 years (n = 24 094 186). We estimated age-standardized vaccination rates, stratified by ethnic group and key sociodemographic characteristics, such as religious affiliation, deprivation, educational attainment, geography, living conditions, country of birth, language skills and health status. To understand the association of ethnicity with lower vaccination rates, we conducted a logistic regression model adjusting for differences in geographic, sociodemographic and health characteristics. ResultsAll ethnic groups had lower age-standardized rates of vaccination compared with the white British population, whose vaccination rate of at least one dose was 94% (95% CI: 94%-94%). Black communities had the lowest rates, with 75% (74-75%) of black African and 66% (66-67%) of black Caribbean individuals having received at least one dose. The drivers of these lower rates were partly explained by accounting for sociodemographic differences. However, modelled estimates showed significant differences remained for all minority ethnic groups, compared with white British individuals. CONCLUSIONS: Lower COVID-19 vaccination rates are consistently observed amongst all ethnic minorities.

AIMS: To understand geographical and temporal patterns in the diabetes gap, the excess mortality risk associated with type 2 diabetes (T2D), in three high-income countries. METHODS: Using databases from Canada (Ontario), Spain (Catalonia) and the UK (England), we harmonized the study design and the analytical strategy to extract information on subjects aged over 35 years with incident T2D between 1998 and 2018 matched to up to five subjects without diabetes. We used Poisson models to estimate age-specific mortality trends by diabetes status and rate ratios and rate differences associated with T2D. RESULTS: In more than 6 million people, 694 454 deaths occurred during a follow-up of 52 million person-years. Trends in all-cause mortality rates differed between Ontario and England; yet, the diabetes gaps were very similar in recent years: in 2018, we estimated 1.3 (95% confidence interval: 0.8, 1.8) and 0.8 (0.2, 1.5) more deaths per 1000 person-years in 50-year-old men with diabetes in Ontario and England, respectively, and 8.9 (6.1, 11.7) and 12.1 (9.1, 15.1) in 80-year-old men; between-country differences were small also in women. In Catalonia, rate ratios comparing T2D with no diabetes in men in 2018 were 1.53 (1.11, 2.11) at 50 years old, 0.88 (0.72, 1.06) at 60 years old, 0.74 (0.60, 0.90) at 70 years old and 0.81 (0.66, 1.00) at 80 years old, indicating lower mortality rates in men with T2D from the age of 60 years; rates were similar in women with and without diabetes at all ages. The diabetes gaps in cardiorenal mortality mirrored those of all-cause mortality: we observed consistent reductions in the proportions of cardiorenal deaths in subjects aged 80 years but variations in subjects aged ≤70 years, regardless of the presence of diabetes. CONCLUSIONS: By reducing the confounding impact of epidemiological and analytical differences, this study showed geographical similarities and differences in the diabetes gap: an excess risk of all-cause and cardiorenal mor

OBJECTIVE: To estimate associations between covid-19 vaccination and long covid symptoms in adults with SARS-CoV-2 infection before vaccination. DESIGN: Observational cohort study. SETTING: Community dwelling population, UK. PARTICIPANTS: 28 356 participants in the Office for National Statistics COVID-19 Infection Survey aged 18-69 years who received at least one dose of an adenovirus vector or mRNA covid-19 vaccine after testing positive for SARS-CoV-2 infection. MAIN OUTCOME MEASURE: Presence of long covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021. RESULTS: Mean age of participants was 46 years, 55.6% (n=15 760) were women, and 88.7% (n=25 141) were of white ethnicity. Median follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (83.8% of participants). 6729 participants (23.7%) reported long covid symptoms of any severity at least once during follow-up. A first vaccine dose was associated with an initial 12.8% decrease (95% confidence interval -18.6% to -6.6%, P<0.001) in the odds of long covid, with subsequent data compatible with both increases and decreases in the trajectory (0.3% per week, 95% confidence interval -0.6% to 1.2% per week, P=0.51). A second dose was associated with an initial 8.8% decrease (95% confidence interval -14.1% to -3.1%, P=0.003) in the odds of long covid, with a subsequent decrease by 0.8% per week (-1.2% to -0.4% per week, P<0.001). Heterogeneity was not found in associations between vaccination and long covid by sociodemographic characteristics, health status, hospital admission with acute covid-19, vaccine type (adenovirus vector or mRNA), or duration from SARS-CoV-2 infection to vaccination. CONCLUSIONS: The likelihood of long covid symptoms was observed to decrease after covid-19 vaccination and evidence suggested sustained improvement after a second dose, at least over the median follow-up of 67 days. Vaccination may co

AIMS: To quantify ethnic differences in the risk of all-cause mortality and cardiovascular disease (CVD) events following a first CVD event in people with and without type 2 diabetes. METHODS: We identified 5,349,271 subjects with a first CVD between 1 January 2002 and 31 May 2020 in England; CVD included aortic aneurism, cerebrovascular accident, heart failure, myocardial infarction, peripheral vascular disease, and other cardiovascular diseases. We estimated adjusted hazard ratios (HRs) for type 2 diabetes and ethnicity of three outcomes: fatal and nonfatal second CVD event (different phenotype compared to the first) and all-cause mortality. RESULTS: Relative to White, HRs indicated lower rates in all ethnicities and for all outcomes in both men (from 0.64 to 0.79 for all-cause death; 0.78-0.79 for CVD-related death; and 0.85-0.98 for a second CVD event) and women (0.69-0.77; 0.77-0.83; 0.83-0.95, respectively). Irrespective of ethnicity and sex, type 2 diabetes increased rates of all outcomes by around a third. CONCLUSIONS: Prognosis following a CVD event was consistently worse in subjects with type 2 diabetes while varied across ethnicities, suggesting the implementation of different strategies for the secondary prevention of CVD in different ethnic groups.

BACKGROUND AND AIMS: To describe sociodemographic, lifestyle, environmental and traditional clinical risk factor differences between ethnic groups and to investigate the extent to which such differences confound the association between ethnic groups and the risk of cardiovascular disease (CVD) METHODS AND RESULTS: A total of 440,693 white European (55.9% women), 7305 South Asian (48.6%) and 7628 black African or Caribbean (57.7%) people were included from UK Biobank. Associations between ethnicity and cardiovascular outcomes (composite of non-fatal stroke, non-fatal myocardial infarction and CVD death) were explored using Cox-proportional hazard models. Models were adjusted for sociodemographic, lifestyle, environmental and clinical risk factors. Over a median (IQR) of 12.6 (11.8, 13.3) follow-up years, there were 22,711 (5.15%) cardiovascular events in white European, 463 (6.34%) in South Asian and 302 (3.96%) in black African or Caribbean individuals. For South Asian people, the cardiovascular hazard ratio (HR) compared to white European people was 1.28 (99% CI [1.16, 1.43]). For black African or Caribbean people, the HR was 0.80 (0.66, 0.97). The elevated risk of CVD in South Asians remained after adjusting for differences in sociodemographic, lifestyle, environmental and clinical factors, whereas the lower risk in black African or Caribbean was largely attenuated. CONCLUSIONS: South Asian, but not black African or Caribbean individuals, have a higher risk of CVD compared to white European individuals. This higher risk in South Asians was independent of sociodemographic, lifestyle, environmental and clinical factors.

BACKGROUND AND AIMS: Both polygenic risk scores (PGS) and self-reported walking pace have been shown to predict cardiovascular disease; whether combining both factors produces greater risk differentiation is, however, unknown. METHODS AND RESULTS: We estimated the 10-year absolute risk of coronary artery disease (CAD), adjusted for traditional risk factors, and the C-index across nine PGS and self-reported walking pace in UK Biobank study participants between Mar/2006-Feb/2021. In 380,693 individuals (54.8% women), over a median (5th, 95th percentile) of 11.9 (8.3, 13.4) years, 2,603 (1.2%) CAD events occurred in women and 8,259 (4.8%) in men. Both walking pace and genetic risk were strongly associated with CAD. The absolute 10-year risk of CAD was highest in slow walkers at high genetic risk (top 20% of PGS): 2.72% (95% CI: 2.30-3.13) in women; 9.60% (8.62-10.57) in men. The risk difference between slow and brisk walkers was greater at higher [1.26% (0.81-1.71) in women; 3.63% (2.58-4.67) in men] than lower [0.76% (0.59-0.93) and 2.37% (1.96-2.78), respectively] genetic risk. Brisk walkers at high genetic risk had equivalent (women) or higher (men) risk than slow walkers at moderate-to-low genetic risk (bottom 80% of PGS). When added to a model containing traditional risk factors, both factors separately improved risk discrimination; combining them resulted in the greatest discrimination: C-index of 0.801 (0.793-0.808) in women; 0.732 (0.728-0.737) in men. CONCLUSION: Self-reported slow walkers at high genetic risk had the greatest risk of CAD, identifying a potentially important population for intervention. Both PGS and walking pace contributed to risk discrimination.

OBJECTIVES: This review aims to summarize key methods for estimating years of life lost (YLL), highlighting their differences and how they can be implemented in current software, and applies them in a real-world example. STUDY DESIGN AND SETTING: We investigated the common YLL methods: (1) Years of potential life lost (YPLL); (2) Global Burden of Disease (GBD) approach; (3) Life tables; (4) Poisson regression; and (5) Flexible parametric Royston-Parmar regression. We used data from UK Biobank and multimorbidity as our example. RESULTS: For the YPLL and GBD method, the analytical procedures allow only to quantify the average YLL within each group (with and without multimorbidity) and, from them, their difference; conversely, for the other methods both the remaining life expectancy within each group and the YLL could be estimated. At 65 years, the YLL in those with vs. without multimorbidity was 1.8, 1.2, and 2.7 years using the life tables approach and the Poisson, and Royston-Parmar regression, respectively; corresponding values were -0.73 and -0.05 years for YPLL and using the GBD approach. CONCLUSION: While deciding among different methods to estimate YLL, researchers should consider the purpose of the research, the type of available data, and the flexibility of the model.

AIMS: Most trials leading to the approval of glucagon-like peptide receptor agonists (GLP-1RAs) and sodium-glucose co-transporter-2 inhibitors (SGLT2is) were primarily designed to confirm their non-inferiority to placebo (commonly using an upper 95% confidence limit threshold of 1.3) and, if confirmed, superiority (threshold 1): this asymmetry of margins (1 vs. 1.3) favours the active intervention. We aimed to quantify the probability of clinical superiority of the active treatment by applying the same threshold used to claim non-inferiority. MATERIALS AND METHODS: We searched PubMed and Cochrane CENTRAL for cardiorenal outcome trials in subjects with type 2 diabetes published before 5 December 2021, to reconstruct from Kaplan-Meier plots individual-level data for the primary outcome or all-cause mortality. We calculated Bayesian posterior densities to obtain the probability for a treatment effect (hazard ratio) <0.769, which is symmetric to the 1.3 threshold (i.e. its reciprocal 1/1.3), emulating a scenario where the active treatment is placebo and placebo is the active treatment. RESULTS: We extracted data from 27 Kaplan-Meier plots (18 for the primary outcome, nine for mortality). Probabilities of clinical superiority to placebo varied significantly: for GLP-1RAs, from a minimum of 0% to a maximum of 69% for the primary outcome and from 0% to 8% for mortality; corresponding estimates for SGLT2is were 0% to 96% and 0% to 93%. Probabilities were on average greater for SGLT2is, particularly in trials investigating kidney or heart failure outcomes. CONCLUSIONS: The probability of clinical superiority to placebo varies widely across trials previously reported as showing superiority of GLP-1RAs or SGLT2is compared with placebo. These results showed within- and between-class differences, highlight the drawbacks of a binary interpretation of the results, particularly in the context of the current designs of non-inferiority trials, and have implications for decision maker

We investigated long COVID incidence by vaccination status in a random sample of UK adults from April 2020 to November 2021. Persistent symptoms were reported by 9.5% of 3090 breakthrough severe acute respiratory syndrome coronavirus 2 infections and 14.6% of unvaccinated controls (adjusted odds ratio, 0.59 [95% confidence interval, .50-.69]), emphasizing the need for public health initiatives to increase population-level vaccine uptake.

BACKGROUND: Frailty is characterized by the loss of biological reserves and vulnerability to adverse outcomes. In individuals with chronic kidney disease (CKD), numerous pathophysiological factors may be responsible for frailty development including inflammation, physical inactivity, reduced energy intake, and metabolic acidosis. Given that both CKD and frailty incur a significant healthcare burden, it is important to understand the relationship of CKD and frailty in real-world routine clinical practice, and how simple frailty assessment methods (e.g. frailty indexes) may be useful. We investigated the risk of frailty development in CKD and the impact of frailty status on mortality and end-stage kidney disease (ESKD). METHODS: A retrospective cohort study using primary care records from the Clinical Practice Research Datalink linked to Hospital Episode Statistics and the UK Office for National Statistics was undertaken in 819 893 participants aged ≥40 years, of which 140 674 had CKD. Frailty was defined using an electronic frailty index, generated electronically from primary care records. Cox proportional hazard and flexible parametric survival models were used to investigate the risk of developing frailty and the effect of frailty on risk of all-cause and cardiovascular mortality, and ESKD. RESULTS: The mean age of those with CKD was 77.5 (SD 9.7) years [61.0 (SD 12.1) years in no-CKD group]; 62.0% of the CKD group were female (compared with 53.3% in no-CKD group). The mean estimated glomerular filtration rate of those with CKD was 46.1 (SD 9.9) mL/min/1.73 m2 . The majority of those with CKD (75.3%) were frail [vs. 45.4% in those without CKD (no-CKD)]. Over 3 years (median), 69.5% of those with CKD developed frailty. Compared with no-CKD, those with CKD had increased rates of developing mild (hazard ratio: 1.02; 95% confidence interval: 1.01-1.04), moderate (1.30; 1.26-1.34), and severe (1.50; 1.37-1.65) frailty. Mild (1.22; 1.19-1.24), moderate (1.60; 1.56-1.63)

AIMS: To determine whether telephone and face-to-face primary care consultation rates, costs, and temporal trends during 2000 to 2018 differed by the number of comorbidities in people with type 2 diabetes (T2DM). METHODS: A total of 120 409 adults with newly diagnosed T2DM between 2000 and 2018 were classified by the number of prevalent and incident comorbidities. Data on face-to-face and telephone primary care consultations with a nurse or physician were obtained. Crude and sex- and age-adjusted annual consultation rates and associated costs were calculated based on the number of comorbidities at the time of consultation. RESULTS: The crude rate of face-to-face primary care consultations for patients without comorbidities was 10.3 (95% confidence interval [CI] 10.3-10.4) per person-year, 12.7 (95% CI 12.7-12.7) for patients with one comorbidity, 15.1 (95% CI 15.1-15.2) for those with two comorbidities, and 18.7 (95% CI 18.7-18.8) for those with three or more comorbidities. The mean annual inflation-adjusted cost for face-to-face consultations was £412.70 per patient without comorbidities, £516.80 for one comorbidity, £620.75 for two comorbidities, and £778.83 for three or more comorbidities. The age- and sex-adjusted face-to-face consultation rate changed by an average of -3.3% (95% CI -4.4 to -2.3) per year from 2000 to 2018 for patients without comorbidities, -2.7% (95% CI -4.0 to -1.3) for those with one comorbidity, -2.2% (95% CI -3.3 to -1.2) for those with two comorbidities, and -4.3% (95% CI -8.7 to +0.3) for those with three or more comorbidities. CONCLUSIONS: Although consultation rates for all patients decreased from 2000 to 2018, there was a significant disparity between the rate for patients with and without comorbidities. Patients with T2DM and comorbidities may require different models of service delivery.

OBJECTIVE: Using a large national database of people hospitalised with COVID-19, we investigated the contribution of cardio-metabolic conditions, multi-morbidity and ethnicity on the risk of in-hospital cardiovascular complications and death. METHODS: A multicentre, prospective cohort study in 302 UK healthcare facilities of adults hospitalised with COVID-19 between 6 February 2020 and 16 March 2021. Logistic models were used to explore associations between baseline patient ethnicity, cardiometabolic conditions and multimorbidity (0, 1, 2, >2 conditions), and in-hospital cardiovascular complications (heart failure, arrhythmia, cardiac ischaemia, cardiac arrest, coagulation complications, stroke), renal injury and death. RESULTS: Of 65 624 patients hospitalised with COVID-19, 44 598 (68.0%) reported at least one cardiometabolic condition on admission. Cardiovascular/renal complications or death occurred in 24 609 (38.0%) patients. Baseline cardiometabolic conditions were independently associated with increased odds of in-hospital complications and this risk increased in the presence of cardiometabolic multimorbidity. For example, compared with having no cardiometabolic conditions, 1, 2 or ≥3 conditions was associated with 1.46 (95% CI 1.39 to 1.54), 2.04 (95% CI 1.93 to 2.15) and 3.10 (95% CI 2.92 to 3.29) times higher odds of any cardiovascular/renal complication, respectively. A similar pattern was observed for all-cause death. Compared with the white group, the South Asian (OR 1.19, 95% CI 1.10 to 1.29) and black (OR 1.53 to 95% CI 1.37 to 1.72) ethnic groups had higher risk of any cardiovascular/renal complication. CONCLUSIONS: In hospitalised patients with COVID-19, cardiovascular complications or death impacts just under half of all patients, with the highest risk in those of South Asian or Black ethnicity and in patients with cardiometabolic multimorbidity.

BACKGROUND: Obesity accompanied by excess ectopic fat storage has been postulated as a risk factor for severe disease in people with SARS-CoV-2 through the stimulation of inflammation, functional immunologic deficit and a pro-thrombotic disseminated intravascular coagulation with associated high rates of venous thromboembolism. METHODS: Observational studies in COVID-19 patients reporting data on raised body mass index at admission and associated clinical outcomes were identified from MEDLINE, Embase, Web of Science and the Cochrane Library up to 16 May 2020. Mean differences and relative risks (RR) with 95% confidence intervals (CIs) were aggregated using random effects models. RESULTS: Eight retrospective cohort studies and one cohort prospective cohort study with data on of 4,920 patients with COVID-19 were eligible. Comparing BMI ≥ 25 vs <25 kg/m2, the RRs (95% CIs) of severe illness and mortality were 2.35 (1.43-3.86) and 3.52 (1.32-9.42), respectively. In a pooled analysis of three studies, the RR (95% CI) of severe illness comparing BMI > 35 vs <25 kg/m2 was 7.04 (2.72-18.20). High levels of statistical heterogeneity were partly explained by age; BMI ≥ 25 kg/m2 was associated with an increased risk of severe illness in older age groups (≥60 years), whereas the association was weaker in younger age groups (<60 years). CONCLUSIONS: Excess adiposity is a risk factor for severe disease and mortality in people with SARS-CoV-2 infection. This was particularly pronounced in people 60 and older. The increased risk of worse outcomes from SARS-CoV-2 infection in people with excess adiposity should be taken into account when considering individual and population risks and when deciding on which groups to target for public health messaging on prevention and detection measures. Systematic review registration: PROSPERO 2020: CRD42020179783.

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 re

BACKGROUND: Obesity, depressive disorders and antidepressant drugs are associated with increased mortality, cardiovascular disease, diabetes, fractures and falls. We explored outcomes associated with the most commonly prescribed antidepressants in overweight or obese people with depression. METHODS AND FINDINGS: We identified a cohort of overweight or obese adults (≥18 years) in primary care from the UK Clinical Practice Research Datalink, linked with hospital and mortality data, between 1 January 2000 and 31 December 2016 who developed incident depression to January 2019. Cox proportional hazards models and 99% confidence intervals were used to estimate hazard ratios (HR) for mortality, cardiovascular disease, diabetes, and falls/fractures associated with exposure to selective serotonin reuptake inhibitors (SSRIs), tricyclic (TCA)/other, combination antidepressants, citalopram, fluoxetine, sertraline, amitriptyline and mirtazapine, adjusting for potential confounding variables. In 519,513 adults, 32,350 (9.2 per 1,000 years) displayed incident depression and 21,436 (66.3%) were prescribed ≥1 antidepressant. Compared with no antidepressants, all antidepressant classes were associated with increased relative risks of cardiovascular disorders [SSRI HR: 1.32 (1.14-1.53), TCA/Other HR: 1.26 (1.01-1.58)], and diabetes (any type) [SSRI HR: 1.28 (1.10-1.49), TCA/Other: 1.52 (1.19-1.94)]. All commonly prescribed antidepressants except citalopram were associated with increased mortality compared with no antidepressants. However, prescription ≥1 year of ≥40mg citalopram was associated with increased mortality and falls/fractures and ≥1 year 100mg sertraline with increased falls/fractures. CONCLUSIONS: In overweight/obese people with depression, antidepressants may be overall and differentially associated with increased risks of some adverse outcomes. Further research is required to exclude indication bias and residual confounding.

Although myocarditis and pericarditis were not observed as adverse events in coronavirus disease 2019 (COVID-19) vaccine trials, there have been numerous reports of suspected cases following vaccination in the general population. We undertook a self-controlled case series study of people aged 16 or older vaccinated for COVID-19 in England between 1 December 2020 and 24 August 2021 to investigate hospital admission or death from myocarditis, pericarditis and cardiac arrhythmias in the 1-28 days following adenovirus (ChAdOx1, n = 20,615,911) or messenger RNA-based (BNT162b2, n = 16,993,389; mRNA-1273, n = 1,006,191) vaccines or a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive test (n = 3,028,867). We found increased risks of myocarditis associated with the first dose of ChAdOx1 and BNT162b2 vaccines and the first and second doses of the mRNA-1273 vaccine over the 1-28 days postvaccination period, and after a SARS-CoV-2 positive test. We estimated an extra two (95% confidence interval (CI) 0, 3), one (95% CI 0, 2) and six (95% CI 2, 8) myocarditis events per 1 million people vaccinated with ChAdOx1, BNT162b2 and mRNA-1273, respectively, in the 28 days following a first dose and an extra ten (95% CI 7, 11) myocarditis events per 1 million vaccinated in the 28 days after a second dose of mRNA-1273. This compares with an extra 40 (95% CI 38, 41) myocarditis events per 1 million patients in the 28 days following a SARS-CoV-2 positive test. We also observed increased risks of pericarditis and cardiac arrhythmias following a positive SARS-CoV-2 test. Similar associations were not observed with any of the COVID-19 vaccines, apart from an increased risk of arrhythmia following a second dose of mRNA-1273. Subgroup analyses by age showed the increased risk of myocarditis associated with the two mRNA vaccines was present only in those younger than 40.

Despite growing awareness of the dangers of a dichotomous interpretation of trial results based on the 'statistical significance' of a treatment effect, the uptake of new approaches has been slow in diabetes medicine. We showcase a number of ways to interpret the evidence for a treatment effect applied to the cardiovascular outcome trials of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose co-transporter-2 inhibitors (SGLT-2is): the P value function (or confidence curves), which depicts the treatment effect across the whole spectrum of confidence levels; the counternull value, which is the hazard ratio (i.e. treatment effect size) supported by the same amount of evidence as the null value (i.e. no treatment effect); and the S value, which quantifies the strength of the evidence against the null hypothesis in terms of the number of coin tosses yielding the same side. We show how this approach identifies potential treatment effects, highlights similarities among trials straddling the threshold of statistical significance, and quantifies differences in the strength of the evidence from trials reporting statistically significant results. For example, while REWIND, CANVAS and CREDENCE failed to reach statistical significance at the .05 level for all-cause mortality, their counternull values indicate that reduced death rates by 19%, 24% and 31%, respectively, are supported by the same amount of evidence as that indicating no treatment effect. Moreover, similarities among results emerge in trials of GLP-1RAs (REWIND, EXSCEL and LEADER) lying closely around the threshold of 'statistical significance'. Lastly, several S values, such as for the primary outcome in HARMONY Outcomes (S value 10.9) and all-cause death in EMPAREG-OUTCOME (S value 15.0), stand out compared with values for other outcomes and other trials, suggesting much larger differences in the evidence between these studies and several others that cluster around the .05 significance thresho

AIMS: The primary aim was to evaluate the effectiveness of a model integrating diabetes services across primary, secondary and community care (Transformation model). The secondary aim was to understand whether changes resulted from the model. METHODS: The model was implemented In Leicester, Leicestershire and Rutland (UK) across three clinical commissioning groups, the acute trust and accompanying stakeholders. One clinical commissioning group (Leicester City) implemented the entire model and was the primary evaluation population. A quasi-experimental interrupted time series design was employed. The primary outcome was number of Type 2 diabetes-related bed-days per 1000 patients. RESULTS: In the primary population, the mean number of Type 2 diabetes-related bed-days per 1000 patients was increasing before model implementation by 0.33/month (95% confidence interval: -0.07, 0.72), whereas it was decreasing after implementation by a mean value of -0.14/month (-0.33, 0.06); a statistically significant difference (p = 0.04). Secondary analyses showed: nationally, there was no significant change between the pre- and post-periods so it is unlikely that large secular change drove the improvement; the other two Leicestershire clinical commissioning groups saw improvement or stability; underlying processes worked as hypothesised overall; diabetes biomedical markers deteriorated in the primary care population suggesting a change in case-mix due to moving some patients out of secondary care. CONCLUSIONS: Given that the initial aim was to shift services from secondary to primary care without causing harm, an improvement is better than expected. This observational evaluation cannot show conclusively that improvements were due to the Transformation model, but secondary analyses support this.

BACKGROUND: People from South Asian and black minority ethnic groups are disproportionately affected by the COVID-19 pandemic. It is unknown whether deprivation mediates this excess ethnic risk. METHODS: We used UK Biobank with linked COVID-19 outcomes occurring between 16th March 2020 and 24th August 2020. A four-way decomposition mediation analysis was used to model the extent to which the excess risk of testing positive, severe disease and mortality for COVID-19 in South Asian and black individuals, relative to white individuals, would be eliminated if levels of high material deprivation were reduced within the population. RESULTS: We included 15 044 (53.0% women) South Asian and black and 392 786 (55.2% women) white individuals. There were 151 (1.0%) positive tests, 91 (0.6%) severe cases and 31 (0.2%) deaths due to COVID-19 in South Asian and black individuals compared with 1471 (0.4%), 895 (0.2%) and 313 (0.1%), respectively, in white individuals. Compared with white individuals, the relative risk of testing positive for COVID-19, developing severe disease and COVID-19 mortality in South Asian and black individuals were 2.73 (95% CI: 2.26, 3.19), 2.96 (2.31, 3.61) and 4.04 (2.54, 5.55), respectively. A hypothetical intervention moving the 25% most deprived in the population out of deprivation was modelled to eliminate between 40 and 50% of the excess risk of all COVID-19 outcomes in South Asian and black populations, whereas moving the 50% most deprived out of deprivation would eliminate over 80% of the excess risk of COVID-19 outcomes. CONCLUSIONS: The excess risk of COVID-19 outcomes in South Asian and black communities could be substantially reduced with population level policies targeting material deprivation.

AIM: To investigate factors associated with delays in receiving glucose-lowering therapy in patients newly diagnosed with type 2 diabetes mellitus (T2DM), and explore the preferential order and time of intensifications. MATERIALS AND METHODS: Retrospective cohort study including 120 409 adults with T2DM initiating first- to fourth-line glucose-lowering therapy in primary care between 2000 and 2018, using the UK Clinical Practice Research Datalink linked to Hospital Episode Statistics, Office of National Statistics death registration, and 2007 Index of Multiple Deprivation data. Associations were investigated using time-to-event analysis. RESULTS: The longest delays to prescription of first-line therapy were observed in older patients, of black or other ethnicities, and with multimorbidity. People from the most deprived areas received earlier first-line treatment than those from the least deprived areas. The majority were treated with metformin (82.4%) as the first-line prescription, sulphonylurea (50.4%) as second-line, dipeptidyl peptidase-4 inhibitor (27.7%) as third-line, and insulin (28.0%) as fourth-line. In the past 5 years, there was an increase in prescriptions of dipeptidyl peptidase-4-inhibitor and sodium-glucose transport protein-2 inhibitor. The median time was 0.5 years for first-line prescription, 4.1 for second-line, 4.6 for third-line and 4.7 for fourth-line. After T2DM diagnosis, 25% of patients developed cardiovascular disease and non-cardiovascular disease complications within a median time of 12-14 years, and received intensification 5-6 years later. CONCLUSIONS: Within the complex challenges of managing blood glucose levels and risk of additional comorbidities, future health care research and guidelines should focus on overcoming therapeutic inertia particularly at an earlier stage for older patients, from ethnic minorities and with multimorbidities.

BACKGROUND: Health and key workers have elevated odds of developing severe COVID-19; it is not known, however, if this is exacerbated in those with irregular work patterns. We aimed to investigate the odds of developing severe COVID-19 in health and shift workers. METHODS: We included UK Biobank participants in employment or self-employed at baseline (2006-2010) and with linked COVID-19 data to 31st August 2020. Participants were grouped as neither a health worker nor shift worker (reference category) at baseline, health worker only, shift worker only, or both, and associations with severe COVID-19 investigated in logistic regressions. RESULTS: Of 235,685 participants (81·5% neither health nor shift worker, 1·4% health worker only, 16·9% shift worker only, and 0·3% both), there were 580 (0·25%) cases of severe COVID-19. The odds of severe COVID-19 was higher in health workers (adjusted odds ratio: 2·32 [95% CI: 1·33, 4·05]; shift workers (2·06 [1·72, 2·47]); and in health workers who worked shifts (7·56 [3·86, 14·79]). Being both a health worker and a shift worker had a possible greater impact on the odds of severe COVID-19 in South Asian and Black and African Caribbean ethnicities compared to White individuals. CONCLUSIONS: Both health and shift work (measured at baseline, 2006-2010) were independently associated with over twice the odds of severe COVID-19 in 2020; the odds were over seven times higher in health workers who work shifts. Vaccinations, therapeutic and preventative options should take into consideration not only health and key worker status but also shift worker status.

BACKGROUND: Heart failure (HF) together with type 2 diabetes (T2D) and chronic kidney disease (CKD) are major pandemics of the twenty first century. It is not known in people with new onset HF, what the distinct and combined associations are between T2D and CKD comorbidities and cause-specific hospital admissions and death, over the past 20 years. METHODS: An observational study using the UK Clinical Practice Research Datalink linked to the Hospital Episode Statistics in England (1998-2017). Participants were people aged ≥30 years with new onset HF. Exposure groups were HF with: (i) no T2D and no CKD (reference group); (ii) CKD-only (estimated glomerular filtration rate (eGFR) <60 ml/min per 1.73 m2); (iii) T2D-only; (iv) T2D and CKD. CKD severity groups were: CKD-3a (eGFR 45-59); CKD-3b (30-44); CKD-4 (15-29); CKD-5 (<15). Outcomes were cardiovascular and non-cardiovascular hospitalisations and all-cause death. FINDINGS: In 87,709 HF patients (mean age, 78 years; 49% female), 40% had CKD-only, 12% T2D-only, and 16% both. Age-standardised first-year CVD hospitalisation rates were significantly higher in HF patients with CKD-only (46.4; 95% CI 44.9,47.9 per 100 person years) and T2D-only (49.2; 46.7,58.8) than in the reference group (35.1; 34.0,36.1); the highest rate was in patients with T2D-CKD-5: 89.1 (65.8,112.4). Similar patterns were observed for non-CVD hospitalisations and deaths. Group differences remained significant after adjustment for potential confounders. Median survival was highest in the reference (4.4 years) and HF-T2D-only (4.1 years) groups, compared to HF-CKD-only (2.2 years). HF-T2D-CKD group survival ranged from 2.8 (CKD-3a) to 0.7 years (CKD-5). Over time, CVD hospitalisation rates significantly increased for HF-CKD-only (+26%) and reduced (-24%) for HF-T2D-only groups; no reductions were observed in any of the HF-T2D-CKD groups. Trends were similar for non-CVD hospitalisations and death: whilst death rates significantly reduced for HF-T2D-onl

OBJECTIVE: To assess the association between covid-19 vaccines and risk of thrombocytopenia and thromboembolic events in England among adults. DESIGN: Self-controlled case series study using national data on covid-19 vaccination and hospital admissions. SETTING: Patient level data were obtained for approximately 30 million people vaccinated in England between 1 December 2020 and 24 April 2021. Electronic health records were linked with death data from the Office for National Statistics, SARS-CoV-2 positive test data, and hospital admission data from the United Kingdom's health service (NHS). PARTICIPANTS: 29 121 633 people were vaccinated with first doses (19 608 008 with Oxford-AstraZeneca (ChAdOx1 nCoV-19) and 9 513 625 with Pfizer-BioNTech (BNT162b2 mRNA)) and 1 758 095 people had a positive SARS-CoV-2 test. People aged ≥16 years who had first doses of the ChAdOx1 nCoV-19 or BNT162b2 mRNA vaccines and any outcome of interest were included in the study. MAIN OUTCOME MEASURES: The primary outcomes were hospital admission or death associated with thrombocytopenia, venous thromboembolism, and arterial thromboembolism within 28 days of three exposures: first dose of the ChAdOx1 nCoV-19 vaccine; first dose of the BNT162b2 mRNA vaccine; and a SARS-CoV-2 positive test. Secondary outcomes were subsets of the primary outcomes: cerebral venous sinus thrombosis (CVST), ischaemic stroke, myocardial infarction, and other rare arterial thrombotic events. RESULTS: The study found increased risk of thrombocytopenia after ChAdOx1 nCoV-19 vaccination (incidence rate ratio 1.33, 95% confidence interval 1.19 to 1.47 at 8-14 days) and after a positive SARS-CoV-2 test (5.27, 4.34 to 6.40 at 8-14 days); increased risk of venous thromboembolism after ChAdOx1 nCoV-19 vaccination (1.10, 1.02 to 1.18 at 8-14 days) and after SARS-CoV-2 infection (13.86, 12.76 to 15.05 at 8-14 days); and increased risk of arterial thromboembolism after BNT162b2 mRNA vaccination (1.06, 1.01 to 1.10 at 15-21 da

OBJECTIVE: To quantify the association between accelerometer-assessed physical activity and coronavirus disease 2019 (COVID-19) outcomes. METHODS: Data from 82,253 UK Biobank participants with accelerometer data (measured 2013-2015), complete covariate data, and linked COVID-19 data from March 16, 2020, to March 16, 2021, were included. Two outcomes were investigated: severe COVID-19 (positive test result from in-hospital setting or COVID-19 as primary cause of death) and nonsevere COVID-19 (positive test result from community setting). Logistic regressions were used to assess associations with moderate to vigorous physical activity (MVPA), total activity, and intensity gradient. A higher intensity gradient indicates a higher proportion of vigorous activity. RESULTS: Average MVPA was 48.1 (32.7) min/d. Physical activity was associated with lower odds of severe COVID-19 (adjusted odds ratio per standard deviation increase: MVPA, 0.75 [95% CI, 0.67 to 0.85]; total, 0.83 [0.74 to 0.92]; intensity, 0.77 [0.70 to 0.86]), with stronger associations in women (MVPA, 0.63 [0.52 to 0.77]; total, 0.76 [0.64 to 0.90]; intensity, 0.63 [0.53 to 0.74]) than in men (MVPA, 0.84 [0.73 to 0.97]; total, 0.88 [0.77 to 1.01]; intensity, 0.88 [0.77 to 1.00]). In contrast, when mutually adjusted, total activity was associated with higher odds of a nonsevere infection (1.10 [1.04 to 1.16]), whereas the intensity gradient was associated with lower odds (0.91 [0.86 to 0.97]). CONCLUSION: Odds of severe COVID-19 were approximately 25% lower per standard deviation (∼30 min/d) MVPA. A greater proportion of vigorous activity was associated with lower odds of severe and nonsevere infections. The association between total activity and higher odds of a nonsevere infection may be through greater community engagement and thus more exposure to the virus. Results support calls for public health messaging highlighting the potential of MVPA for reducing the odds of severe COVID-19.

Emerging reports of rare neurological complications associated with COVID-19 infection and vaccinations are leading to regulatory, clinical and public health concerns. We undertook a self-controlled case series study to investigate hospital admissions from neurological complications in the 28 days after a first dose of ChAdOx1nCoV-19 (n = 20,417,752) or BNT162b2 (n = 12,134,782), and after a SARS-CoV-2-positive test (n = 2,005,280). There was an increased risk of Guillain-Barré syndrome (incidence rate ratio (IRR), 2.90; 95% confidence interval (CI): 2.15-3.92 at 15-21 days after vaccination) and Bell's palsy (IRR, 1.29; 95% CI: 1.08-1.56 at 15-21 days) with ChAdOx1nCoV-19. There was an increased risk of hemorrhagic stroke (IRR, 1.38; 95% CI: 1.12-1.71 at 15-21 days) with BNT162b2. An independent Scottish cohort provided further support for the association between ChAdOx1nCoV and Guillain-Barré syndrome (IRR, 2.32; 95% CI: 1.08-5.02 at 1-28 days). There was a substantially higher risk of all neurological outcomes in the 28 days after a positive SARS-CoV-2 test including Guillain-Barré syndrome (IRR, 5.25; 95% CI: 3.00-9.18). Overall, we estimated 38 excess cases of Guillain-Barré syndrome per 10 million people receiving ChAdOx1nCoV-19 and 145 excess cases per 10 million people after a positive SARS-CoV-2 test. In summary, although we find an increased risk of neurological complications in those who received COVID-19 vaccines, the risk of these complications is greater following a positive SARS-CoV-2 test.

BACKGROUND: Randomized, controlled cardiovascular outcome trials may not be fully representative of the management of patients with type 2 diabetes across different geographic regions. We conducted analyses of data from the multinational CVD-REAL consortium to determine the association between initiation of sodium-glucose cotransporter-2 inhibitors (SGLT-2i) and cardiovascular outcomes, including subgroup analyses based on patient characteristics. METHODS: De-identified health records from 13 countries across three continents were used to identify patients newly-initiated on SGLT-2i or other glucose-lowering drugs (oGLDs). Propensity scores for SGLT-2i initiation were developed in each country, with 1:1 matching for oGLD initiation. In the matched groups hazard ratios (HRs) for hospitalization for heart failure (HHF), all-cause death (ACD), the composite of HHF or ACD, myocardial infarction (MI) and stroke were estimated by country, and pooled using a weighted meta-analysis. Multiple subgroup analyses were conducted across patient demographic and clinical characteristics to examine any heterogeneity in treatment effects. RESULTS: Following matching, 440,599 new users of SGLT-2i and oGLDs were included in each group. Mean follow-up time was 396 days for SGLT-2i initiation and 406 days for oGLDs initiation. SGLT-2i initiation was associated with a lower risk of HHF (HR: 0.66, 95%CI 0.58-0.75; p < 0.001), ACD (HR: 0.52, 95%CI 0.45-0.60; p < 0.001), the composite of HHF or ACD (HR: 0.60, 95%CI 0.53-0.68; p < 0.001), MI (HR: 0.85, 95%CI 0.78-0.92; p < 0.001), and stroke (HR: 0.78, 95%CI 0.72-0.85; p < 0.001); regardless of patient characteristics, including established cardiovascular disease, or geographic region. CONCLUSIONS: This CVD-REAL study extends the findings from the SGLT-2i clinical trials to the broader setting of an ethnically and geographically diverse population, and across multiple subgroups. Trial registration NCT02993614.

BACKGROUND: Pre-existing comorbidities have been linked to SARS-CoV-2 infection but evidence is sparse on the importance and pattern of multimorbidity (2 or more conditions) and severity of infection indicated by hospitalisation or mortality. We aimed to use a multimorbidity index developed specifically for COVID-19 to investigate the association between multimorbidity and risk of severe SARS-CoV-2 infection. METHODS: We used data from the UK Biobank linked to laboratory confirmed test results for SARS-CoV-2 infection and mortality data from Public Health England between March 16 and July 26, 2020. By reviewing the current literature on COVID-19 we derived a multimorbidity index including: (1) angina; (2) asthma; (3) atrial fibrillation; (4) cancer; (5) chronic kidney disease; (6) chronic obstructive pulmonary disease; (7) diabetes mellitus; (8) heart failure; (9) hypertension; (10) myocardial infarction; (11) peripheral vascular disease; (12) stroke. Adjusted logistic regression models were used to assess the association between multimorbidity and risk of severe SARS-CoV-2 infection (hospitalisation/death). Potential effect modifiers of the association were assessed: age, sex, ethnicity, deprivation, smoking status, body mass index, air pollution, 25-hydroxyvitamin D, cardiorespiratory fitness, high sensitivity C-reactive protein. RESULTS: Among 360,283 participants, the median age was 68 [range 48-85] years, most were White (94.5%), and 1706 had severe SARS-CoV-2 infection. The prevalence of multimorbidity was more than double in those with severe SARS-CoV-2 infection (25%) compared to those without (11%), and clusters of several multimorbidities were more common in those with severe SARS-CoV-2 infection. The most common clusters with severe SARS-CoV-2 infection were stroke with hypertension (79% of those with stroke had hypertension); diabetes and hypertension (72%); and chronic kidney disease and hypertension (68%). Multimorbidity was independently associated wi

INTRODUCTION: Recent evidence suggests that ethnic minority groups are disproportionately at increased risk of hospitalisation and death from SARS-CoV-2 infection. Population-based evidence on potential explanatory factors across minority groups and within subgroups is lacking. This study aims to quantify the association between ethnicity and the risk of hospitalisation and mortality due to COVID-19. METHODS AND ANALYSIS: This is a retrospective cohort study of adults registered across a representative and anonymised national primary care database (QResearch) that includes data on 10 million people in England. Sociodemographic, deprivation, clinical and domicile characteristics will be summarised and compared across ethnic subgroups (categorised as per 2011 census). Cox models will be used to calculate HR for hospitalisation and COVID-19 mortality associated with ethnic group. Potential confounding and explanatory factors (such as demographic, socioeconomic and clinical) will be adjusted for within regression models. The percentage contribution of distinct risk factor classes to the excess risks seen in ethnic groups/subgroups will be calculated. ETHICS AND DISSEMINATION: The study has undergone ethics review in accordance with the QResearch agreement (reference OX102). Findings will be disseminated through peer-reviewed manuscripts, presentations at scientific meetings and conferences with national and international stakeholders.